通信感知一体化及智能反射面通信场景中的波束成形

近年来，随着数据总量与终端设备数量的快速增长，对网络规模和吞吐量的需求持续攀升，这促使移动通信系统必须不断创新升级以满足不断提升的吞吐能力需求。在第六代移动通信系统（Sixth Generation Wireless Systems，6G）的前沿技术中，通信感知一体化（Integrated Sensing and Communications，ISAC）和智能反射面（Intelligent Reflecting Surface,IRS）受到了广泛关注。如何充分利用这两种技术来最大程度地提升无线通信系统的性能，成为了一个重要的研究课题。波束成形技术是实现这一目标的关键手段之一，它不仅能提升通信效率与可靠性，减少干扰泄露和保障用户隐私，同时还能增进感知精度。

本文主要探讨了ISAC和IRS辅助通信场景中的波束成形设计问题，具体内容包括：

（1）针对通信与主动感知一体化固有的自干扰和全双工问题，本文采用被动感知框架，即基站和感知接收机分开部署，并将其应用到车辆到基础设施（Vehicleto-Infrastructure,V2I）通信场景中。在所考虑的广播信道场景下，本文致力于最大化加权总速率同时满足感知信噪比约束要求，并通过运用非凸优化算法求解发射和接收波束设计以实现该目标。仿真结果验证了所提算法的有效性并为感知与通信波束的协调设计提供了有用的见解。

（2）针对现有文献中IRS辅助通信场景自由度研究中存在的特定天线配置要求的局限性，本文研究了在任意天线配置（即每个发射端或接收端的天线数量可以任意设定）下，有源IRS辅助的两用户多输入多输出（Multiple-InputMultiple-Output，MIMO）干扰信道的可达自由度问题。相较于仅关注IRS波束成形设计的传统研究，本文进一步整合了发射端迫零波束成形技术和接收端的干扰解码策略，以应对非对称天线配置所带来的复杂性。基于这一研究，本文使用IRS消除干扰信道，揭示了有源IRS在提升自由度方面的潜力，并针对对称天线配置情况推导出了IRS增益表达式。最后，本文提供了发射端的波束成形向量的显式表达。

In recent years, with the rapid growth of data volume and the number of terminal devices, the demand for network scale and throughput has been continuously increasing. This necessitates continuous innovation and upgrades in mobile communication systems to meet the escalating throughput requirements. At the forefront of the sixth-generation mobile communication systems (6G), integrated sensing and communications (ISAC) and intelligent reflecting surfaces (IRSs) have garnered widespread attention. Maximizing the performance of wireless communication systems using these two technologies has become a critical research topic. Beamforming technology is one of the key means to achieve this goal, as it not only enhances communication efficiency and reliability but also reduces interference leakage, protects user privacy, and enhances sensing accuracy and precision.

This thesis mainly investigates the beamforming design problem in ISAC and IRS-assisted communication scenarios, including:

(1) In addressing the inherent issues of self-interference and full-duplex operation in integrated communication and active sensing, this thesis adopts a passive sensing framework and applies it to the Vehicle-to-Infrastructure (V2I) communication scenario. In the considered broadcast channel scenario, this thesis focuses on maximizing the weighted sum rate while satisfying the required sensing signal-to-noise ratio (SNR) constraint. This thesis accomplishes this by solving for transmit and receive beamforming designs through the use of non-convex optimization algorithms. The simulation results validate the effectiveness of the proposed algorithm and provide useful insights into the coordination design between sensing and communication beams.

(2) To tackle the existing literature's limitation that studies on IRS-assisted communication scenarios often assume specific antenna configuration requirements, this thesis investigates the achievable degrees of freedom (DoF) in an active IRS-assisted two-user multiple-input multiple-output (MIMO) interference channel under arbitrary antenna configurations, where the number of antennas at both the transmitters and receivers can be arbitrary. Different from traditional research that primarily focuses on IRS beamforming design, this work further integrates transmit zero-forcing beamforming techniques with interference decoding strategies at the receiver to address the complexities introduced by asymmetric antenna configurations. Based on the proposed method, this thesis reveals the potential of active IRS in enhancing degrees of freedom, and derive closed-form expressions for the IRS gain for symmetric antenna configurations. Finally, an explicit expression of beamforming vector at the transmitter is provided.

