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2022 Vol. 44, No. 8
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2022, 44(8): 2611-2618.
doi: 10.11999/JEIT220191
Abstract:
Internet of Things (IoT) is a key application of future 6G. However, it is challenging to provide high-quality wireless coverage for billions of IoT devices with limited Radio Frequency (RF) bandwidth. Visible Light Communication (VLC) utilizes abundant ultrahigh bandwidths as complement to RF communication. This paper investigates the Energy Efficiency (EE) of a Simultaneous Lightwave Information and Power Transfer (SLIPT) enabled multi-user VLC system. An EE maximization problem is formulated under constraints of Quality of Service (QoS) requirements of energy harvesting and information rate at users, avoiding clipping distortion by the nonlinearity of the LED and the power budget at VLC transmitter. To solve the considered problem, an iterative algorithm is proposed based on Dinkelbach and successive convex approximation methods to optimize the beamforming vectors and the direct current offset. The convergence of the proposed algorithm is theoretically proved. The impact of the constraint of avoiding clipping distortion by the nonlinearity of the LED on EE is discussed. Simulation results verify the analysis. Moreover, the impacts of QoS requirements of users, the power budget at VLC transmitter and the filed of view of LED on EE are illustrated and analyzed.
Internet of Things (IoT) is a key application of future 6G. However, it is challenging to provide high-quality wireless coverage for billions of IoT devices with limited Radio Frequency (RF) bandwidth. Visible Light Communication (VLC) utilizes abundant ultrahigh bandwidths as complement to RF communication. This paper investigates the Energy Efficiency (EE) of a Simultaneous Lightwave Information and Power Transfer (SLIPT) enabled multi-user VLC system. An EE maximization problem is formulated under constraints of Quality of Service (QoS) requirements of energy harvesting and information rate at users, avoiding clipping distortion by the nonlinearity of the LED and the power budget at VLC transmitter. To solve the considered problem, an iterative algorithm is proposed based on Dinkelbach and successive convex approximation methods to optimize the beamforming vectors and the direct current offset. The convergence of the proposed algorithm is theoretically proved. The impact of the constraint of avoiding clipping distortion by the nonlinearity of the LED on EE is discussed. Simulation results verify the analysis. Moreover, the impacts of QoS requirements of users, the power budget at VLC transmitter and the filed of view of LED on EE are illustrated and analyzed.
2022, 44(8): 2619-2628.
doi: 10.11999/JEIT220026
Abstract:
Facing the development needs of the sixth-generation mobile communication, Visible Light Communication (VLC) is a promising indoor coverage candidate. Due to the open and broadcast features, the information security of VLC can not be ignored. As a novel information security technology, covert wireless communication has been widely investigated in recent years. However, there are significant differences between VLC and radio frequency wireless communication. The results of covert wireless communication can not be directly applied to covert VLC. In view of this, the basic theory of covert VLC is studied in this paper. First, under the constraints of covertness, nonnegativity and average optical power, a functional optimization problem is established. The optimal input distribution is obtained as an exponential distribution, which provides a reference for the signal design of covert VLC. Using the covertness constraint, the condition which should be satisfied by the transmitter’s average optical power is obtained, it provides a basis for the transmitter to set the transmit power. Then, when the transmitter has or has not the knowledge of the warden’s information, the maximum amounts of information that can be covertly transmitted by covert VLC are derived, which reveals the fundamental performance limit of covert VLC. Finally, numerical results verify the theoretical analysis.
Facing the development needs of the sixth-generation mobile communication, Visible Light Communication (VLC) is a promising indoor coverage candidate. Due to the open and broadcast features, the information security of VLC can not be ignored. As a novel information security technology, covert wireless communication has been widely investigated in recent years. However, there are significant differences between VLC and radio frequency wireless communication. The results of covert wireless communication can not be directly applied to covert VLC. In view of this, the basic theory of covert VLC is studied in this paper. First, under the constraints of covertness, nonnegativity and average optical power, a functional optimization problem is established. The optimal input distribution is obtained as an exponential distribution, which provides a reference for the signal design of covert VLC. Using the covertness constraint, the condition which should be satisfied by the transmitter’s average optical power is obtained, it provides a basis for the transmitter to set the transmit power. Then, when the transmitter has or has not the knowledge of the warden’s information, the maximum amounts of information that can be covertly transmitted by covert VLC are derived, which reveals the fundamental performance limit of covert VLC. Finally, numerical results verify the theoretical analysis.
2022, 44(8): 2629-2638.
doi: 10.11999/JEIT220294
Abstract:
In optical camera communication, the classical polynomial fitting algorithm is easy to lose the stripe detail information, the segmentation-based adaptive threshold algorithm can decode the gray value data effectively, but it is time-consuming, and the step size selection has great impact on the decoding performance. To address the above problems, an exponentially weighted filtering algorithm that can ensure the influence of neighboring pixel rows and is relatively smooth is proposed, and it is combined with reference stripes to achieve fast demodulation and decoding. In the decoding process, firstly, the number of pixels is estimated for each light and dark stripe to determine the position of the frame synchronization head and frame tail; Then the frame synchronization head and frame tail are used to determine the range of valid data and estimate the number of pixels corresponding to each bit of data; After that, the duty cycle of valid data is determined and converted into logical values; Finally, the information represented by logical values is output. The experimental results show that the proposed algorithm has low algorithm complexity, and the channel distance can reach 30 cm and the transmission rate is 1.67 kbps in the indoor environment with 300 lx illumination when using a square LED as the transmitter under the condition that the false bit rate is lower than the forward error correction threshold, which can meet the normal transmission requirements..
In optical camera communication, the classical polynomial fitting algorithm is easy to lose the stripe detail information, the segmentation-based adaptive threshold algorithm can decode the gray value data effectively, but it is time-consuming, and the step size selection has great impact on the decoding performance. To address the above problems, an exponentially weighted filtering algorithm that can ensure the influence of neighboring pixel rows and is relatively smooth is proposed, and it is combined with reference stripes to achieve fast demodulation and decoding. In the decoding process, firstly, the number of pixels is estimated for each light and dark stripe to determine the position of the frame synchronization head and frame tail; Then the frame synchronization head and frame tail are used to determine the range of valid data and estimate the number of pixels corresponding to each bit of data; After that, the duty cycle of valid data is determined and converted into logical values; Finally, the information represented by logical values is output. The experimental results show that the proposed algorithm has low algorithm complexity, and the channel distance can reach 30 cm and the transmission rate is 1.67 kbps in the indoor environment with 300 lx illumination when using a square LED as the transmitter under the condition that the false bit rate is lower than the forward error correction threshold, which can meet the normal transmission requirements..
Spectrum-Efficient Hybrid Modulation Based on VOOK and Layered OFDM for Visible Light Communications
2022, 44(8): 2639-2648.
doi: 10.11999/JEIT220368
Abstract:
In order to satisfy the requirements of illumination and high-speed transmission in Visible Light Communications (VLC), a novel spectrum-efficient hybrid modulation based on Variable On-Off Keying (VOOK) and layered Orthogonal Frequency Division Multiplexing (OFDM) is proposed in this paper. First, the VOOK signal is designed to avoid the interference with the layered OFDM transmission. In order to ensure that the hybrid signal operates in the linear dynamic range of Light-Emitting Diode (LED), a novel Reconstructed Layered Optical OFDM (RLO-OFDM) is further conceived. Then, the RLO-OFDM and VOOK signals are combined for simultaneous transmission to realize the dual functionalities of dimming control and spectrum-efficient data transmission. At the receiver side, the VOOK and RLO-OFDM signals are detected in parallel. Moreover, a standard OFDM receiver can be directly employed to detect the RLO-OFDM signal without requiring successive interference cancellation, which reduces notably the receiver complexity and processing latency. Simulation results show that the proposed scheme is capable of supporting the linear dimming control, and achieving high spectrum efficiency.
In order to satisfy the requirements of illumination and high-speed transmission in Visible Light Communications (VLC), a novel spectrum-efficient hybrid modulation based on Variable On-Off Keying (VOOK) and layered Orthogonal Frequency Division Multiplexing (OFDM) is proposed in this paper. First, the VOOK signal is designed to avoid the interference with the layered OFDM transmission. In order to ensure that the hybrid signal operates in the linear dynamic range of Light-Emitting Diode (LED), a novel Reconstructed Layered Optical OFDM (RLO-OFDM) is further conceived. Then, the RLO-OFDM and VOOK signals are combined for simultaneous transmission to realize the dual functionalities of dimming control and spectrum-efficient data transmission. At the receiver side, the VOOK and RLO-OFDM signals are detected in parallel. Moreover, a standard OFDM receiver can be directly employed to detect the RLO-OFDM signal without requiring successive interference cancellation, which reduces notably the receiver complexity and processing latency. Simulation results show that the proposed scheme is capable of supporting the linear dimming control, and achieving high spectrum efficiency.
2022, 44(8): 2649-2658.
doi: 10.11999/JEIT210953
Abstract:
In order to study the multi-functional photon integrated chip for visible light communication and realize the integrated function of visible light signal emission, detection, transmission and power distribution, a miniature Light Emitting Diode(LED) with splitter structure based on silicon-based InGaN/GaN multiple quantum well material is proposed in this paper. The photon integrated chip is characterized in many aspects, such as morphology, optoelectronic characteristics and visible light communication test. The effective transmission of visible light signal and different proportion of multi-port power shunt are realized, and the output light intensity of different ports of the splitter is quantified. Finally, the rectangular wave signal of 300 kHz is loaded at the emitter end of the miniature LED light source by the signal generator, and the modulated visible light signal emitted at the end of the splitter is collected. The waveform change trend of the input / receive signal is the same. It shows that the photonic integrated chip can achieve effective visible light communication. The main purpose of this study is to try to integrate visible light sources and photodetectors on nitride wafers, so as to provide new research ideas and schemes for on-chip integrated processing of visible light signals in all-optical networks of visible light communications. It provides more possibilities for the development of multi-function photon integrated chip terminals for visible light communication networks.
