Joint Beamforming Optimization for RIS-Assisted Dual-Functional Radar-Communication Systems

WANG Huahua; SUN Chen; ZHU Pengyun

doi:10.11999/JEIT221537

Volume 46 Issue 1

Jan. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(1): 222-228

WANG Huahua, SUN Chen, ZHU Pengyun. Joint Beamforming Optimization for RIS-Assisted Dual-Functional Radar-Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 222-228. doi: 10.11999/JEIT221537

Citation:

WANG Huahua, SUN Chen, ZHU Pengyun. Joint Beamforming Optimization for RIS-Assisted Dual-Functional Radar-Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 222-228. doi: 10.11999/JEIT221537

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Joint Beamforming Optimization for RIS-Assisted Dual-Functional Radar-Communication Systems

doi: 10.11999/JEIT221537

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

Funds: The Natural Science Foundation of Chongqing (cstc2021jcyj-msxmX0454)

Received Date: 2022-12-13
Rev Recd Date: 2023-04-24

Available Online: 2023-05-20

Publish Date: 2024-01-17

Abstract

Abstract

Dual-functional Radar-Communication Systems (DFRC) is one of the ideal technologies to effectively solve the problem of network spectrum resource congestion in the future, in this paper, Reconfigurable Intelligent Surface (RIS) technology is introduced to improve the weighted sum rate of users and the detection performance of the system. First, under the radar power constraint, the constant mode constraint of reconfigurable intelligent surface and the overall power budget of communication, an optimization model is built to maximize the weighted sum rate of communication users and the detection performance of the system. By jointly optimizing the active beam of the base station and the passive beam forming of the reconfigurable intelligent surface, an effective alternative optimization algorithm based on weighted least mean square error, fractional programming and manifold optimization is designed. The non-convex optimization problem is transformed into two subproblems and solved by iteration. The simulation results show that the proposed scheme is effective in solving the problem and the user weighted sum rate converges at a lower number of iterations, and it can increase the user's weighted sum rate upper limit by 0.86 bit/(s·Hz) and make the system detection more directional.
- Dual-functional Radar-Communication Systems (DFRC),
- Reconfigurable Intelligent Surface (RIS),
- Beamforming,
- Weighted sum rate

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References(21)

References

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