[1] CHOWDHURY M Z, SHAHJALAL M, AHMED S, et al. 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions [J/OL]. IEEE Open Journal of the Communications Society, 2020, 1: 957-975. DOI: 10.1109/OJCOMS.2020.3010270.
[2] NGUYEN D C, DING M, PATHIRANA P N, et al. 6G Internet of Things: A Comprehensive Survey[J/OL]. IEEE Internet of Things Journal, 2022, 9(1): 359-383. DOI: 10.1109/JIOT.202 1.3103320.
[3] LIU F, MASOUROS C, LI A, et al. MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission[J/OL]. IEEE Transactions on Wireless Communications, 2018, 17(4): 2755-2770. DOI: 10.1109/TWC.2018.2803045.
[4] LIU F, LIU Y F, LI A, et al. Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming[J/OL]. IEEE Transactions on Signal Processing, 2022, 70: 240-253. DOI: 10.1 109TSP.2021.3135692.
[5] CHEN L, WANG Z, DU Y, et al. Generalized Transceiver Beamforming for DFRC With MIMO Radar and MU-MIMO Communication[J/OL]. IEEE Journal on Selected Areas in Communications, 2022, 40(6): 1795-1808. DOI: 10.1109/JSAC.2022.3155515.
[6] HE Z, XU W, SHEN H, et al. Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization[J/OL]. IEEE Journal on Selected Areas in Communications, 2023, 41(9): 2920-2936. DOI: 10.1109/JSAC.2023.3287540.
[7] XU D, YU X, NG D W K, et al. Robust and Secure Resource Allocation for ISAC Systems: A Novel Optimization Framework for Variable-Length Snapshots[J/OL]. IEEE Transactions on Communications, 2022, 70(12): 8196-8214. DOI: 10.1109/TCOMM.2022.3218629.
[8] HUA H, XU J, HAN T X. Optimal Transmit Beamforming for Integrated Sensing and Communication[J/OL]. IEEE Transactions on Vehicular Technology, 2023, 72(8): 10588-10603. DOI: 10.1109/TVT.2023.3262513.
[9] QI C, CI W, ZHANG J, et al. Hybrid Beamforming for Millimeter Wave MIMO Integrated Sensing and Communications[J/OL]. IEEE Communications Letters, 2022, 26(5): 1136-1140. DOI: 10.1109/LCOMM.2022.3157751.
[10] WANG X, FEI Z, ZHANG J A, et al. Partially-Connected Hybrid Beamforming Design for Integrated Sensing and Communication Systems[J/OL]. IEEE Transactions on Communications, 2022, 70(10): 6648-6660. DOI: 10.1109/TCOMM.2022.3202215.
[11] BAZZI A, CHAFII M. On Outage-Based Beamforming Design for Dual-Functional Radar- Communication 6G Systems[J/OL]. IEEE Transactions on Wireless Communications, 2023, 22(8): 5598-5612. DOI: 10.1109/TWC.2023.3235617.
[12] WANG Z, MU X, LIU Y. Near-Field Integrated Sensing and Communications[J/OL]. IEEE Communications Letters, 2023, 27(8): 2048-2052. DOI: 10.1109/LCOMM.2023.3280132.
[13] HE Z, XU W, SHEN H, et al. Energy Efficient Beamforming Optimization for Integrated Sensing and Communication[J/OL]. IEEE Wireless Communications Letters, 2022, 11(7): 1374- 1378. DOI: 10.1109/LWC.2022.3169517.
[14] MA S, SHENG H, YANG R, et al. Covert Beamforming Design for Integrated Radar Sensing and Communication Systems[J/OL]. IEEE Transactions on Wireless Communications, 2023, 22(1): 718-731. DOI: 10.1109/TWC.2022.3197940.
[15] CONG D, GUO S, ZHANG H, et al. Beamforming Design for Integrated Sensing and Communication Systems With Finite Alphabet Input[J/OL]. IEEE Wireless Communications Letters, 2022, 11(10): 2190-2194. DOI: 10.1109/LWC.2022.3196498.
[16] CHU J, LIU R, LI M, et al. Joint Secure Transmit Beamforming Designs for Integrated Sensing and Communication Systems[J/OL]. IEEE Transactions on Vehicular Technology, 2023, 72(4): 4778-4791. DOI: 10.1109/TVT.2022.3225952.
