MIMO Signal Modulation Recognition Algorithm Based on ICA and Feature Extraction

Tianqi ZHANG; Congcong FAN; Wanying GE; Tian ZHANG

doi:10.11999/JEIT190320

Volume 42 Issue 9

Sep. 2020

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(9): 2208-2215

Tianqi ZHANG, Congcong FAN, Wanying GE, Tian ZHANG. MIMO Signal Modulation Recognition Algorithm Based on ICA and Feature Extraction[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2208-2215. doi: 10.11999/JEIT190320

Citation:

Tianqi ZHANG, Congcong FAN, Wanying GE, Tian ZHANG. MIMO Signal Modulation Recognition Algorithm Based on ICA and Feature Extraction[J]. Journal of Electronics & Information Technology, 2020, 42(9): 2208-2215. doi: 10.11999/JEIT190320

Citation:

PDF( 1577 KB)

MIMO Signal Modulation Recognition Algorithm Based on ICA and Feature Extraction

doi: 10.11999/JEIT190320

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61671095, 61702065, 61701067, 61771085), The Project of Key Laboratory of Signal and Information Processing of Chongqing (CSTC2009CA2003), The Chongqing Graduate Research and Innovation Project (CYS17219), The Research Project of Chongqing Educational Commission (KJ1600427, KJ1600429)

Received Date: 2019-05-06
Rev Recd Date: 2020-03-18

Available Online: 2020-06-26

Publish Date: 2020-09-27

Abstract

Abstract

For blind modulation recognition of Multiple Input Multiple Output (MIMO) signals in non-cooperative communication, a modulation recognition method based on Independent Component Analysis (ICA) and feature extraction is proposed. According to the signal independence of each transmitting antenna in space division multiplexing MIMO system, the ICA algorithm is used to separate the transmitting signal from the received mixed signal. In order to realize modulation recognition under completely blind condition, the Minimum Description Length (MDL) criterion is used to estimate the number of transmitting antennas before ICA separation. After obtaining the transmitted signal, four characteristic parameters are constructed by using six-order cumulant, cyclic spectrum and fourth-power spectrum algorithm, and then the modulation type of the signal is identified by using hierarchical neural network classifier. The simulation results show that the proposed method can effectively recognize {2PSK, 2ASK, 2FSK, 4PSK, 4ASK, MSK, 8PSK, 16QAM} eight MIMO signals at low SNR. When the number of transmitting antennas is 2, the number of receiving antennas is 5 and the SNR is 2dB, the recognition rate can reach more than 98%.
- Signal processing,
- Multiple Input Multiple Output (MIMO) signals,
- Independent Component Analysis (ICA),
- Sixth-order cumulant,
- Cyclic spectrum,
- Neural network

FullText(HTML)

References(16)

References

ZHAO Yong, XU Yitao, JIANG Han, et al. Recognition of digital modulation signals based on high-order cumulants[C]. 2015 International Conference on Wireless Communications & Signal Processing, Nanjing, China, 2015: 1–5. doi: 10.1109/WCSP.2015.7341279.

郭立民, 寇韵涵, 陈涛, 等. 基于栈式稀疏自编码器的低信噪比下低截获概率雷达信号调制类型识别[J]. 电子与信息学报, 2018, 40(4): 875–881. doi: 10.11999/JEIT170588

GUO Limin, KOU Yunhan, CHEN Tao, et al. Low probability of intercept radar signal recognition based on stacked sparse auto-encoder[J]. Journal of Electronics &Information Technology, 2018, 40(4): 875–881. doi: 10.11999/JEIT170588

陈涛, 柳立志, 郭立民. 基于MWC压缩采样宽带接收机的雷达信号脉内调制识别[J]. 电子与信息学报, 2018, 40(4): 867–874. doi: 10.11999/JEIT170612

CHEN Tao, LIU Lizhi, and GUO Limin. Intra-pulse modulation recognition of radar signals based on MWC compressed sampling wideband receiver[J]. Journal of Electronics &Information Technology, 2018, 40(4): 867–874. doi: 10.11999/JEIT170612

张利, 李青. 基于高阶累积量的调制识别算法的研究[J]. 信息工程大学学报, 2017, 18(4): 403–408. doi: 10.3969/j.issn.1671-0673.2017.04.005