In order to study the multi-functional photon integrated chip for visible light communication and realize the integrated function of visible light signal emission, detection, transmission and power distribution, a miniature Light Emitting Diode(LED) with splitter structure based on silicon-based InGaN/GaN multiple quantum well material is proposed in this paper. The photon integrated chip is characterized in many aspects, such as morphology, optoelectronic characteristics and visible light communication test. The effective transmission of visible light signal and different proportion of multi-port power shunt are realized, and the output light intensity of different ports of the splitter is quantified. Finally, the rectangular wave signal of 300 kHz is loaded at the emitter end of the miniature LED light source by the signal generator, and the modulated visible light signal emitted at the end of the splitter is collected. The waveform change trend of the input / receive signal is the same. It shows that the photonic integrated chip can achieve effective visible light communication. The main purpose of this study is to try to integrate visible light sources and photodetectors on nitride wafers, so as to provide new research ideas and schemes for on-chip integrated processing of visible light signals in all-optical networks of visible light communications. It provides more possibilities for the development of multi-function photon integrated chip terminals for visible light communication networks.
2022, 44(8): 2659-2665.
doi: 10.11999/JEIT220142
Abstract:
The robust beamforming design for the aggregated Visible Light Communication (VLC) and Radio Frequency (RF) system are studied for the first time. Specifically, with imperfect Channel State Informations (CSIs) of both VLC and RF channels, robust beam formers design schemes are proposed to minimize the transmit power of the aggregated VLC-RF system, while satisfying both the minimum rate requirements and dimming control constraints. However, there are infinite constraints of the robust beamforming design problem, which is intractable in general. Through Semi-Definite Relaxation (SDR), the non-convex original problem is relaxed firstly, and then conservative reformulated it into a convex Semi-Definite Program (SDP) by exploiting\begin{document}$\mathcal{S}$\end{document} ![]()
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The robust beamforming design for the aggregated Visible Light Communication (VLC) and Radio Frequency (RF) system are studied for the first time. Specifically, with imperfect Channel State Informations (CSIs) of both VLC and RF channels, robust beam formers design schemes are proposed to minimize the transmit power of the aggregated VLC-RF system, while satisfying both the minimum rate requirements and dimming control constraints. However, there are infinite constraints of the robust beamforming design problem, which is intractable in general. Through Semi-Definite Relaxation (SDR), the non-convex original problem is relaxed firstly, and then conservative reformulated it into a convex Semi-Definite Program (SDP) by exploiting
2022, 44(8): 2666-2676.
doi: 10.11999/JEIT220379
Abstract:
The system Ergodic Sum Rate (ESR) performance of a mixed Free Space Optical/ Radio Frequency (FSO/RF) Satellite-Aerial-Terrestrial Integrated Network (SATIN) combining multi-antenna beamforming scheme and uplink Non-Orthogonal Multiple Access (NOMA) technology is investigated in this paper. Firstly, a beamforming scheme using statistical channel state information is proposed to maximize the ESR of the considered system, where multi-antenna UAV is deployed with uplink NOMA technology. Secondly, under the assumption that the satellite-UAV link with FSO undergoes Gamma-Gamma fading while the UAV-terrestrial links adopted RF experience correlated Rayleigh fading, the closed-form expression for ESR of the considered SATIN is derived. Finally, numerical results are provided to validate the theoretical analysis. The simulation results show that, compared with the Orthogonal Multiple Access (OMA) scheme, the proposed scheme improves the system ESR, and the proposed scheme has the performance superiority over the other benchmark beamforming scheme.
The system Ergodic Sum Rate (ESR) performance of a mixed Free Space Optical/ Radio Frequency (FSO/RF) Satellite-Aerial-Terrestrial Integrated Network (SATIN) combining multi-antenna beamforming scheme and uplink Non-Orthogonal Multiple Access (NOMA) technology is investigated in this paper. Firstly, a beamforming scheme using statistical channel state information is proposed to maximize the ESR of the considered system, where multi-antenna UAV is deployed with uplink NOMA technology. Secondly, under the assumption that the satellite-UAV link with FSO undergoes Gamma-Gamma fading while the UAV-terrestrial links adopted RF experience correlated Rayleigh fading, the closed-form expression for ESR of the considered SATIN is derived. Finally, numerical results are provided to validate the theoretical analysis. The simulation results show that, compared with the Orthogonal Multiple Access (OMA) scheme, the proposed scheme improves the system ESR, and the proposed scheme has the performance superiority over the other benchmark beamforming scheme.
2022, 44(8): 2677-2685.
doi: 10.11999/JEIT211568
Abstract:
The popularity of Light-Emitting Diode (LED) lighting provides a green and low-cost solution for high-accuracy indoor positioning. As the most economical LED modulation method, On-Off Keying (OOK) has poor positioning accuracy due to the defects of switching speed, response time, and synchronization between nodes. In this paper, an indoor positioning beacon based on the new OOK coded pulse-pair and its corresponding asynchronous visible light positioning model is proposed. Herein, each LED only needs to perform OOK according to the proposed rules, and the optimal position of the PhotoDetector (PD) terminal under the maximum posterior probability criterion can be estimated. It is verified that when the channel (including LED and receiver) has ideal bandwidth, 200 MHz, and 100 MHz bandwidth, the terminal can achieve a positioning accuracy of 6 mm, 7 mm, and 1 cm with a 90% probability under the condition of 30 dB Signal-to-Noise Ratio (SNR). Under the same conditions, compared with asynchronous Code Division Multiple Access (CDMA) positioning, traditional OOK positioning based on fingerprint and traditional OOK positioning based on received signal strength, the proposed method in this paper can get a significantly better positioning effect. In addition, when the SNR deteriorates from 30 dB to 15 dB, the positioning accuracy of the terminal can also be robustly maintained in the order of centimeters.
The popularity of Light-Emitting Diode (LED) lighting provides a green and low-cost solution for high-accuracy indoor positioning. As the most economical LED modulation method, On-Off Keying (OOK) has poor positioning accuracy due to the defects of switching speed, response time, and synchronization between nodes. In this paper, an indoor positioning beacon based on the new OOK coded pulse-pair and its corresponding asynchronous visible light positioning model is proposed. Herein, each LED only needs to perform OOK according to the proposed rules, and the optimal position of the PhotoDetector (PD) terminal under the maximum posterior probability criterion can be estimated. It is verified that when the channel (including LED and receiver) has ideal bandwidth, 200 MHz, and 100 MHz bandwidth, the terminal can achieve a positioning accuracy of 6 mm, 7 mm, and 1 cm with a 90% probability under the condition of 30 dB Signal-to-Noise Ratio (SNR). Under the same conditions, compared with asynchronous Code Division Multiple Access (CDMA) positioning, traditional OOK positioning based on fingerprint and traditional OOK positioning based on received signal strength, the proposed method in this paper can get a significantly better positioning effect. In addition, when the SNR deteriorates from 30 dB to 15 dB, the positioning accuracy of the terminal can also be robustly maintained in the order of centimeters.
2022, 44(8): 2686-2694.
doi: 10.11999/JEIT220027
Abstract:
The traditional Direct Current (DC) biased offset Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM) system obtains a unipolar signal by adding a DC offset and limiting amplitude. Due to the randomness of the Inverse Discrete Fourier Transform (IDFT) output time domain signal, a fixed DC offset will produce larger non-linear limiting distortion. It is proposed to design an Adaptive DC offset Optical OFDM (ADCO-OFDM) system to minimize the Mean Square Error (MSE) between the symbols before and after bilateral clipping as the optimization objective, and to solve the DC that minimizes nonlinear clipping distortion. The principle of the ADCO-OFDM system is introduced, the Signal-to-Noise Ratio (SNR) of sub-carrier bits is deduced, an optimization model for minimizing the mean square error is established, and the process of solving the optimal DC offset is given. The Monte Carlo simulation method is used to analyze the Bit Error Rate (BER) and optical power consumption, which verifies the correctness of the system design and performance analysis.
The traditional Direct Current (DC) biased offset Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM) system obtains a unipolar signal by adding a DC offset and limiting amplitude. Due to the randomness of the Inverse Discrete Fourier Transform (IDFT) output time domain signal, a fixed DC offset will produce larger non-linear limiting distortion. It is proposed to design an Adaptive DC offset Optical OFDM (ADCO-OFDM) system to minimize the Mean Square Error (MSE) between the symbols before and after bilateral clipping as the optimization objective, and to solve the DC that minimizes nonlinear clipping distortion. The principle of the ADCO-OFDM system is introduced, the Signal-to-Noise Ratio (SNR) of sub-carrier bits is deduced, an optimization model for minimizing the mean square error is established, and the process of solving the optimal DC offset is given. The Monte Carlo simulation method is used to analyze the Bit Error Rate (BER) and optical power consumption, which verifies the correctness of the system design and performance analysis.