[17] HUA H, XU J, HAN T X. Optimal Transmit Beamforming for Integrated Sensing and Communication[J/OL]. IEEE Transactions on Vehicular Technology, 2023, 72(8): 10588-10603. DOI: 10.1109/TVT.2023.3262513.
[18] ZHAO N, WANG Y, ZHANG Z, et al. Joint Transmit and Receive Beamforming Design for Integrated Sensing and Communication[J/OL]. IEEE Communications Letters, 2022, 26(3): 662-666. DOI: 10.1109/LCOMM.2021.3140093.
[19] AN J, LI H, NG D W K, et al. Fundamental Detection Probability vs. Achievable Rate Tradeoff in Integrated Sensing and Communication Systems[J/OL]. IEEE Transactions on Wireless Communications, 2023, 22(12): 9835-9853. DOI: 10.1109/TWC.2023.3273850.
[20] ZHONG Y, BI T, WANG J, et al. Empowering the V2X Network by Integrated Sensing and Communications: Background, Design, Advances, and Opportunities[J/OL]. IEEE Network, 2022, 36(4): 54-60. DOI: 10.1109/MNET.001.2100688.
[21] CHOI J, VA V, GONZALEZ-PRELCIC N, et al. Millimeter-Wave Vehicular Communication to Support Massive Automotive Sensing[J/OL]. IEEE Communications Magazine, 2016, 54 (12): 160-167. DOI: 10.1109/MCOM.2016.1600071CM.
[22] SAMCZYNSKI P, et al. A concept of GSM-based passive radar for vehicle traffic monitoring [C/OL]//Proc. Microw., Radar, Remote Sens. Symp. (MRRS). 2011: 271-274. DOI: 10.1109/ MRRS.2011.6053652.
[23] LIU F, YUAN W, MASOUROS C, et al. Radar-Assisted Predictive Beamforming for Vehicular Links Communication Served by Sensing[J/OL]. IEEE Transactions on Wireless Communications, 2020, 19(11): 7704-7719. DOI: 10.1109TWC.2020.3015735.
[24] YING Z, CUI Y, MU J, et al. Particle Filter based Predictive Beamforming for Integrated Vehicle Sensing and Communication[C/OL]//Proc. IEEE VTC-Fall. 2021: 1-5. DOI: 10.1109VTC20 21-Fall52928.2021.9625076.
[25] YUAN W, LIU F, MASOUROS C, et al. Bayesian Predictive Beamforming for Vehicular Networks A Low-Overhead Joint Radar-Communication Approach[J/OL]. IEEE Transactions on Wireless Communications, 2021, 20(3): 1442-1456. DOI: 10.1109TWC.2020.3033776.
[26] LIU C, YUAN W, LI S, et al. Learning-Based Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks[J/OL]. IEEE Journal on Selected Areas in Communications, 2022, 40(8): 2317-2334. DOI: 10.1109JSAC.2022.3180803.
[27] MU J, GONG Y, ZHANG F, et al. Integrated Sensing and Communication-Enabled Predictive Beamforming With Deep Learning in Vehicular Networks[J/OL]. IEEE Communications Letters, 2021, 25(10): 3301-3304. DOI: 10.1109LCOMM.2021.3098748.
[28] LIU B, LIU J, KATO N. Optimal Beamformer Design for Millimeter Wave Dual-Functional Radar-Communication Based V2X Systems[J/OL]. IEEE Journal on Selected Areas in Communications, 2022, 40(10): 2980-2993. DOI: 10.1109/JSAC.2022.3196089.
[29] DU Z, LIU F, YUAN W, et al. Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets[J/OL]. IEEE Transactions on Wireless Communications, 2023, 22(6): 3612-3627. DOI: 10.1109/TWC.2022.3219890.
[30] LIU Q, LIANG H, LUO R, et al. Energy-Efficiency Computation Offloading Strategy in UAV Aided V2X Network With Integrated Sensing and Communication[J/OL]. IEEE Open Journal of the Communications Society, 2022, 3: 1337-1346. DOI: 10.1109/OJCOMS.2022.3195703.
[31] LIU Q, LUO R, LIANG H, et al. Energy-Efficient Joint Computation Offloading and Resource Allocation Strategy for ISAC-Aided 6G V2X Networks[J/OL]. IEEE Transactions on Green Communications and Networking, 2023, 7(1): 413-423. DOI: 10.1109/TGCN.2023.3234263.
