Robust Resource Allocation Algorithm for Reconfigurable Intelligent Surface-assisted Backscatter Communication Systems Based on Statistical Channel State Information
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摘要: 为解决传统反向散射通信(BackCom)系统存在通信距离短、系统吞吐量较低和克服信道不确定性能力差的问题，该文提出一种基于统计信道状态信息(CSI)的智能反射面(RIS)辅助反向散射通信系统鲁棒资源分配算法。考虑功率站最大发射功率约束、反射节点的能量中断约束和吞吐量中断约束、反射系数约束、RIS相移约束和信息传输时间约束，建立了系统加权和吞吐量最大化的鲁棒资源分配模型；利用伯恩斯坦不等式、交替优化和半正定松弛方法，将原非凸问题转换成凸优化问题求解，并提出一种基于迭代的鲁棒吞吐量最大化算法。仿真结果表明，与传统非鲁棒资源分配算法和无RIS资源分配算法相比，所提算法具有更强的鲁棒性和更高的吞吐量。Abstract: In order to solve the problems of short-distance communication, lower system throughput and the effects of channel uncertainties in traditional Backscatter Communication (BackCom) systems, a robust resource allocation algorithm for a Reconfigurable Intelligent Surface (RIS)-assisted backscatter communication system with statistical Channel State Information (CSI) is proposed in this paper. A system weighting and sum throughput-maximization robust resource allocation model is formulated by considering the maximum transmit power constraint of the power station, the energy outage constraint and throughput outage constraint of backscatter nodes, the reflection coefficient constraint, the phase shift constraint of the RIS and the information transmission time constraint; Then, the original non-convex problem is transformed into a convex optimization problem by using the methods of Bernstein-type inequality, the alternating optimization, and the semi-definite relaxation technique. An iteration-based robust throughput maximization algorithm is designed. Simulation results show that the proposed algorithm had stronger robustness and higher throughput compared it with the traditional non-robust resource allocation algorithm and the resource allocation algorithm without RIS.
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算法1 基于迭代的鲁棒吞吐量最大化算法 初始化系统参数: $ M,K,L,T,P_k^C,R_k^{\min},{\bar g_k},{{\boldsymbol{g}}_{l,k}},{\bar {\boldsymbol{f}}_k},{\bar {\boldsymbol{h}}_k},\sigma _{{H},K}^2 $,
$\sigma _{h,k}^2,{P_{\max}},{\delta _k} $, $ {\upsilon _k},{\tilde {\boldsymbol{\varTheta}} ^{(l - 1)}},t_k^{(l - 1)},\alpha _k^{(l - 1)} $，收敛精度$ \varepsilon , $设置内
层最大迭代次数${L_{\max}},$初始化迭代次数$ l = 0, $令
$ {R_{{\mathrm{sum}}}} = \sum\nolimits_{k = 1}^K {{\psi _k}{R_k}} {\text{ }} $(1) While $ |R_{{\mathrm{sum}}}^{(l)} - R_{{\mathrm{sum}}}^{(l - 1)}| \ge \varepsilon $或$l \le {L_{\max}},$do (2) 设置迭代次数$ l = l + 1 $ (3) Repeat (4) 固定$ \{ {\tilde {\boldsymbol{\varTheta}} ^{(l - 1)}},t_k^{(l - 1)},\alpha _k^{(l - 1)}\} $求解式(20)得到$ {{\boldsymbol{W}}^{(l)}} $，进
而得到$ {{\boldsymbol{w}}_k}^* $并更新$ {\boldsymbol{w}}_k^{(l)}; $(5) Until收敛 (6) Repeat (7) 固定$ \{ {\boldsymbol{w}}_k^{(l)},\alpha _k^{(l - 1)}\} $求解式(23)得到$ \{ {\tilde {\boldsymbol{\varTheta }}^{(l)}},t_k^{(l)}\} $进而得
到$ \theta _l^ * $和$ t_k^ * $并更新$ \{ \theta _l^{(l)},t_k^{(l)}\} $(8) Until收敛 (9) Repeat (10) 固定$ \{ {\boldsymbol{w}}_k^{(l)},\theta _l^{(l)},t_k^{(l)}\} $求解式(25)得到$ \alpha _k^ * $并更新$ \alpha _k^{(l)} $ (11) Until收敛 (12) 将$ \{ {\boldsymbol{w}}_k^{(l)},\theta _l^{(l)},t_k^{(l)},\alpha _k^{(l)}\} $带入更新$ {R_{{\mathrm{sum}}}} $ (13) End while (14) 得到最优的$ \{ {{\boldsymbol{w}}_k}^* = {\boldsymbol{w}}_k^{(l)},\theta _l^ * = \theta _l^{(l)},t_k^ * = t_k^{(l)},\alpha _k^ * = \alpha _k^{(l)}\} $ 
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[1] XU Yongjun, GUI Guan, GACANIN Haris, et al. A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges[J]. IEEE Communications Surveys & Tutorials, 2021, 23(2): 668–695. doi: 10.1109/COMST.2021.3059896. [2] XU Yongjun, QIN Zhijin, GUI Guan, et al. Energy efficiency maximization in NOMA enabled backscatter communications with QoS guarantee[J]. IEEE Wireless Communications Letters, 2021, 10(2): 353–357. doi: 10.1109/LWC.2020.3031042. [3] XU Yongjun, XIE Hao, WU Qingqing, et al. Robust max-min energy efficiency for RIS-aided HetNets with distortion noises[J]. IEEE Transactions on Communications, 2022, 70(2): 1457–1471. doi: 10.1109/TCOMM.2022.3141798. [4] 张晓茜, 徐勇军. 