2022, 44(8): 2695-2702.
doi: 10.11999/JEIT210758
Abstract:
Optical communication technology using visible optical signal as a new information carrier is greatly developed in recent years. In order to develop a new generation of photonic integrated chip as a terminal device of the visible optical communication network, to meet the composite requirements of the visible optical signal transmission,reception, transmission and processing. Based on the silicon-based InGaN/GaN multi-quantum well material, a composite photon integrated chip integrating visible band micro Light-Emitting Diode (LED) light source, waveguide directional coupler and micro photodetector is designed. A luminescence detection coexistence phenomenon of a InGaN/GaN multi-quantum well material is used in this chip to achieve the above composite function. As the transmitting end, the micro LED light source can emit the blue band visible light signal. Its luminous intensity is linear modulated by the injection current, which can realize the amplitude modulation visible light communication, which is suitable for the transmitting end of visible light communication. The visible light signal transmitted by the micro LED light source is transmitted into the waveguide directional coupler, which realizes the effective in-chip transmission coupling and the average optical power distribution of the chip. After the visible light signal passed through the coupled transmission enters the microphotodetector, a photocurrent matching the intensity of the coupled transmitted light signal can be monitored. Finally, effective visible light communication of this chip is also confirmed by visible light communication testing. It provides more possibilities for developing composite functional photon integrated chip terminals facing the needs of visible optical communication networks through this reserach.
Optical communication technology using visible optical signal as a new information carrier is greatly developed in recent years. In order to develop a new generation of photonic integrated chip as a terminal device of the visible optical communication network, to meet the composite requirements of the visible optical signal transmission,reception, transmission and processing. Based on the silicon-based InGaN/GaN multi-quantum well material, a composite photon integrated chip integrating visible band micro Light-Emitting Diode (LED) light source, waveguide directional coupler and micro photodetector is designed. A luminescence detection coexistence phenomenon of a InGaN/GaN multi-quantum well material is used in this chip to achieve the above composite function. As the transmitting end, the micro LED light source can emit the blue band visible light signal. Its luminous intensity is linear modulated by the injection current, which can realize the amplitude modulation visible light communication, which is suitable for the transmitting end of visible light communication. The visible light signal transmitted by the micro LED light source is transmitted into the waveguide directional coupler, which realizes the effective in-chip transmission coupling and the average optical power distribution of the chip. After the visible light signal passed through the coupled transmission enters the microphotodetector, a photocurrent matching the intensity of the coupled transmitted light signal can be monitored. Finally, effective visible light communication of this chip is also confirmed by visible light communication testing. It provides more possibilities for developing composite functional photon integrated chip terminals facing the needs of visible optical communication networks through this reserach.
2022, 44(8): 2703-2709.
doi: 10.11999/JEIT220328
Abstract:
Ultrathin vertical-structure GaN Light Emitting Diode (LED) that can enhance light extraction efficiency as well as modulation bandwidth is a key optical element for visible light communication. In order to meet the requirement of underwater blue light communication, vertical-structure blue LED is designed and fabricated according to subwavelength vertical structure LED model. The fabricated vertical-structure LED can achieve a transmission rate of 10 Mbps under the NRZ-OOK modulation scheme. Furthermore,this vertical-structure LED is used to establish an underwater blue light communication system, which can achieve a full-duplex data communication with a modulation rate of 2 Mbps.
Ultrathin vertical-structure GaN Light Emitting Diode (LED) that can enhance light extraction efficiency as well as modulation bandwidth is a key optical element for visible light communication. In order to meet the requirement of underwater blue light communication, vertical-structure blue LED is designed and fabricated according to subwavelength vertical structure LED model. The fabricated vertical-structure LED can achieve a transmission rate of 10 Mbps under the NRZ-OOK modulation scheme. Furthermore,this vertical-structure LED is used to establish an underwater blue light communication system, which can achieve a full-duplex data communication with a modulation rate of 2 Mbps.
2022, 44(8): 2710-2716.
doi: 10.11999/JEIT220112
Abstract:
DC-bias Optical-Orthogonal Frequency Division Multiplexing (DCO-OFDM) has a high Peak-to-Average Power Ratio (PAPR) and is susceptible to multipath interference and noise frequency bias. To address this challenge, carrier Index Modulation (IM) is introduced into DCO-OFDM and a DCO-OFDM-IM modulation scheme suitable for visible light communication is proposed. In this scheme, the signal mapping constraint model bases on the combination of composite index and Euclidian distance is used to perform block composite index of subcarriers, which can not only transfer information using traditional constellation modulation in the signal domain, but also carry additional information through the carrier index in the frequency domain, which improves effectively the system peak to average ratio and bit error rate performance. The theoretical bit error rate of DCO-OFDM-IM system is derived and verified by monte Carlo method. The results show that compared with traditional DCO-OFDM system, when the number of subcarriers is 256, the modulation order is 4, and the system bit error rate is 10–3, the required Signal-to-Noise Ratio (SNR) of DCO-OFDM-IM system is improved by about 2 dB on average. When the BER is 10–3, the required SNR of the combined index and Euclidian distance algorithm improved by 2 dB on average compared with the random carrier combination system. When the system Complementary Cumulative Distribution Function (CCDF) is 10–1, the average ratio of the original signal peaks of DCO-OFDM-IM is decreased by about 2.4 dB compared with that of DCO-OFDM.
DC-bias Optical-Orthogonal Frequency Division Multiplexing (DCO-OFDM) has a high Peak-to-Average Power Ratio (PAPR) and is susceptible to multipath interference and noise frequency bias. To address this challenge, carrier Index Modulation (IM) is introduced into DCO-OFDM and a DCO-OFDM-IM modulation scheme suitable for visible light communication is proposed. In this scheme, the signal mapping constraint model bases on the combination of composite index and Euclidian distance is used to perform block composite index of subcarriers, which can not only transfer information using traditional constellation modulation in the signal domain, but also carry additional information through the carrier index in the frequency domain, which improves effectively the system peak to average ratio and bit error rate performance. The theoretical bit error rate of DCO-OFDM-IM system is derived and verified by monte Carlo method. The results show that compared with traditional DCO-OFDM system, when the number of subcarriers is 256, the modulation order is 4, and the system bit error rate is 10–3, the required Signal-to-Noise Ratio (SNR) of DCO-OFDM-IM system is improved by about 2 dB on average. When the BER is 10–3, the required SNR of the combined index and Euclidian distance algorithm improved by 2 dB on average compared with the random carrier combination system. When the system Complementary Cumulative Distribution Function (CCDF) is 10–1, the average ratio of the original signal peaks of DCO-OFDM-IM is decreased by about 2.4 dB compared with that of DCO-OFDM.
2022, 44(8): 2717-2724.
doi: 10.11999/JEIT220366
Abstract:
As one of the promising candidates of the next-generation network, Visible Light Communication (VLC) is expected to provide a strict delay QoS guarantee because of its high transmission rate. In the existing research of the VLC field, most of them assume that the direction of terminals is always vertically upward during the whole process of receiving signals. However, in a practical VLC system, the terminal rotation has considerable impacts on the angle of incidence and then affects the channel gain and transmission rate of VLC. In this paper, the achievable transmission rate of rotated terminals with the delay QoS constraint for the multi-source VLC system is investigated. Firstly, based on the three-dimension discrete-time Markov chain, a rotation model for the VLC terminal is proposed, which depicts the random rotation process of the VLC terminal from the perspective of temporal correlation. Secondly, the vectored transmission process of rotated terminals is mapped into Markov service process. Based on the effective capacity theory, the achievable transmission rate with the statistical delay QoS constraint for VLC system supporting terminal rotation is investigated. Finally, simulation results manifest significant rotation impacts on the VLC system capacity and the accuracy of the derived effective capacity.
As one of the promising candidates of the next-generation network, Visible Light Communication (VLC) is expected to provide a strict delay QoS guarantee because of its high transmission rate. In the existing research of the VLC field, most of them assume that the direction of terminals is always vertically upward during the whole process of receiving signals. However, in a practical VLC system, the terminal rotation has considerable impacts on the angle of incidence and then affects the channel gain and transmission rate of VLC. In this paper, the achievable transmission rate of rotated terminals with the delay QoS constraint for the multi-source VLC system is investigated. Firstly, based on the three-dimension discrete-time Markov chain, a rotation model for the VLC terminal is proposed, which depicts the random rotation process of the VLC terminal from the perspective of temporal correlation. Secondly, the vectored transmission process of rotated terminals is mapped into Markov service process. Based on the effective capacity theory, the achievable transmission rate with the statistical delay QoS constraint for VLC system supporting terminal rotation is investigated. Finally, simulation results manifest significant rotation impacts on the VLC system capacity and the accuracy of the derived effective capacity.
2022, 44(8): 2725-2729.
doi: 10.11999/JEIT211559
Abstract:
Integrated communication and sensing is an emerging technology towards 6G. Since there is a spectral emission-detection overlap of GaN QW(Quantum Well) diode, GaN-based photodiode can absorb short-wavelength light photons emitted from another light-emitting diode sharing identical QW structure to generate photocurrent, offering the coexistence of emission, sensing and communication functionalities. Based on this intriguing phenomenon and because single QW diode chip has a weak external light signal sensing due to its luminous interference and the transceiver separation chips have some problems, such as low efficiency, weak compactness and poor robustness, this paper monolithically integrate GaN-based transmitter and receiver into a single chip, wherein they share identical QW structure and are fabricated using the same process flow. Asymmetric optical links are thus established using monolithic GaN optoelectronic chip, opening a feasible route to develop integrated visible light communication and sensing technology.