[32] LI Y, LIU F, DU Z, et al. ISAC-Enabled V2I Networks Based on 5G NR: How Much Can the Overhead Be Reduced?[C/OL]//2023 IEEE International Conference on Communications Workshops (ICC Workshops). 2023: 691-696. DOI: 10.1109/ICCWorkshops57953.2023.102 83528.
[33] KUSCHEL H, CRISTALLINI D, OLSEN K E. Tutorial Passive radar tutorial[J/OL]. IEEE Aerospace and Electronic Systems Magazine, 2019, 34(2): 2-19. DOI: 10.1109MAES.2018.1 60146.
[34] PUCCI L, MATRICARDI E, PAOLINI E, et al. Performance Analysis of a Bistatic Joint Sensing and Communication System[C/OL]//Proc. IEEE Int. Conf. Commun. (ICC), Seoul, South Korea. 2022: 73-78. DOI: 10.1109ICCWorkshops53468.2022.9814645.
[35] CAO N, CHEN Y, GU X, et al. Joint Bi-Static Radar and Communications Designs for Intelligent Transportation[J/OL]. IEEE Transactions on Vehicular Technology, 2020, 69(11): 13060- 13071. DOI: 10.1109TVT.2020.3020218.
[36] MEI W, ZHENG B, YOU C, et al. Intelligent Reflecting Surface-Aided Wireless Networks: From Single-Reflection to Multireflection Design and Optimization[J/OL]. Proc. IEEE, 2022, 110(9): 1380-1400. DOI: 10.1109/JPROC.2022.3170656.
[37] HAN Y, LI N, LIU Y, et al. Artificial Noise Aided Secure NOMA Communications in STARRIS Networks[J/OL]. IEEE Wireless Communications Letters, 2022, 11(6): 1191-1195. DOI: 10.1109/LWC.2022.3161020.
[38] DI RENZO M, ZAPPONE A, DEBBAH M, et al. Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead [J/OL]. IEEE Journal on Selected Areas in Communications, 2020, 38(11): 2450-2525. DOI: 10.1109/JSAC.2020.3007211.
[39] HUANG C, ZAPPONE A, ALEXANDROPOULOS G C, et al. Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication[J/OL]. IEEE Transactions on Wireless Communications, 2019, 18(8): 4157-4170. DOI: 10.1109/TWC.2019.2922609.
[40] WU Q, ZHANG R. Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network[J/OL]. IEEE Communications Magazine, 2020, 58(1): 106- 112. DOI: 10.1109/MCOM.001.1900107.
[41] GUO H, LIANG Y C, CHEN J, et al. Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks[J/OL]. IEEE Transactions on Wireless Communications, 2020, 19(5): 3064-3076. DOI: 10.1109/TWC.2020.2970061.
[42] WU Q, ZHANG R. Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints[J/OL]. IEEE Journal on Selected Areas in Communications, 2020, 38(8): 1735-1748. DOI: 10.1109/JSAC.2020.3000807.
[43] PAN C, REN H, WANG K, et al. Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer[J/OL]. IEEE Journal on Selected Areas in Communications, 2020, 38(8): 1719-1734. DOI: 10.1109/JSAC.2020.3000802.
[44] CUI M, ZHANG G, ZHANG R. Secure Wireless Communication via Intelligent Reflecting Surface[J/OL]. IEEE Wireless Communications Letters, 2019, 8(5): 1410-1414. DOI: 10.110 9/LWC.2019.2919685.
[45] LONG R, LIANG Y C, PEI Y, et al. Active Reconfigurable Intelligent Surface-Aided Wireless Communications[J/OL]. IEEE Transactions on Wireless Communications, 2021, 20(8): 4962- 4975. DOI: 10.1109/TWC.2021.3064024.
[46] CHENG H V, YU W. Multiplexing Gain of Modulating Phases Through Reconfigurable Intelligent Surface[C/OL]//Proc. IEEE Int. Symp. Inf. Theory (ISIT). 2021: 2346-2351. DOI: 10.1109/ISIT45174.2021.9517711.
