Large-Scale STAR-RIS Assisted Near-Field ISAC Transmission Method

WANG Xiaoming; LI Jiaqi; LIU Ting; JIANG Rui; XU Youyun

doi:10.11999/JEIT240018

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2025 >

WANG Xiaoming, LI Jiaqi, LIU Ting, JIANG Rui, XU Youyun. Large-Scale STAR-RIS Assisted Near-Field ISAC Transmission Method[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240018

Citation:

WANG Xiaoming, LI Jiaqi, LIU Ting, JIANG Rui, XU Youyun. Large-Scale STAR-RIS Assisted Near-Field ISAC Transmission Method[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240018

Citation:

PDF( 4026 KB)

Large-Scale STAR-RIS Assisted Near-Field ISAC Transmission Method

doi: 10.11999/JEIT240018

1.
School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.
School of Artificial Intelligence (School of Future Technology), Nanjing University of Information Science and Technology, Nanjing 210044, China

Funds: The National Natural Science Foundation of China (62101274, 62371246)

Received Date: 2024-01-16
Rev Recd Date: 2024-09-06

Available Online: 2024-09-28

Abstract

Abstract

Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surfaces (STAR-RIS) is able to create an all-space intelligent radio environment to effectively improve the performance of wireless communication systems, thus it has vast research potential. Therefore, in this paper, a large-scale STAR-RIS-assisted near-field Integrated Sensing and Communication (ISAC) approach is proposed. Cramér-Rao Bound (CRB) of the three-dimensional estimation of the sensing target is optimized. First, the near-field system model is built and then beam steering vectors between base station, STAR-RIS, communication users, sensing target and sensor are derived respectively. Second, the sensing performance is optimized by designing the transmit beamforming matrix, the covariance matrix of transmit signal and the STAR-RIS coefficients. Third, a non-convex optimization problem is solved via semi-definite relaxation approach. The simulation results show the effectiveness of our proposed ISAC approach, and the positioning performance advantage brought by the extra distance freedom of near field.

FullText(HTML)

References(20)