Integrated communication and sensing is an emerging technology towards 6G. Since there is a spectral emission-detection overlap of GaN QW(Quantum Well) diode, GaN-based photodiode can absorb short-wavelength light photons emitted from another light-emitting diode sharing identical QW structure to generate photocurrent, offering the coexistence of emission, sensing and communication functionalities. Based on this intriguing phenomenon and because single QW diode chip has a weak external light signal sensing due to its luminous interference and the transceiver separation chips have some problems, such as low efficiency, weak compactness and poor robustness, this paper monolithically integrate GaN-based transmitter and receiver into a single chip, wherein they share identical QW structure and are fabricated using the same process flow. Asymmetric optical links are thus established using monolithic GaN optoelectronic chip, opening a feasible route to develop integrated visible light communication and sensing technology.
2022, 44(8): 2730-2738.
doi: 10.11999/JEIT210600
Abstract:
Physical layer security is effective to solve the problem of communication security of Internet of Things (IoT). As a full duplex eavesdropper with active attack and passive eavesdropping exists in the IoT, Unmanned Aerial Vehicle (UAV) transmits artificial noise to the eavesdropper for improving secrecy performance in this paper. Based on estimating eavesdropper position, a trajectory optimization algorithm based on Q-learning is proposed to track the eavesdropper mobility and obtain the optimal secrecy performance. The results show that the proposed algorithm converges quickly. UAV can track the eavesdropper mobility to determine the best position of jamming the eavesdropping channel, which guarantees maximum achievable secrecy rate.
Physical layer security is effective to solve the problem of communication security of Internet of Things (IoT). As a full duplex eavesdropper with active attack and passive eavesdropping exists in the IoT, Unmanned Aerial Vehicle (UAV) transmits artificial noise to the eavesdropper for improving secrecy performance in this paper. Based on estimating eavesdropper position, a trajectory optimization algorithm based on Q-learning is proposed to track the eavesdropper mobility and obtain the optimal secrecy performance. The results show that the proposed algorithm converges quickly. UAV can track the eavesdropper mobility to determine the best position of jamming the eavesdropping channel, which guarantees maximum achievable secrecy rate.
2022, 44(8): 2739-2748.
doi: 10.11999/JEIT210540
Abstract:
Many physical phenomena can be described by the diffusion equations, such as the emission of chimney pollutants, chemical substance leakage, etc. Therefore, the estimation of diffusion source parameters is of great significance in practical applications. Currently, most of the proposed methods for estimating parameters of diffusion sources are aimed at instantaneous point source signals. For non-instantaneous actual diffusion processes, there is a problem of model mismatch. In this paper, the diffusion source model is extended to variable pulse-width signals, and the parameter estimation algorithm of corresponding non-instantaneous point sources are proposed. In this algorithm, the actual measurement value is obtained by sampling with the wireless sensor network, a combination coefficient is found to combine linearly the actual measurement value into an exponential function, and then the combined data is analyzed according to the Finite Rate of Innovation (FRI) sampling theory by using the annihilation filter method to solve the diffusion source parameters. The simulation results analyze the performance factors that affect parameter recovery, including noise, the number of sensors, etc., and the accuracy of the non-instantaneous diffusion point source parameter estimation method is validated.
Many physical phenomena can be described by the diffusion equations, such as the emission of chimney pollutants, chemical substance leakage, etc. Therefore, the estimation of diffusion source parameters is of great significance in practical applications. Currently, most of the proposed methods for estimating parameters of diffusion sources are aimed at instantaneous point source signals. For non-instantaneous actual diffusion processes, there is a problem of model mismatch. In this paper, the diffusion source model is extended to variable pulse-width signals, and the parameter estimation algorithm of corresponding non-instantaneous point sources are proposed. In this algorithm, the actual measurement value is obtained by sampling with the wireless sensor network, a combination coefficient is found to combine linearly the actual measurement value into an exponential function, and then the combined data is analyzed according to the Finite Rate of Innovation (FRI) sampling theory by using the annihilation filter method to solve the diffusion source parameters. The simulation results analyze the performance factors that affect parameter recovery, including noise, the number of sensors, etc., and the accuracy of the non-instantaneous diffusion point source parameter estimation method is validated.
2022, 44(8): 2749-2756.
doi: 10.11999/JEIT210571
Abstract:
Focusing on problems of Non-Orthogonal Multiple Access (NOMA) that are limited to linear modulation, and considering the imperfect Channel State Information (CSI) in the actual system, this paper proposes a nonlinear waveform NOMA system under imperfect CSI based on Minimum Shift Keying type (MSK-type) modulations. First, two-user uplink asynchronous and synchronous system models are established using oversampling and matched filtering techniques. Furthermore, based on the matrix decomposition theory and Successive Interference Cancellation (SIC) mechanism, the transmit power and normalized delay when the system throughput reaches the maximum under perfect or imperfect CSI are derived. Finally, the numerical simulation results show the relationship between system throughput and system parameters such as frame length, response length, waveform, and frequency pulse under perfect and imperfect CSI.
Focusing on problems of Non-Orthogonal Multiple Access (NOMA) that are limited to linear modulation, and considering the imperfect Channel State Information (CSI) in the actual system, this paper proposes a nonlinear waveform NOMA system under imperfect CSI based on Minimum Shift Keying type (MSK-type) modulations. First, two-user uplink asynchronous and synchronous system models are established using oversampling and matched filtering techniques. Furthermore, based on the matrix decomposition theory and Successive Interference Cancellation (SIC) mechanism, the transmit power and normalized delay when the system throughput reaches the maximum under perfect or imperfect CSI are derived. Finally, the numerical simulation results show the relationship between system throughput and system parameters such as frame length, response length, waveform, and frequency pulse under perfect and imperfect CSI.
2022, 44(8): 2757-2766.
doi: 10.11999/JEIT210663
Abstract:
In order to improve the performance of Wi-Fi fingerprint indoor positioning technology, a method based on Convolutional Neural Networks (CNN) for Channel State Information (CSI) fingerprint indoor positioning is first proposed. This method combines the CSI amplitude difference and phase difference information to train the CNN model in the offline stage. Positioning experiments are carried out in two different indoor positioning scenarios in the gallery and the laboratory, and the average positioning errors of 25 cm and 48 cm are obtained respectively; Then, on this basis, the focus is on improving the timeliness of CNN-based CSI indoor positioning. The Convolutional AutoEncoder (CAE) is introduced to realize the dimensionality reduction processing of CSI. Under the premise of ensuring the accuracy of the original positioning method, the positioning time is increased by 40% and the memory consumption is reduced to 1/15 of the original algorithm. The experimental results verify the effectiveness of the proposed algorithm.
In order to improve the performance of Wi-Fi fingerprint indoor positioning technology, a method based on Convolutional Neural Networks (CNN) for Channel State Information (CSI) fingerprint indoor positioning is first proposed. This method combines the CSI amplitude difference and phase difference information to train the CNN model in the offline stage. Positioning experiments are carried out in two different indoor positioning scenarios in the gallery and the laboratory, and the average positioning errors of 25 cm and 48 cm are obtained respectively; Then, on this basis, the focus is on improving the timeliness of CNN-based CSI indoor positioning. The Convolutional AutoEncoder (CAE) is introduced to realize the dimensionality reduction processing of CSI. Under the premise of ensuring the accuracy of the original positioning method, the positioning time is increased by 40% and the memory consumption is reduced to 1/15 of the original algorithm. The experimental results verify the effectiveness of the proposed algorithm.
2022, 44(8): 2767-2776.
doi: 10.11999/JEIT210535
Abstract:
The information transmission process in Device to Device (D2D) communications is not only affected by physical communication conditions but also closely related to the dynamic properties of users. To explore the internal relationship between information transmission and user awareness diffusion, they are regarded as two propagation processes, and the interprocess interaction factors are introduced to describe the interaction in this paper. Furthermore, a coupling propagation dynamical model of information and user awareness is established and analyzed comprehensively. Specifically, the existence and uniqueness of the equilibrium and its global stability are proved through theoretical analysis, which reveals the final state of coupling propagation between information and user awareness in D2D communications. The theoretical results are also verified by experimental analysis. Meanwhile, compared with the traditional model and the propagation model without considering the interaction of process, the scale of information propagation can be expanded and the information propagation process can be described more accurately by the proposed model.
The information transmission process in Device to Device (D2D) communications is not only affected by physical communication conditions but also closely related to the dynamic properties of users. To explore the internal relationship between information transmission and user awareness diffusion, they are regarded as two propagation processes, and the interprocess interaction factors are introduced to describe the interaction in this paper. Furthermore, a coupling propagation dynamical model of information and user awareness is established and analyzed comprehensively. Specifically, the existence and uniqueness of the equilibrium and its global stability are proved through theoretical analysis, which reveals the final state of coupling propagation between information and user awareness in D2D communications. The theoretical results are also verified by experimental analysis. Meanwhile, compared with the traditional model and the propagation model without considering the interaction of process, the scale of information propagation can be expanded and the information propagation process can be described more accurately by the proposed model.
