RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks

LI Meiling; ZHU Yuncan; SHEN Chenning; LI Xingwang

doi:10.11999/JEIT240842

Volume 47 Issue 4

Apr. 2025

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Article Navigation > Journal of Electronics & Information Technology > 2025 > 47(4): 1043-1051

LI Meiling, ZHU Yuncan, SHEN Chenning, LI Xingwang. RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks[J]. Journal of Electronics & Information Technology, 2025, 47(4): 1043-1051. doi: 10.11999/JEIT240842

Citation:

LI Meiling, ZHU Yuncan, SHEN Chenning, LI Xingwang. RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks[J]. Journal of Electronics & Information Technology, 2025, 47(4): 1043-1051. doi: 10.11999/JEIT240842

Citation:

LI Meiling, ZHU Yuncan, SHEN Chenning, LI Xingwang. RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks[J]. Journal of Electronics & Information Technology, 2025, 47(4): 1043-1051. doi: 10.11999/JEIT240842

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RIS-Assisted ISAC with Non-orthogonal Multiple Access Transmission and Resource Allocation Optimization in Vehicular Networks

doi: 10.11999/JEIT240842 cstr: 32379.14.JEIT240842

1.
School of Electronics Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
2.
Shanxi Communication Tongda Microwave Technology Co., Ltd., Taiyuan 030006, China
3.
School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China

Funds: The National Key Research and Development Program of China (2024YFE0200300), Special Fund for Science and Technology Innovation Teams of Shanxi Province (202304051001035), Taiyuan double hundred Research Project (2024TYJB0134), Shanxi Province Science and Technology Achievement Transformation Guidance Special Project (202204021301055), The Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (20240023), Shanxi Scientific Research Practice Innovation Project (2023KY647)

Received Date: 2024-10-08
Rev Recd Date: 2025-02-28

Available Online: 2025-03-25

Publish Date: 2025-04-01

Abstract

Abstract

Objective To address the issue of limited V2X communication and sensing paths in 6G dense urban environments, an RIS-assisted ISAC-V2X system framework is proposed. Considering vehicle mobility under Non-Line-of-Sight (NLOS) conditions, the Extended Kalman Filter (EKF) algorithm is utilized to track and predict the positions of moving vehicles by combining real-time Channel State Information (CSI) from the ISAC echo signals. A multi-vehicle power allocation optimization scheme based on Non-Orthogonal Multiple Access (NOMA) is introduced to enhance the downlink communication sum rate while maintaining sensing accuracy. The Karush-Kuhn-Tucker (KKT) conditions are incorporated as a feedback mechanism to prevent the system from converging to a local optimum. Simulation results demonstrate that the proposed system outperforms the traditional RIS-assisted ISAC-V2X system in terms of both communication and sensing performance. Methods This study establishes an RIS-assisted ISAC-V2X-NOMA system model. Considering vehicle mobility in NLOS conditions, the EKF algorithm is employed to track and predict vehicle locations base on real-time CSI from the ISAC signals. Subsequently, a multi-vehicle power allocation optimization scheme based on NOMA is proposed, with the KKT conditions introduced to avoid local optima and ensure global optimality. To comprehensively evaluate channel estimation performance, 1000 Monte Carlo simulations are conducted, and performance analyses are carried out on MATLAB with comparisons to traditional RIS-assisted ISAC-V2X systems under different scenarios, ultimately validating the superiority of the proposed system. Results and Discussions The sensor tracking performance of the proposed system is presented, which indicate that the introduction of RIS significantly improves the angle and distance tracking accuracy. As the number of RIS reflection elements increases, the system’s Root Mean Square Error (RMSE) decreases, validating the effectiveness of RIS in complex dynamic environments. Then, the communication performance analysis between the proposed system and the traditional system under different antenna configurations is presented, where one can observe that the communication sum rate increases as the vehicle approaches the RIS surface and decreases as it moves away, which can be also improved by increasing the number of antennas. In dense environments with limited resources, the proposed system obviously outperforms the traditional system in terms of communication sum rate under the same RIS configuration. Finally, one can also observe that power allocation optimization using NOMA allows more efficient resource management and reduced inter-user interference, further improving communication rates. These results demonstrate the significant advantages of the proposed system in terms of both communication and sensing performance in V2X systems. Conclusions This paper proposes an RIS-assisted ISAC-V2X-NOMA system framework. By utilizing RIS to dynamically adjust the propagation path of ISAC signals and designing an EKF-based vehicle tracking and prediction method, efficient real-time vehicle sensing and communication are achieved. Furthermore, a multi-vehicle power allocation optimization scheme based on NOMA is proposed to enhance communication rate and resource utilization. The results suggest that the proposed system not only reduces pilot signal overhead but also enhances the overall system performance.

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References(20)

References

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