ZHANG Li and LI Qing. Research on modulation recognition algorithm based on higher-order cumulant[J]. Journal of Information Engineering University, 2017, 18(4): 403–408. doi: 10.3969/j.issn.1671-0673.2017.04.005

谭晓衡, 褚国星, 张雪静, 等. 基于高阶累积量和小波变换的调制识别算法[J]. 系统工程与电子技术, 2018, 40(1): 171–177. doi: 10.3969/j.issn.1001-506X.2018.01.25

TAN Xiaoheng, CHU Guoxing, ZHANG Xuejing, et al. Modulation recognition algorithm based on high - order cumulants and wavelet transform[J]. Systems Engineering and Electronics, 2018, 40(1): 171–177. doi: 10.3969/j.issn.1001-506X.2018.01.25

赵雄文, 郭春霞, 李景春. 基于高阶累积量和循环谱的信号调制方式混合识别算法[J]. 电子与信息学报, 2016, 38(3): 674–680. doi: 10.11999/JEIT150747

ZHAO Xiongwen, GUO Chunxia, and LI Jingchun. Mixed recognition algorithm for signal modulation schemes by high-order cumulants and cyclic spectrum[J]. Journal of Electronics &Information Technology, 2016, 38(3): 674–680. doi: 10.11999/JEIT150747

CHOQUEUSE V, AZOU S, YAO K, et al. Blind modulation recognition for MIMO systems[J]. MTA Review, 2009, 19(2): 183–196.

张路平, 王建新. MIMO信号调制方式盲识别[J]. 应用科学学报, 2012, 30(2): 135–140. doi: 10.3969/j.issn.0255-8297.2012.02.005

ZHANG Luping and WANG Jianxin. Blind modulation recognition for MIMO signals[J]. Journal of Applied Sciences, 2012, 30(2): 135–140. doi: 10.3969/j.issn.0255-8297.2012.02.005

DAS D, BORA P K, and BHATTACHARJEE R. Blind modulation recognition of the lower order PSK signals under the MIMO Keyhole channel[J]. IEEE Communications Letters, 2018, 22(9): 1834–1837. doi: 10.1109/LCOMM.2018.2853638

WEI Mengchuan, WEI Zaixue, YANG Jianyi, et al. Automatic modulation recognition of digital signal based on auto-encoding network in MIMO System[C]. The 18th IEEE International Conference on Communication Technology, Chongqing, China, 2018: 1017–1021. doi: 10.1109/ICCT.2018.8600148.

LIU Xiaokai, ZHAO Chenglin, WANG Pengbiao, et al. Blind modulation classification algorithm based on machine learning for spatially correlated MIMO system[J]. IET Communications, 2017, 11(7): 1000–1007. doi: 10.1049/iet-com.2015.1222

COMON P and JUTTEN C. Handbook of Blind Source Separation: Independent Component Analysis and Applications[M]. Oxford: Academic Press, 2010: 147–153.

许宏吉, 刘琚, 谷波, 等. 空时分组码通信中的一类ICA盲检测方案[J]. 通信学报, 2007, 28(6): 12–19. doi: 10.3321/j.issn:1000-436X.2007.06.003

XU Hongji, LIU Ju, GU Bo, et al. ICA based blind detection scheme in space-time block coding communications[J]. Journal on Communications, 2007, 28(6): 12–19. doi: 10.3321/j.issn:1000-436X.2007.06.003

WANG Rui. Research on digital signal modulation recognition and parameter estimation based on cyclostationarity[D]. [Master dissertation], University of Electronic Science and Technology, 2012: 20–24.

REYNALDI A, LUKAS S, and MARGARETHA H. Backpropagation and Levenberg-Marquardt algorithm for training finite element neural network[C]. The 6th UKSim/AMSS European Symposium on Computer Modeling and Simulation, Valetta, Malta, 2012: 89–94. doi: 10.1109/EMS.2012.56.

KHOSRAVIANI M, KALBKHANI H, and SHAYESTEH M G. Digital modulation recognition in MIMO systems based on segmentation of received data[C]. 2017 Iranian Conference on Electrical Engineering, Tehran, Iran, 2017: 1998–2002. doi: 10.1109/IranianCEE.2017.7985384.

Relative Articles

Supplements(0)

Cited By

Proportional views