2022, 44(8): 2777-2784.
doi: 10.11999/JEIT210520
Abstract:
With the continuous rise of high-speed services such as high-definition video live broadcast and virtual reality, it is difficult for a single network to meet the business needs of users. Using a variety of heterogeneous links to achieve concurrent transmission can effectively aggregate bandwidth resources and improve the quality of service. However, in heterogeneous wireless networks, due to the complex link conditions and the different quality of multiple links, the existing multi-path concurrent transmission algorithms can not make the optimal decision adaptively according to the complex network conditions. In this paper, a multi-path concurrent transmission control algorithm based on adaptive network coding is proposed. The Asynchronous Advanced Actor Critical (A3C) reinforcement learning is introduced. Through adaptive network coding, the coding packet size and redundancy size can be intelligently selected according to the current network conditions, so as to solve the problem of disordered packet. Simulation results show that the algorithm can improve the transmission rate by about 10% and improve the user experience.
With the continuous rise of high-speed services such as high-definition video live broadcast and virtual reality, it is difficult for a single network to meet the business needs of users. Using a variety of heterogeneous links to achieve concurrent transmission can effectively aggregate bandwidth resources and improve the quality of service. However, in heterogeneous wireless networks, due to the complex link conditions and the different quality of multiple links, the existing multi-path concurrent transmission algorithms can not make the optimal decision adaptively according to the complex network conditions. In this paper, a multi-path concurrent transmission control algorithm based on adaptive network coding is proposed. The Asynchronous Advanced Actor Critical (A3C) reinforcement learning is introduced. Through adaptive network coding, the coding packet size and redundancy size can be intelligently selected according to the current network conditions, so as to solve the problem of disordered packet. Simulation results show that the algorithm can improve the transmission rate by about 10% and improve the user experience.
2022, 44(8): 2785-2791.
doi: 10.11999/JEIT210543
Abstract:
The 3rd Generation Partnership Project (3GPP) mode 4 provides a direct communication mode to support the C-V2X applications. However, the dynamic traffic load and vehicle mobility lead to uncertainty of channel quality with serious packet collision problem. In order to meet the demand of ultra reliability and low latency of V2X communication. A Reservation-Reuse Combined Q-learning Semi Persistent Scheduling (RRC-QSPS) algorithm is proposed for efficient distributed resource allocation in dynamic load environment. Firstly, the theoretical model of the collision probability of Semi Persistent Scheduling (SPS) algorithm is built. Then, the Q-learning model of vehicle agent in dynamic load environment is proposed with the reservation-reuse combined action and Q function. By using\begin{document}$ \varepsilon $\end{document} ![]()
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The 3rd Generation Partnership Project (3GPP) mode 4 provides a direct communication mode to support the C-V2X applications. However, the dynamic traffic load and vehicle mobility lead to uncertainty of channel quality with serious packet collision problem. In order to meet the demand of ultra reliability and low latency of V2X communication. A Reservation-Reuse Combined Q-learning Semi Persistent Scheduling (RRC-QSPS) algorithm is proposed for efficient distributed resource allocation in dynamic load environment. Firstly, the theoretical model of the collision probability of Semi Persistent Scheduling (SPS) algorithm is built. Then, the Q-learning model of vehicle agent in dynamic load environment is proposed with the reservation-reuse combined action and Q function. By using
2022, 44(8): 2792-2801.
doi: 10.11999/JEIT210450
Abstract:
In ultra-dense heterogeneous wireless networks with malicious terminals, a Vertical Handover Algorithm Considering Terminal Security and Resource Scheduling (CTSRS-VHA) is proposed to solve the problem of low resource allocation efficiency and congestion caused by high concurrent access requests. Firstly, the terminal security evaluation model is built on the network side through the attack detection algorithm based on the finite state machine, and the terminal security degree is calculated. Secondly, a multi-objective optimization function is constructed based on network congestion, user data transmission rate and terminal security degree. Thirdly, by analyzing the comprehensive benefits between the network and the terminal, the multi-objective optimization function is converted into a single objective optimization function, and the solution is proved to be Pareto optimal. Finally, the simulation results and analysis show that the proposed algorithm can improve the network access security level and total throughput, and reduce the network congestion and handover failure rate.
In ultra-dense heterogeneous wireless networks with malicious terminals, a Vertical Handover Algorithm Considering Terminal Security and Resource Scheduling (CTSRS-VHA) is proposed to solve the problem of low resource allocation efficiency and congestion caused by high concurrent access requests. Firstly, the terminal security evaluation model is built on the network side through the attack detection algorithm based on the finite state machine, and the terminal security degree is calculated. Secondly, a multi-objective optimization function is constructed based on network congestion, user data transmission rate and terminal security degree. Thirdly, by analyzing the comprehensive benefits between the network and the terminal, the multi-objective optimization function is converted into a single objective optimization function, and the solution is proved to be Pareto optimal. Finally, the simulation results and analysis show that the proposed algorithm can improve the network access security level and total throughput, and reduce the network congestion and handover failure rate.
2022, 44(8): 2802-2813.
doi: 10.11999/JEIT210533
Abstract:
To solve the problem of low efficiency for multiple-hop adaptive time synchronization in Wireless Sensor Networks (WSN), an Adaptive and Efficient time synchronization Optimization (AEO) algorithm is proposed based on receiver-receiver time synchronization model. Firstly, in pairwise time synchronization, slave node receives the synchronization message from reference node and confirmed. After the synchronization period, the time correction is realized by fitting estimation and data update. Then the interactive parameter synchronization package is constructed. The slave node exchanges interactive parameter synchronization package with the master to realize pairwise synchronization. Secondly, the Voronoi polygon topology is established. The network also identifies the IDentification (ID) of reference nodes and neighbor nodes in the topology. The coverage area of reference nodes exchange synchronization information by neighboring nodes to realize adaptive regions joint time synchronization. The simulation results show that the algorithm has less synchronization errors and lower network energy consumption in pairwise time synchronization. Meanwhile, the Voronoi topology improves connectivity efficiency and convergence time compared with other typical topologies.
To solve the problem of low efficiency for multiple-hop adaptive time synchronization in Wireless Sensor Networks (WSN), an Adaptive and Efficient time synchronization Optimization (AEO) algorithm is proposed based on receiver-receiver time synchronization model. Firstly, in pairwise time synchronization, slave node receives the synchronization message from reference node and confirmed. After the synchronization period, the time correction is realized by fitting estimation and data update. Then the interactive parameter synchronization package is constructed. The slave node exchanges interactive parameter synchronization package with the master to realize pairwise synchronization. Secondly, the Voronoi polygon topology is established. The network also identifies the IDentification (ID) of reference nodes and neighbor nodes in the topology. The coverage area of reference nodes exchange synchronization information by neighboring nodes to realize adaptive regions joint time synchronization. The simulation results show that the algorithm has less synchronization errors and lower network energy consumption in pairwise time synchronization. Meanwhile, the Voronoi topology improves connectivity efficiency and convergence time compared with other typical topologies.
2022, 44(8): 2814-2823.
doi: 10.11999/JEIT210608
Abstract:
In order to improve the anti-jamming performance of frequency hopping asynchronous network in complex electromagnetic environment, a Multi-agent Fuzzy Deep Reinforcement Learning algorithm based on Centralized Training and Decentralized Execution (MFDRL-CTDE) is proposed. Considering the complex electromagnetic environment with multiple interferences and the asynchronous network structure, the corresponding state-action space and reward function are designed. For dealing with the interaction between agents and the dynamic environment, the framework of Centralized Training and Decentralized Execution (CTDE) is introduced. Then, a fusion weight allocation strategy based on fuzzy inference system is proposed to solve the weight allocation problem in the process of network fusion. And the Dueling DQN algorithm and the prioritized experience replay technology are used to improve the efficiency of the algorithm. The simulation results show that the algorithm has a great advantage in convergence speed and best performance, and has good adaptability to the changeable complex electromagnetic environment.
In order to improve the anti-jamming performance of frequency hopping asynchronous network in complex electromagnetic environment, a Multi-agent Fuzzy Deep Reinforcement Learning algorithm based on Centralized Training and Decentralized Execution (MFDRL-CTDE) is proposed. Considering the complex electromagnetic environment with multiple interferences and the asynchronous network structure, the corresponding state-action space and reward function are designed. For dealing with the interaction between agents and the dynamic environment, the framework of Centralized Training and Decentralized Execution (CTDE) is introduced. Then, a fusion weight allocation strategy based on fuzzy inference system is proposed to solve the weight allocation problem in the process of network fusion. And the Dueling DQN algorithm and the prioritized experience replay technology are used to improve the efficiency of the algorithm. The simulation results show that the algorithm has a great advantage in convergence speed and best performance, and has good adaptability to the changeable complex electromagnetic environment.
2022, 44(8): 2824-2832.
doi: 10.11999/JEIT210523
Abstract:
In order to solve the problem that the drop rate keeps increasing due to the ultra-high dynamic characteristics of ultra-dense heterogeneous wireless networks, and considering the large time cost of previous vertical handoff algorithm based on fuzzy logic correlation, a vertical handoff algorithm for improving user experience is proposed. Firstly, 5G core access and mobile management functions are used to discover all candidate networks near the terminals. At the same time, the environment awareness ability of Self-Organized Network(SON) technology is used to monitor the running status of networks at any time and maintain actively the neighbor relationship table between them. Then, the Dynamic Fuzzy Neural Network (DFNN) algorithm is introduced to execute the handover decision, and the network parameters obtained are taken as the input of the system to generate dynamically a rule base that is effective for vertical handoff. After learning, the output decision value is calculated, and the best access network for the terminal is selected. Finally, the simulation results show that the algorithm can significantly alleviate the drop of calls in the process of vertical handoff and reduce the probability of handover failure. Meanwhile, compared with other similar algorithms, it can maintain a lower time cost.
