Joint Beamforming Design for STAR-RIS Assisted URLLC-NOMA System

ZHU Jianyue; WU Yutong; CHEN Xiao; XIE Yaqin; XU Yao; ZHANG Zhizhong

doi:10.11999/JEIT240717

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ZHU Jianyue, WU Yutong, CHEN Xiao, XIE Yaqin, XU Yao, ZHANG Zhizhong. Joint Beamforming Design for STAR-RIS Assisted URLLC-NOMA System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240717

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ZHU Jianyue, WU Yutong, CHEN Xiao, XIE Yaqin, XU Yao, ZHANG Zhizhong. Joint Beamforming Design for STAR-RIS Assisted URLLC-NOMA System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240717

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Joint Beamforming Design for STAR-RIS Assisted URLLC-NOMA System

doi: 10.11999/JEIT240717

1.
School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing210044, China
2.
School of Cyberspace Security, Southeast University, Nanjing211189, China
3.
School of Artificial Intelligence/School of Future Technology, Nanjing University of Information Science, Nanjing University of Information Science and Technology, Nanjing210044, China

Funds: The National Natural Science Foundation of China (62101273), The Natural Science Foundation of Jiangsu Province of China (BK20220439, BK20220438), The Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 22KJB510005, 22KJB510033), Jiangsu Provincial Key Research and Development Program (BE2023088), Jiangsu Provincial Innovation and Entrepreneurship Team (No. (2023)200008)

Received Date: 2024-08-19
Rev Recd Date: 2025-02-14

Available Online: 2025-02-24

Abstract

Abstract

Objective This paper addresses the energy efficiency challenge in Ultra-Reliable Low-Latency Communication (URLLC) systems, crucial for mission-critical applications such as industrial automation and remote surgery. The integration of Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces (STAR-RIS) with Non-Orthogonal Multiple Access (NOMA) is proposed to improve spectral efficiency and coverage while meeting URLLC’s stringent reliability and latency requirements. However, the joint optimization of base station beamforming, STAR-RIS transmission, and reflection matrices presents a non-trivial problem due to non-convexity and coupled variables. This work aims to minimize energy consumption under a total power constraint by jointly designing these parameters, advancing STAR-RIS-aided NOMA systems for URLLC. Methods To address the non-convex optimization problem, the proposed methodology involves several key steps. First, the user rate function under finite blocklength transmission is analyzed, considering the specific requirements of URLLC. This analysis facilitates the reformulation of the original problem into an equivalent form more amenable to optimization. Specifically, the rate function is approximated using a Taylor series expansion, and the effect of finite blocklength on decoding error probability is incorporated into the optimization framework.Next, an alternating optimization framework is adopted to decouple the joint design problem into subproblems, each focused on optimizing either the base station beamforming, the STAR-RIS transmission matrix, or the reflection matrix. Semidefinite Relaxation (SDR) techniques are then applied to address the non-convexity of these subproblems, ensuring efficient and tractable solutions. The SDR method transforms the original non-convex constraints into convex ones by relaxing certain matrix rank constraints, which are subsequently recovered using randomization techniques.The proposed approach is validated through extensive simulations, comparing its performance with Orthogonal Multiple Access (OMA) and traditional RIS-aided schemes. The simulation setup includes a multi-user scenario with varying channel conditions, blocklengths, and reliability requirements. Results and Discussions The main contributions of this paper are summarized as follows:(1) Joint Optimization of Active and Passive Beamforming Vectors: To minimize system transmission power, the paper jointly optimizes the active beamforming vector at the base station and the passive beamforming vector at the reflective surface, presenting an efficient joint beamforming design algorithm (Table 1). (2) Validation and Energy Efficiency Comparison: Experimental results confirm the effectiveness of the proposed joint beamforming design. A comparison of energy consumption performance for STAR-RIS under different modes is provided. Specifically, the proposed STAR-RIS-aided NOMA scheme demonstrates a significant reduction in power consumption compared to OMA and conventional RIS-aided systems (Fig. 2 and Fig. 5). The proposed joint beamforming and STAR-RIS optimization framework effectively addresses the trade-offs between energy consumption, reliability, and latency in URLLC systems. Conclusions This paper presents a comprehensive framework for the transmission design of STAR-RIS-aided NOMA systems in URLLC scenarios. By jointly optimizing beamforming, transmission, and reflection matrices, the proposed method significantly enhances energy efficiency while meeting the stringent requirements of URLLC. The use of alternating optimization and SDR techniques effectively addresses the non-convexity of the problem, providing practical and scalable solutions.The results highlight the potential of STAR-RIS-aided NOMA systems to support next-generation wireless communication applications, laying the foundation for further research in this area. Future work will explore the integration of machine learning techniques to further enhance the performance and adaptability of the proposed framework. Additionally, the impact of hardware impairments and imperfect channel state information on system performance will be investigated to ensure robustness in real-world deployments.
- Reconfigurable Intelligent Surface,
- Non-Orthogonal Multiple Access (NOMA),
- Beamforming Design

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References(25)

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