Hybrid Reconfigurable Intelligent Surface Assisted Integrated Sensing and Communication: Energy Efficient Beamforming Design

CHU Hongyun; YANG Mengyao; HUANG Hang; ZHENG Ling; PAN Xue; XIAO Ge

doi:10.11999/JEIT230699

Volume 46 Issue 6

Jun. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(6): 2462-2469

CHU Hongyun, YANG Mengyao, HUANG Hang, ZHENG Ling, PAN Xue, XIAO Ge. Hybrid Reconfigurable Intelligent Surface Assisted Integrated Sensing and Communication: Energy Efficient Beamforming Design[J]. Journal of Electronics & Information Technology, 2024, 46(6): 2462-2469. doi: 10.11999/JEIT230699

Citation:

CHU Hongyun, YANG Mengyao, HUANG Hang, ZHENG Ling, PAN Xue, XIAO Ge. Hybrid Reconfigurable Intelligent Surface Assisted Integrated Sensing and Communication: Energy Efficient Beamforming Design[J]. Journal of Electronics & Information Technology, 2024, 46(6): 2462-2469. doi: 10.11999/JEIT230699

Citation:

CHU Hongyun, YANG Mengyao, HUANG Hang, ZHENG Ling, PAN Xue, XIAO Ge. Hybrid Reconfigurable Intelligent Surface Assisted Integrated Sensing and Communication: Energy Efficient Beamforming Design[J]. Journal of Electronics & Information Technology, 2024, 46(6): 2462-2469. doi: 10.11999/JEIT230699

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Hybrid Reconfigurable Intelligent Surface Assisted Integrated Sensing and Communication: Energy Efficient Beamforming Design

doi: 10.11999/JEIT230699

1.
Xi’an University of Posts and Telecommunications, Xi’an 710121, China
2.
Nanjing Research Institute of Electronic Equipment, Nanjing 210013, China

Funds: The National Natural Science Foundation of China (62102314), The 173 Program for Technology (2022-JCJQ-JJ-0730), The Natural Science Foundation of Shaanxi Province (2022JQ-635)

Received Date: 2023-07-12
Accepted Date: 2023-11-14
Rev Recd Date: 2023-11-14

Available Online: 2023-11-21

Publish Date: 2024-06-30

Abstract

Abstract

Energy Efficiency (EE) is an important design metric for 5G+/6G wireless communications, and Reconfigurable Intelligent Surface (RIS) is widely recognized as a potential means to improve EE. Unlike passive RIS, hybrid RIS consists of both active and passive components, which can amplify the signal strength while phase-shifting the incoming wave, and can effectively overcome the “multiplicative fading” effect caused by fully passive RIS. In view of this, a hybrid RIS-assisted Integrated Sensing and Communication (ISAC) downlink transmission system is proposed in this paper. In order to investigate the intrinsic correlation between data transmission capacity and energy consumption, the paper jointly optimizes the beamforming and phase-shifting of hybrid RIS at the Base Station (BS) under the constraints of BS transmit power, beampattern gain, and hybrid RIS power and amplitude with the goal of maximizing the global EE in a multiuser network. To solve this complex fractional programming problem, an algorithm based on Alternating Optimization (AO) is proposed to solve it. To overcome the problem of high algorithm complexity caused by the introduction of auxiliary variables in the AO algorithm, a solution algorithm based on a cascaded deep learning network is proposed using the association of coupled optimization variables. Simulation results show that the proposed hybrid RIS-assisted ISAC scheme outperforms existing schemes in terms of sum rate and EE, and the algorithm converges quickly.

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References(24)

References

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