In order to solve the problem that the drop rate keeps increasing due to the ultra-high dynamic characteristics of ultra-dense heterogeneous wireless networks, and considering the large time cost of previous vertical handoff algorithm based on fuzzy logic correlation, a vertical handoff algorithm for improving user experience is proposed. Firstly, 5G core access and mobile management functions are used to discover all candidate networks near the terminals. At the same time, the environment awareness ability of Self-Organized Network(SON) technology is used to monitor the running status of networks at any time and maintain actively the neighbor relationship table between them. Then, the Dynamic Fuzzy Neural Network (DFNN) algorithm is introduced to execute the handover decision, and the network parameters obtained are taken as the input of the system to generate dynamically a rule base that is effective for vertical handoff. After learning, the output decision value is calculated, and the best access network for the terminal is selected. Finally, the simulation results show that the algorithm can significantly alleviate the drop of calls in the process of vertical handoff and reduce the probability of handover failure. Meanwhile, compared with other similar algorithms, it can maintain a lower time cost.
2022, 44(8): 2833-2841.
doi: 10.11999/JEIT210458
Abstract:
Service Function Chain (SFC) path generation aims to provide users with diversified network function customization services with high speed and low delay. Most of the existing SFC path selection algorithms aim at specific network topology or use a single evaluation index, which has the problems of weak generalization and single evaluation standard. In view of this, an SFC path selection optimization model (SFC-GAT) based on Graph ATtention network (GAT) is proposed. Its core is no longer to fix the network topology, but to model the SFC path selection problem as a path attention problem. The generalization of the model is enhanced by redesigning the path selection diagram and path update strategy; The effect of path optimization from the perspective of delay and load capacity is evaluated to solve the problem of single evaluation of path performance. The simulation results show that compared with the shortest path and minimum overload path selection strategy under constraints, SFC-GAT can improve the comprehensive performance of path selection by at least 12% and 7%.
Service Function Chain (SFC) path generation aims to provide users with diversified network function customization services with high speed and low delay. Most of the existing SFC path selection algorithms aim at specific network topology or use a single evaluation index, which has the problems of weak generalization and single evaluation standard. In view of this, an SFC path selection optimization model (SFC-GAT) based on Graph ATtention network (GAT) is proposed. Its core is no longer to fix the network topology, but to model the SFC path selection problem as a path attention problem. The generalization of the model is enhanced by redesigning the path selection diagram and path update strategy; The effect of path optimization from the perspective of delay and load capacity is evaluated to solve the problem of single evaluation of path performance. The simulation results show that compared with the shortest path and minimum overload path selection strategy under constraints, SFC-GAT can improve the comprehensive performance of path selection by at least 12% and 7%.
Research on Non-Line-Of-Sight Recognition Method Based on Weighted K-Nearest Neighbor Classification
2022, 44(8): 2842-2851.
doi: 10.11999/JEIT210422
Abstract:
In the Ultra-WideBand (UWB) positioning system, the signal occlusion and the misjudgment of the direct signal affect seriously the positioning accuracy in complex environment. To solve this problem, Saturation (S) is proposed, which is a new characteristic parameter based on Channel Impulse Response (CIR). In this study, the Relief algorithm and the Mutual Information Feature Selection (MIFS) algorithm are used for feature selection combined with feature parameters proposed by researchers. Based on the correlation of the parameters, the optimal feature subset with corresponding weights is used for weighted K-nearest neighbor classification, which improves the accuracy of the Non-Line-Of-Sight (NLOS) recognition system. The influence of the number of training dataset and the value of K on the Weighted K-Nearest Neighbor (WKNN) algorithm is analyzed. An optimization scheme is proposed to reduce the amount of calculation and improve the real-time performance of the NLOS recognition system. The experimental results in different environments show that the method has high recognition accuracy and wide applicability, and the recognition accuracy reaches 95%.
In the Ultra-WideBand (UWB) positioning system, the signal occlusion and the misjudgment of the direct signal affect seriously the positioning accuracy in complex environment. To solve this problem, Saturation (S) is proposed, which is a new characteristic parameter based on Channel Impulse Response (CIR). In this study, the Relief algorithm and the Mutual Information Feature Selection (MIFS) algorithm are used for feature selection combined with feature parameters proposed by researchers. Based on the correlation of the parameters, the optimal feature subset with corresponding weights is used for weighted K-nearest neighbor classification, which improves the accuracy of the Non-Line-Of-Sight (NLOS) recognition system. The influence of the number of training dataset and the value of K on the Weighted K-Nearest Neighbor (WKNN) algorithm is analyzed. An optimization scheme is proposed to reduce the amount of calculation and improve the real-time performance of the NLOS recognition system. The experimental results in different environments show that the method has high recognition accuracy and wide applicability, and the recognition accuracy reaches 95%.
2022, 44(8): 2852-2858.
doi: 10.11999/JEIT210489
Abstract:
This paper investigates the problems of mutual coupling analysis and angle estimation for linear Coprime sensor Linear Arrays (CLA). Firstly, the CLA is defined. It is proved that the steering vector CLA is unambiguous. Afterwards, based on high-order cumulants, a third-order tensor model of the array output is established. Array steering vectors are subsequently estimated via tensor decomposition. Finally, unambiguous direction estimates are derived from the estimated steering vectors. The sensor spacings of the CLA can be designed as much greater than a half-wavelength, thereby significantly reducing array mutual coupling effect. Using impedance matching mutual coupling model, the mutual coupling effect and angle estimation performance are compared with the existing well-known array configurations to show the effectiveness of the CLA.
This paper investigates the problems of mutual coupling analysis and angle estimation for linear Coprime sensor Linear Arrays (CLA). Firstly, the CLA is defined. It is proved that the steering vector CLA is unambiguous. Afterwards, based on high-order cumulants, a third-order tensor model of the array output is established. Array steering vectors are subsequently estimated via tensor decomposition. Finally, unambiguous direction estimates are derived from the estimated steering vectors. The sensor spacings of the CLA can be designed as much greater than a half-wavelength, thereby significantly reducing array mutual coupling effect. Using impedance matching mutual coupling model, the mutual coupling effect and angle estimation performance are compared with the existing well-known array configurations to show the effectiveness of the CLA.
2022, 44(8): 2859-2866.
doi: 10.11999/JEIT210582
Abstract:
For the two-dimensional DOA estimation problem of low elevation target of Very High Frequency (VHF) array radar, a fast two-dimensional algorithm based on Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, the two-dimensional DOA estimation problem is transformed into two one-dimensional DOA problems by using the uncoupled characteristics of azimuth and elevation under uniformed planar array, and the target information is extracted by azimuth and elevation dimensional digital beamforming, and then based on signal mode, the over-complete expression in the signal space domain is established. Finally, the ADMM algorithm is used to estimate azimuth and elevation. ADMM algorithm avoids the complicated calculation of two-dimension joint estimation, reduces greatly the complexity, and the algorithm process does not need the eigenvalue decomposition, which improves further the operation efficiency. Simulation results show the superiority of the algorithm.
For the two-dimensional DOA estimation problem of low elevation target of Very High Frequency (VHF) array radar, a fast two-dimensional algorithm based on Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, the two-dimensional DOA estimation problem is transformed into two one-dimensional DOA problems by using the uncoupled characteristics of azimuth and elevation under uniformed planar array, and the target information is extracted by azimuth and elevation dimensional digital beamforming, and then based on signal mode, the over-complete expression in the signal space domain is established. Finally, the ADMM algorithm is used to estimate azimuth and elevation. ADMM algorithm avoids the complicated calculation of two-dimension joint estimation, reduces greatly the complexity, and the algorithm process does not need the eigenvalue decomposition, which improves further the operation efficiency. Simulation results show the superiority of the algorithm.
2022, 44(8): 2867-2877.
doi: 10.11999/JEIT210565
Abstract:
Micro-Doppler effect is a frequency modulation phenomenon caused by the rotation, vibration, precession or other micro-motions of targets (or their components), which is able to reflect the geometric structure and motion state of the target. In this paper, the time-frequency distribution characteristics of micro motion echo induced by the rotation of target fan blades under near-field and far-field conditions are analyzed comprehensively. First, the signal models of the near-field and far-field radar micro motion echo are established. Then, the instantaneous frequencies are derived from the signal model of the far-field micro motion echo. The results show that the spectrogram of the far-field micro motion echo is composed of the sinusoidal flashes, zero-frequency flash, and rectangular flashes induced by the tip scattering points, hub scattering points, and mirror reflection points, respectively. Finally, the instantaneous frequencies corresponding to the above three kinds of local scattering points under near-field condition are directly derived, which indicates that the spectrogram of the near-field micro motion echo behaves as the combination of the sine-like flashes, zero-frequency flash, and partial cosine flashes. The formation mechanisms about the above flashes are explained from the perspectives of the integral operation properties and electromagnetic scattering theories. Also, the relationship between the flashes and the number, size, rotation velocity of the blades is revealed. This paper will be helpful to the applications of target fine modeling, target classification and recognition. The correctness of the analyses is validated by simulated and field experimental data.