[47] CHENG H V, YU W. Degree-of-Freedom of Modulating Information in the Phases of Reconfigurable Intelligent Surface[J/OL]. IEEE Transactions on Information Theory, 2024, 70(1): 170-188. DOI: 10.1109/TIT.2023.3332425.
[48] SEDDIK K G. On the Degrees of Freedom of IRS-Assisted Non-Coherent MIMO Communications[J/OL]. IEEE Communications Letters, 2022, 26(5): 1175-1179. DOI: 10.1109/LCOM M.2022.3153556.
[49] NAFEA M, YENER A. Secure Communication in a Multi-antenna Wiretap Channel with a Reconfigurable Intelligent Surface[C/OL]//Proc. 17th Int. Symp. Wireless Commun. Syst. (ISWCS). 2021: 1-6. DOI: 10.1109/ISWCS49558.2021.9562188.
[50] BAFGHI A H A, JAMALI V, NASIRI-KENARI M, et al. Degrees of Freedom of the K-User Interference Channel Assisted by Active and Passive IRSs[J/OL]. IEEE Transactions on Communications, 2022, 70(5): 3063-3080. DOI: 10.1109/TCOMM.2022.3159658.
[51] CHAE S H, LEE K. Cooperative Communication for the Rank-Deficient MIMO Interference Channel with a Reconfigurable Intelligent Surface[J/OL]. IEEE Transactions on Wireless Communications, 2022: 1-1. DOI: 10.1109/TWC.2022.3208881.
[52] JAFAR S A, FAKHEREDDIN M J. Degrees of Freedom for the MIMO Interference Channel [J/OL]. IEEE Transactions on Information Theory, 2007, 53(7): 2637-2642. DOI: 10.1109/TI T.2007.899557.
[53] BOYD S, VANDENBERGHE L. Convex optimization[M]. Cambridge university press, 2004.
[54] HASSANIEN A, AMIN M G, ZHANG Y D, et al. Dual-Function Radar-Communications: Information Embedding Using Sidelobe Control and Waveform Diversity[J/OL]. IEEE Transactions on Signal Processing, 2016, 64(8): 2168-2181. DOI: 10.1109/TSP.2015.2505667.
[55] AHMED A, ZHANG Y D, HIMED B. Multi-user dual-function radar-communications exploiting sidelobe control and waveform diversity[C/OL]//2018 IEEE Radar Conference (Radar- Conf18). 2018: 0698-0702. DOI: 10.1109/RADAR.2018.8378644.
[56] TSE D. Fundamentals of Wireless Communication[J]. Cambridge University Press google schola, 2005, 2: 614-624.
[57] SHI Q, RAZAVIYAYN M, LUO Z Q, et al. An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel[J/OL]. IEEE Transactions on Signal Processing, 2011, 59(9): 4331-4340. DOI: 10.1109TSP.2011.2147784.
[58] CUI Y, LIU F, JING X, et al. Integrating Sensing and Communications for Ubiquitous IoT: Applications, Trends, and Challenges[J/OL]. IEEE Network, 2021, 35(5): 158-167. DOI: 10.1109/MNET.010.2100152.
[59] MEALEY R M. A Method for Calculating Error Probabilities in a Radar Communication System[J/OL]. IEEE Transactions on Space Electronics and Telemetry, 1963, 9(2): 37-42. DOI: 10.1109/TSET.1963.4337601.
[60] LIU F, CUI Y, MASOUROS C, et al. Integrated Sensing and Communications Toward Dual- Functional Wireless Networks for 6G and Beyond[J/OL]. IEEE Journal on Selected Areas in Communications, 2022, 40(6): 1728-1767. DOI: 10.1109JSAC.2022.3156632.
[61] MOZAFFARI M, SAAD W, BENNIS M, et al. A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems[J/OL]. IEEE Communications Surveys & Tutorials, 2019, 21(3): 2334-2360. DOI: 10.1109/COMST.2019.2902862.
[62] GARCIA M H C, MOLINA-GALAN A, BOBAN M, et al. A Tutorial on 5G NR V2X Communications[J/OL]. IEEE Communications Surveys & Tutorials, 2021, 23(3): 1972-2026. DOI: 10.1109/COMST.2021.3057017.
[63] DOKHANCHI S H, MYSORE B S, MISHRA K V, et al. A mmWave Automotive Joint Radar- Communications System[J/OL]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(3): 1241-1260. DOI: 10.1109TAES.2019.2899797.