References

[1]	WEI Zhiqing, QU Hanyang, WANG Yuan, et al. Integrated sensing and communication signals toward 5G-A and 6G: A survey[J]. IEEE Internet of Things Journal, 2023, 10(13): 11068–11092. doi: 10.1109/JIOT.2023.3235618.
[2]	BASHARAT S, HASSAN S A, PERVAIZ H, et al. Reconfigurable intelligent surfaces: Potentials, applications, and challenges for 6G wireless networks[J]. IEEE Wireless Communications, 2021, 28(6): 184–191. doi: 10.1109/MWC.011.2100016.
[3]	LIU Yuanwei, MU Xidong, LIU Xiao, et al. Reconfigurable intelligent surface-aided multi-user networks: Interplay between NOMA and RIS[J]. IEEE Wireless Communications, 2022, 29(2): 169–176. doi: 10.1109/MWC.102.2100363.
[4]	张在琛, 江浩. 智能超表面使能无人机高能效通信信道建模与传输机理分析[J]. 电子学报, 2023, 51(10): 2623–2634. doi: 10.12263/DZXB.20221352. ZHANG Zaichen and JIANG Hao. Channel modeling and characteristics analysis for high energy-efficient RIS-assisted UAV communications[J]. Acta Electronica Sinica, 2023, 51(10): 2623–2634. doi: 10.12263/DZXB.20221352.
[5]	JIANG Hao, XIONG Baiping, ZHANG Hongming, et al. Physics-based 3D end-to-end modeling for double-RIS assisted non-stationary UAV-to-ground communication channels[J]. IEEE Transactions on Communications, 2023, 71(7): 4247–4261. doi: 10.1109/TCOMM.2023.3266832.
[6]	GUO Yuan, LIU Yang, WU Qingqing, et al. Joint beamforming for RIS aided full-duplex integrated sensing and uplink communication[C]. The IEEE International Conference on Communications, Rome, Italy, 2023: 4249–4254. doi: 10.1109/ICC45041.2023.10279303.
[7]	XU Jiaqi, LIU Yuanwei, MU Xidong, et al. STAR-RISs: Simultaneous transmitting and reflecting reconfigurable intelligent surfaces[J]. IEEE Communications Letters, 2021, 25(9): 3134–3138. doi: 10.1109/LCOMM.2021.3082214.
[8]	WANG Zhaolin, MU Xidong, XU Jiaqi, et al. Simultaneously transmitting and reflecting surface (STARS) for terahertz communications[J]. IEEE Journal of Selected Topics in Signal Processing, 2023, 17(4): 861–877. doi: 10.1109/JSTSP.2023.3279621.
[9]	CHEN Jiagao and YU Xiangbin. Ergodic rate analysis and phase design of STAR-RIS aided NOMA with statistical CSI[J]. IEEE Communications Letters, 2022, 26(12): 2889–2893. doi: 10.1109/LCOMM.2022.3202346.
[10]	WANG Yufei, YANG Zheng, CUI Jingjing, et al. Optimizing the fairness of STAR-RIS and NOMA assisted integrated sensing and communication systems[J]. IEEE Transactions on Wireless Communications, 2024, 23(6): 5895–5907. doi: 10.1109/TWC.2023.3328872.
[11]	LIU Zhenrong, LI Zongze, WEN Miaowen, et al. STAR-RIS-aided mobile edge computing: Computation rate maximization with binary amplitude coefficients[J]. IEEE Transactions on Communications, 2023, 71(7): 4313–4327. doi: 10.1109/TCOMM.2023.3274137.
[12]	LI Haochen, WANG Zhaolin, MU Xidong, et al. Near-field integrated sensing, positioning, and communication: A downlink and uplink framework[J]. IEEE Journal on Selected Areas in Communications, 2024, 42(9): 2196–2212. doi: 10.1109/JSAC.2024.3413956.
[13]	JIANG Hao, XIONG Baiping, ZHANG Hongming, et al. Hybrid far-and near-field modeling for reconfigurable intelligent surface assisted V2V channels: A sub-array partition based approach[J]. IEEE Transactions on Wireless Communications, 2023, 22(11): 8290–8303. doi: 10.1109/TWC.2023.3262063.
[14]	TANG Wankai, CHEN Mingzheng, CHEN Xiangyu, et al. Wireless communications with reconfigurable intelligent surface: Path loss modeling and experimental measurement[J]. IEEE Transactions on Wireless Communications, 2021, 20(1): 421–439. doi: 10.1109/TWC.2020.3024887.
[15]	WEI Xiuhong, DAI Linglong, ZHAO Yajun, et al. Codebook design and beam training for extremely large-scale RIS: Far-field or near-field?[J]. China Communications, 2022, 19(6): 193–204. doi: 10.23919/JCC.2022.06.015.
[16]	SENGIJPTA S K. Fundamentals of statistical signal processing: Estimation theory[J]. Technometrics, 1995, 37(4): 465–466. doi: 10.1080/00401706.1995.10484391.
[17]	SHI Qingjiang and HONG Mingyi. Penalty dual decomposition method for nonsmooth nonconvex optimization—Part I: Algorithms and convergence analysis[J]. IEEE Transactions on Signal Processing, 2020, 68: 4108–4122. doi: 10.1109/TSP.2020.3001906.
[18]	LUO Zhiquan, MA W, SO A M C, et al. Semidefinite relaxation of quadratic optimization problems[J]. IEEE Signal Processing Magazine, 2010, 27(3): 20–34. doi: 10.1109/MSP.2010.936019.
[19]	LIU Fan, LIU Yafeng, LI Ang, et al. Cramér-rao bound optimization for joint radar-communication beamforming[J]. IEEE Transactions on Signal Processing, 2022, 70: 240–253. doi: 10.1109/TSP.2021.3135692.
[20]	LIU Xiang, HUANG Tianyao, SHLEZINGER N, et al. Joint transmit beamforming for multiuser MIMO communications and MIMO radar[J]. IEEE Transactions on Signal Processing, 2020, 68: 3929–3944. doi: 10.1109/TSP.2020.3004739.