Micro-Doppler effect is a frequency modulation phenomenon caused by the rotation, vibration, precession or other micro-motions of targets (or their components), which is able to reflect the geometric structure and motion state of the target. In this paper, the time-frequency distribution characteristics of micro motion echo induced by the rotation of target fan blades under near-field and far-field conditions are analyzed comprehensively. First, the signal models of the near-field and far-field radar micro motion echo are established. Then, the instantaneous frequencies are derived from the signal model of the far-field micro motion echo. The results show that the spectrogram of the far-field micro motion echo is composed of the sinusoidal flashes, zero-frequency flash, and rectangular flashes induced by the tip scattering points, hub scattering points, and mirror reflection points, respectively. Finally, the instantaneous frequencies corresponding to the above three kinds of local scattering points under near-field condition are directly derived, which indicates that the spectrogram of the near-field micro motion echo behaves as the combination of the sine-like flashes, zero-frequency flash, and partial cosine flashes. The formation mechanisms about the above flashes are explained from the perspectives of the integral operation properties and electromagnetic scattering theories. Also, the relationship between the flashes and the number, size, rotation velocity of the blades is revealed. This paper will be helpful to the applications of target fine modeling, target classification and recognition. The correctness of the analyses is validated by simulated and field experimental data.
2022, 44(8): 2878-2883.
doi: 10.11999/JEIT210476
Abstract:
In order to overcome the large directional angle error caused by the structure error angle of the orthogonal magnetic loop antenna, a three-magnetic loop directional antenna design scheme is proposed. The principle of the direction finding of the three-magnetic loop antenna is described, and the simulation model of the directional angle error with respect to the structure error angle of the three-magnetic loop antenna is established. The simulation analysis shows that under the same structural error angle condition, compared with the orthogonal magnetic loop antenna, the maximum directional angle error of the three magnetic loop antenna can theoretically be reduced by 50%. The comparative experiment results under the low frequency (f<200 kHz) situation show that compared with orthogonal magnetic loop antennas, the maximum directional angle error of the three magnetic loop antenna is reduced by 65%, and the overall directional angle error is optimized by approximately 50%, the experimental results are in good agreement with the simulation results.
In order to overcome the large directional angle error caused by the structure error angle of the orthogonal magnetic loop antenna, a three-magnetic loop directional antenna design scheme is proposed. The principle of the direction finding of the three-magnetic loop antenna is described, and the simulation model of the directional angle error with respect to the structure error angle of the three-magnetic loop antenna is established. The simulation analysis shows that under the same structural error angle condition, compared with the orthogonal magnetic loop antenna, the maximum directional angle error of the three magnetic loop antenna can theoretically be reduced by 50%. The comparative experiment results under the low frequency (f<200 kHz) situation show that compared with orthogonal magnetic loop antennas, the maximum directional angle error of the three magnetic loop antenna is reduced by 65%, and the overall directional angle error is optimized by approximately 50%, the experimental results are in good agreement with the simulation results.
2022, 44(8): 2884-2892.
doi: 10.11999/JEIT210567
Abstract:
A sparse Bayesian dictionary learning-based parameter estimation method is proposed to overcome the performance degradation in presence of dictionary mismatch in Space-Time Adaptive Processing (STAP). First, multiple measurements are constructed by using direction compensated space samples. Second, the bilinear transformation is utilized to separate the velocity and acceleration of the maneuvering target. Finally, the dynamic dictionaries of velocity and acceleration are established by the Taylor’s series, and then the maneuvering target parameters are estimated by sparse Bayesian dictionary learning. Numerical results show that the proposed method can obtain better accuracy in parameter estimation, and can provide an improved performance to the sparse recovery methods with pre-discretized dictionary in STAP parameter estimation.
A sparse Bayesian dictionary learning-based parameter estimation method is proposed to overcome the performance degradation in presence of dictionary mismatch in Space-Time Adaptive Processing (STAP). First, multiple measurements are constructed by using direction compensated space samples. Second, the bilinear transformation is utilized to separate the velocity and acceleration of the maneuvering target. Finally, the dynamic dictionaries of velocity and acceleration are established by the Taylor’s series, and then the maneuvering target parameters are estimated by sparse Bayesian dictionary learning. Numerical results show that the proposed method can obtain better accuracy in parameter estimation, and can provide an improved performance to the sparse recovery methods with pre-discretized dictionary in STAP parameter estimation.
2022, 44(8): 2893-2902.
doi: 10.11999/JEIT210484
Abstract:
Moving target in shallow sea environment can generate stable interference sound field, which contains information such as target distance and velocity.In this paper, a method of passive distance and velocity estimation based on moving target interference sound field is proposed. First, the interference phenomenon and structure characteristics in shallow sea waveguide are analyzed theoretically, and the focusing principle of matching interference field method is deduced. Then, the time-frequency interference field of the moving target is transformed into range-frequency interference field which is related to the target range and velocity, and the distance and velocity of the target are estimated simultaneously by correlative processing with the copy sound field. Further, the value distance performance of the algorithm and the influence of sea depth, sound velocity profile, sea surface and other sound field parameters on the value distance performance are investigated through simulation, and the simulation conclusion of the algorithm tolerance is given. At last, the validity of the algorithm is verified by the data of practical target at sea.
Moving target in shallow sea environment can generate stable interference sound field, which contains information such as target distance and velocity.In this paper, a method of passive distance and velocity estimation based on moving target interference sound field is proposed. First, the interference phenomenon and structure characteristics in shallow sea waveguide are analyzed theoretically, and the focusing principle of matching interference field method is deduced. Then, the time-frequency interference field of the moving target is transformed into range-frequency interference field which is related to the target range and velocity, and the distance and velocity of the target are estimated simultaneously by correlative processing with the copy sound field. Further, the value distance performance of the algorithm and the influence of sea depth, sound velocity profile, sea surface and other sound field parameters on the value distance performance are investigated through simulation, and the simulation conclusion of the algorithm tolerance is given. At last, the validity of the algorithm is verified by the data of practical target at sea.
2022, 44(8): 2903-2913.
doi: 10.11999/JEIT210556
Abstract:
Differential Computational Analysis (DCA) is a side channel analysis method applied to white box security analysis. Its efficiency has been verified in the analysis of white-box Advanced Encryption Standard (AES). A new DCA-like attack is proposed named Intermediate-Values Mean Difference Analysis(IVMDA). The analysis takes the results of the lookup table in the white-box SM4 implementation as the analysis object, and uses the method of statistical analysis to extract the key. Compared with the existing white-box SM4 analysis method, the intermediate-values mean difference analysis requires fewer conditions, and the analysis efficiency is higher. After successfully analyzing the white-box SM4 implementation, a software countermeasure is proposed to improve its security. The software countermeasure uses nonlinear components to confuse the intermediate state in the white-box implementation and eliminate the correlation between the intermediate state and the key. The experimental results show that the countermeasure can effectively resist the intermediate-values mean difference analysis.
Differential Computational Analysis (DCA) is a side channel analysis method applied to white box security analysis. Its efficiency has been verified in the analysis of white-box Advanced Encryption Standard (AES). A new DCA-like attack is proposed named Intermediate-Values Mean Difference Analysis(IVMDA). The analysis takes the results of the lookup table in the white-box SM4 implementation as the analysis object, and uses the method of statistical analysis to extract the key. Compared with the existing white-box SM4 analysis method, the intermediate-values mean difference analysis requires fewer conditions, and the analysis efficiency is higher. After successfully analyzing the white-box SM4 implementation, a software countermeasure is proposed to improve its security. The software countermeasure uses nonlinear components to confuse the intermediate state in the white-box implementation and eliminate the correlation between the intermediate state and the key. The experimental results show that the countermeasure can effectively resist the intermediate-values mean difference analysis.
2022, 44(8): 2914-2923.
doi: 10.11999/JEIT210441
Abstract:
MIBS is a Feistel structured lightweight block cipher aimed at extremely constrained resources environment. In this paper, an 8-round meet-in-the-middle distinguisher of MIBS is constructed by utilizing multiset and effective differential enumeration technique. Then, the meet-in-the-middle attacks on 12-round and 13-round MIBS-80 are proposed based on the new distinguisher. In the attack process, the plaintexts are filtered utilizing the differential properties and the guessed keys are reduced using the relation of master key and round key in the key expansion algorithm of MIBS-80. The time complexity of attacking 12-round and 13-round MIBS-80 is 253.2 and 262, respectively. Compared with the known results of the meet-in-the-middle attack, the number of rounds of meet-in-the-middle attack on MIBS-80 is increased by 2-round.
MIBS is a Feistel structured lightweight block cipher aimed at extremely constrained resources environment. In this paper, an 8-round meet-in-the-middle distinguisher of MIBS is constructed by utilizing multiset and effective differential enumeration technique. Then, the meet-in-the-middle attacks on 12-round and 13-round MIBS-80 are proposed based on the new distinguisher. In the attack process, the plaintexts are filtered utilizing the differential properties and the guessed keys are reduced using the relation of master key and round key in the key expansion algorithm of MIBS-80. The time complexity of attacking 12-round and 13-round MIBS-80 is 253.2 and 262, respectively. Compared with the known results of the meet-in-the-middle attack, the number of rounds of meet-in-the-middle attack on MIBS-80 is increased by 2-round.
2022, 44(8): 2924-2931.
doi: 10.11999/JEIT210466
Abstract:
Ground objects in high-resolution remote sensing images are often closely related to the scene categories. If the constraint information of the scene on the ground object can be usefully employed, it is expected to improve further the performance of object detection. Considering the relationship between scene information and objects, a scene constrained object detection method in high-resolution remote sensing images by Relation-aware Global Attention (RGA) is proposed. First, the global scene features are learned by adding the global relational attention to the basic network in Feature fusion and Scaling-based Single Shot Detector (FS-SSD). Then, object is predicted by combining the oriented response convolution module with the multiscale feature module under the constraints of learned global scene features. Finally, two loss functions are used to optimize jointly the network to achieve object detection. Four experiments are conducted on NWPU VHR-10 dataset and better object detection performance is achieved under the constraints of scene information.