[64] SUN H, CHIA L G, RAZUL S G. Through-Wall Human Sensing With WiFi Passive Radar [J/OL]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(4): 2135-2148. DOI: 10.1109/TAES.2021.3069767.
[65] MESSER H, ZINEVICH A, ALPERT P. Environmental Monitoring by Wireless Communication Networks[J/OL]. Science, 2006, 312(5774): 713-713. https://www.science.org/doi/abs/10 .1126/science.1120034.
[66] RAPPAPORT T S, SUN S, MAYZUS R, et al. Millimeter Wave Mobile Communications for 5G Cellular: It Will Work![J/OL]. IEEE Access, 2013, 1: 335-349. DOI: 10.1109/ACCESS.2 013.2260813.
[67] 中国联通官方号. 浙江联通打造“5G-A”多维能力网络助力“数智浙江”新发展[EB/OL]. (2023-09-07). https://baijiahao.baidu.com/s?id=1776298736740721506&wfr=spider&for=pc.
[68] 陈珂. 再突破！山东移动5G-A 技术应用迈上新台阶[N/OL]. 人民邮电报, 2024-02-17. https://www.cnii.com.cn/rmydb/202402/t20240217_544017.html.
[69] 吴凡, 沈燕妮. 首个5G-A 通感一体化基站试点在深圳福田开通[N/OL]. 深圳特区报, 2023-07-08. https://www.sohu.com/a/695817360_121384255.
[70] 东南网. 全球首个“5G-A 通感一体低空协同组网”于厦门成功试点[EB/OL]. (2023-12- 28). https://baijiahao.baidu.com/s?id=1786487279044594108&wfr=spider&for=pc.
[71] 徐冠英. 我省积极探索5G-A 技术试点——一体覆盖“空天地”锻造物联“加速器” [N/OL]. 新华日报, 2023-11-12. https://xh.xhby.net/pc/con/202311/12/content_1261802.html.
[72] LIU F, MASOUROS C, PETROPULU A P, et al. Joint Radar and Communication Design Applications, State-of-the-Art, and the Road Ahead[J/OL]. IEEE Transactions on Communications, 2020, 68(6): 3834-3862. DOI: 10.1109TCOMM.2020.2973976.
[73] SCHMIDT R. Multiple emitter location and signal parameter estimation[J/OL]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276-280. DOI: 10.1109/TAP.1986.1143830.
[74] ZHANG L, WANG H. Device-Free Tracking via Joint Velocity and AOA Estimation With Commodity WiFi[J/OL]. IEEE Sensors Journal, 2019, 19(22): 10662-10673. DOI: 10.1109/JS EN.2019.2929580.
[75] ZHANG D, WU D, NIU K, et al. Practical Issues and Challenges in CSI-based Integrated Sensing and Communication[C/OL]//Proc. IEEE Int. Conf. Commun. Workshops (ICC Workshops). 2022: 836-841. DOI: 10.1109/ICCWorkshops53468.2022.9814523.
[76] CHENG X, DUAN D, GAO S, et al. Integrated Sensing and Communications (ISAC) for Vehicular Communication Networks (VCN)[J/OL]. IEEE Internet of Things Journal, 2022, 9 (23): 23441-23451. DOI: 10.1109/JIOT.2022.3191386.
[77] LIU A, HUANG Z, LI M, et al. A Survey on Fundamental Limits of Integrated Sensing and Communication[J/OL]. IEEE Communications Surveys & Tutorials, 2022, 24(2): 994-1034. DOI: 10.1109/COMST.2022.3149272.
[78] BEN-TAL A, NEMIROVSKI A. Lectures on modern convex optimization: analysis, algorithms, and engineering applications[M]. SIAM, 2001.
[79] 陈路漫, 陈跃, 王姝. 亚运有我| 亚运场馆5G 不够用？一张薄板让信号增强10 倍[N/OL]. 科技金融时报, 2023-09-14. https://news.sohu.com/a/720519923_121777418.
[80] 无线电管理局. 辽宁省工业和信息化厅开展电磁兼容分析助力通信新技术发展[EB/OL]. (2024-02-08). https://www.miit.gov.cn/jgsj/wgj/dfjx/art/2024/art_607620de543945acbd77d27 5c3a5ece1.html.