Ground objects in high-resolution remote sensing images are often closely related to the scene categories. If the constraint information of the scene on the ground object can be usefully employed, it is expected to improve further the performance of object detection. Considering the relationship between scene information and objects, a scene constrained object detection method in high-resolution remote sensing images by Relation-aware Global Attention (RGA) is proposed. First, the global scene features are learned by adding the global relational attention to the basic network in Feature fusion and Scaling-based Single Shot Detector (FS-SSD). Then, object is predicted by combining the oriented response convolution module with the multiscale feature module under the constraints of learned global scene features. Finally, two loss functions are used to optimize jointly the network to achieve object detection. Four experiments are conducted on NWPU VHR-10 dataset and better object detection performance is achieved under the constraints of scene information.
2022, 44(8): 2932-2939.
doi: 10.11999/JEIT211444
Abstract:
When light travels in water, it is absorbed by water and scattered by particles, resulting in color distortion, low quality, and poor visibility of underwater images. To solve this problem, an underwater image enhancement method is proposed based on blue-green channel color compensation. First, the characteristics of the underwater imaging model is analyzed, and the depth of the underwater scene is classified according to the proportion of the mean value of the blue and green channels in the sum of the mean value of the three channels, the light attenuation rate characteristic is used to adaptively compensate the color, and multi-scene color correction is realized. Then the color-compensated image is divided into four regions: dark tone, mid-dark tone, mid-bright tone, and bright tone. The dark region of the image is mapped to the bright region using the dark region mapping function, which improves the contrast while suppressing the generation of noise. Finally, bilinear interpolation is used to solve the regional effect of block processing. Experimental results on real underwater datasets show that compared with existing methods, this method can improve low-quality underwater images in a variety of scenes.
When light travels in water, it is absorbed by water and scattered by particles, resulting in color distortion, low quality, and poor visibility of underwater images. To solve this problem, an underwater image enhancement method is proposed based on blue-green channel color compensation. First, the characteristics of the underwater imaging model is analyzed, and the depth of the underwater scene is classified according to the proportion of the mean value of the blue and green channels in the sum of the mean value of the three channels, the light attenuation rate characteristic is used to adaptively compensate the color, and multi-scene color correction is realized. Then the color-compensated image is divided into four regions: dark tone, mid-dark tone, mid-bright tone, and bright tone. The dark region of the image is mapped to the bright region using the dark region mapping function, which improves the contrast while suppressing the generation of noise. Finally, bilinear interpolation is used to solve the regional effect of block processing. Experimental results on real underwater datasets show that compared with existing methods, this method can improve low-quality underwater images in a variety of scenes.
2022, 44(8): 2940-2948.
doi: 10.11999/JEIT210545
Abstract:
Light Field Depth Estimation(LFDE) is critical to the related applications such as 3D reconstruction, automatic driving and object tracking. However, the existing depth learning-based methods bring details lost on the edge, weak texture and other complex areas, because of ignoring the geometric characteristics of the light field image in the learning network. This paper proposes a semantic guided LFDE network, which utilizes contextual information of light field images to solve ill posed problems in complex regions. Encoder-decoder structure of semantic perception module is designed to reconstruct the spatial information for better obtaining the object boundary. The spatial pyramid pooling structure uses the atrous convolution to increase the receptive field and capture the multi-scale contextual information. Then, an adaptive local cross-channel interaction feature attention module without dimensionality reduction is used to eliminate information redundancy, and multi-channels are effectively fused. Finally, the stacked hourglass is introduced to connect multiple hourglass modules in series, and more rich context information is obtained by using the encoder-decoder structure. The experimental results on 4D light field dataset new HCI demonstrate that the proposed method has higher accuracy and generalization ability, which is superior to the depth estimation method compared, and retains better edge details.
Light Field Depth Estimation(LFDE) is critical to the related applications such as 3D reconstruction, automatic driving and object tracking. However, the existing depth learning-based methods bring details lost on the edge, weak texture and other complex areas, because of ignoring the geometric characteristics of the light field image in the learning network. This paper proposes a semantic guided LFDE network, which utilizes contextual information of light field images to solve ill posed problems in complex regions. Encoder-decoder structure of semantic perception module is designed to reconstruct the spatial information for better obtaining the object boundary. The spatial pyramid pooling structure uses the atrous convolution to increase the receptive field and capture the multi-scale contextual information. Then, an adaptive local cross-channel interaction feature attention module without dimensionality reduction is used to eliminate information redundancy, and multi-channels are effectively fused. Finally, the stacked hourglass is introduced to connect multiple hourglass modules in series, and more rich context information is obtained by using the encoder-decoder structure. The experimental results on 4D light field dataset new HCI demonstrate that the proposed method has higher accuracy and generalization ability, which is superior to the depth estimation method compared, and retains better edge details.
2022, 44(8): 2949-2956.
doi: 10.11999/JEIT210537
Abstract:
For steganalysis, many studies have shown that convolutional neural networks have better performance than traditional artificially designed features. However, the ability of linear convolution layer to express higher-order features is limited and the feature map of each channel is not distinguished in the existing detection model which based on Convolutional Neural Networks (CNN). To solve these problems, an image steganography detection model based on Multi-layer perceptual convolution and channel weighting is constructed in this paper. The Multi-layer perceptual convolution layer (Mlpconv)is used to replace the traditional linear convolution layer to enhance the expressiveness ability of high-order features of the detection model. The channel weighting module is added to the model, which assigns different weights to each convolution channel based on global information, so that the useful features can be enhanced and the useless features can be suppressed, and the detection features extracted from the quality model can be improved. The experimental results show that the detection accuracy of proposed detection model is higher than that of Xu-Net, Yedroudj-Net, and Zhang-Net for different typical steganography algorithms and different embedding rates. And compared with the optimal Zhu-Net, the accuracy rate is increased by 1.95～6.15%.
For steganalysis, many studies have shown that convolutional neural networks have better performance than traditional artificially designed features. However, the ability of linear convolution layer to express higher-order features is limited and the feature map of each channel is not distinguished in the existing detection model which based on Convolutional Neural Networks (CNN). To solve these problems, an image steganography detection model based on Multi-layer perceptual convolution and channel weighting is constructed in this paper. The Multi-layer perceptual convolution layer (Mlpconv)is used to replace the traditional linear convolution layer to enhance the expressiveness ability of high-order features of the detection model. The channel weighting module is added to the model, which assigns different weights to each convolution channel based on global information, so that the useful features can be enhanced and the useless features can be suppressed, and the detection features extracted from the quality model can be improved. The experimental results show that the detection accuracy of proposed detection model is higher than that of Xu-Net, Yedroudj-Net, and Zhang-Net for different typical steganography algorithms and different embedding rates. And compared with the optimal Zhu-Net, the accuracy rate is increased by 1.95～6.15%.
2022, 44(8): 2957-2965.
doi: 10.11999/JEIT210472
Abstract:
In order to solve the problem that the Siamese network can not express the rotating target, a Siamese network tracking algorithm based on asymmetric convolution is proposed. Firstly, asymmetric convolution kernels are constructed, which can be applied to existing networks. Then, under the framework of Siamese network, the convolution module of AlexNet is replaced, and the network is designed separately in the training and tracking stages. Finally, three asymmetric convolution kernels are added in parallel in the last layer of the network, and the maximum value is selected as the target position after the three response maps are weighted fused. The experimental results show that compared with SiamFC, the accuracy and success rate are improved by 8.7% and 4.5% on OTB2015 dataset, respectively.
In order to solve the problem that the Siamese network can not express the rotating target, a Siamese network tracking algorithm based on asymmetric convolution is proposed. Firstly, asymmetric convolution kernels are constructed, which can be applied to existing networks. Then, under the framework of Siamese network, the convolution module of AlexNet is replaced, and the network is designed separately in the training and tracking stages. Finally, three asymmetric convolution kernels are added in parallel in the last layer of the network, and the maximum value is selected as the target position after the three response maps are weighted fused. The experimental results show that compared with SiamFC, the accuracy and success rate are improved by 8.7% and 4.5% on OTB2015 dataset, respectively.
2022, 44(8): 2966-2976.
doi: 10.11999/JEIT211459
Abstract:
Single-cell intrinsic biophysical properties including structural properties (e.g., cellular diameter and nuclear diameter) and electrical properties (e.g., specific membrane capacitance and cytoplasmic conductivity) have been applied to cell subtype classifications, and cell status evaluations are promising in biomedical research and clinical diagnosis. Different types of single-cell structural and electrical properties detection methods are reviewed in this paper, then fixed and flow methods and microfluidic methods are introduced. The working principles, developments, main advantages and disadvantages of these methods are summarized, and the challenges and future research opportunities for measurements of single-cell structural and electrical properties are discussed.
Single-cell intrinsic biophysical properties including structural properties (e.g., cellular diameter and nuclear diameter) and electrical properties (e.g., specific membrane capacitance and cytoplasmic conductivity) have been applied to cell subtype classifications, and cell status evaluations are promising in biomedical research and clinical diagnosis. Different types of single-cell structural and electrical properties detection methods are reviewed in this paper, then fixed and flow methods and microfluidic methods are introduced. The working principles, developments, main advantages and disadvantages of these methods are summarized, and the challenges and future research opportunities for measurements of single-cell structural and electrical properties are discussed.