面向零功耗物联网的反向散射通信综述[J]. 通信学报, 2022, 43(11): 199–212. doi: 10.11959/j.issn.1000−436x.2022199.ZHANG Xiaoxi and XU Yongjun. Survey on backscatter communication for zero-power IoT[J]. Journal on Communications, 2022, 43(11): 199–212. doi: 10.11959/j.issn.1000−436x.2022199. [5] LI Dong. How many reflecting elements are needed for energy- and spectral-efficient intelligent reflecting surface-assisted communication[J]. IEEE Transactions on Communications, 2022, 70(2): 1320–1331. doi: 10.1109/TCOMM.2021.3128544. [6] 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]. IEEE Journal on Selected Areas in Communications, 2020, 38(11): 2450–2525. doi: 10.1109/JSAC.2020.3007211. [7] MA Hui, ZHANG Haijun, ZHANG Ning, et al. Reconfigurable intelligent surface with energy harvesting assisted cooperative ambient backscatter communications[J]. IEEE Wireless Communications Letters, 2022, 11(6): 1283–1287. doi: 10.1109/LWC.2022.3164257. [8] HAKIMI A, ZARGARI S, TELLAMBURA C, et al. IRS-enabled backscattering in a downlink non-orthogonal multiple access system[J]. IEEE Communications Letters, 2022, 26(12): 2984–2988. doi: 10.1109/LCOMM.2022.3204489. [9] GALAPPATHTHIGE D L, REZAEI F, TELLAMBURA C, et al. RIS-empowered ambient backscatter communication systems[J]. IEEE Wireless Communications Letters, 2023, 12(1): 173–177. doi: 10.1109/LWC.2022.3220158. [10] ZUO Jiakou, LIU Yuanwei, YANG Liang, et al. Reconfigurable intelligent surface enhanced NOMA assisted backscatter communication system[J]. IEEE Transactions on Vehicular Technology, 2021, 70(7): 7261–7266. doi: 10.1109/TVT.2021.3087582. [11] LV Weigang, BAI Jiale, YAN Qing, et al. RIS-assisted green secure communications: Active RIS or passive RIS?[J]. IEEE Wireless Communications Letters, 2023, 12(2): 237–241. doi: 10.1109/LWC.2022.3221609. [12] REHMAN H U, BELLILI F, MEZGHANI A, et al. Modulating intelligent surfaces for multiuser MIMO systems: Beamforming and modulation design[J]. IEEE Transactions on Communications, 2022, 70(5): 3234–3249. doi: 10.1109/TCOMM.2022.3160540. [13] ZHAO Jinqiu, YE Jia, GUO Shuaishuai, et al. Reconfigurable intelligent surface enabled joint backscattering and communication[J]. IEEE Transactions on Vehicular Technology, 2023: 1–12. doi: 10.1109/TVT.2023.3305330. [14] 吕斌, 曹怡, 李健, 等. IRS辅助的认知反向散射通信网络性能增强方案[J]. 通信学报, 2021, 42(12): 172–181. doi: 10.11959/ j.issn.1000−436x.2021233.LV Bin, CAO Yi, LI Jian, et al. Performance enhancement scheme for IRS-assisted cognitive backscatter communication network[J]. Journal on Communications, 2021, 42(12): 172–181. doi: 10.11959/j.issn.1000−436x.2021233. [15] GONG Shimin, HUANG Xiaoxia, XU Jing, et al. Backscatter relay communications powered by wireless energy beamforming[J]. IEEE Transactions on Communications, 2018, 66(7): 3187–3200. doi: 10.1109/TCOMM.2018.2809613. [16] 张晓茜, 徐勇军, 吴翠先, 等. 智能反射面增强的全双工环境反向散射通信系统波束成形算法[J]. 电子与信息学报, 2024, 46(3): 914–924. doi: 10.11999/JEIT230356.ZHANG Xiaoxi, XU Yongjun, WU Cuixian, et al. Beamforming design for reconfigurable intelligent surface enhanced full-duplex ambient backscatter communication networks[J]. Journal of Electronics & Information Technology, 2024, 46(3): 914–924. doi: 10.11999/JEIT230356. [17] GU Bowen, LI Dong, LIU Ye, et al. Exploiting constructive interference for backscatter communication systems[J]. IEEE Transactions on Communications, 2023, 71(7): 4344–4359. doi: 10.1109/TCOMM.2023.3277519. [18] WANG Kunyun, SO A M C, CHANG T H, et al. Outage constrained robust transmit optimization for multiuser MISO downlinks: Tractable approximations by conic optimization[J]. IEEE Transactions on Signal Processing, 2014, 62(21): 5690–5705. doi: 10.1109/TSP.2014.2354312. [19] XIN Yanan, XU Yongjun, LIU Qilie, et al. Robust and outage-constrained energy efficiency optimization in RIS-assisted NOMA networks[C]. 2022 IEEE 95th Vehicular Technology Conference, Helsinki, Finland, 2022: 1–5. doi: 10.1109/VTC2022-Spring54318.2022.9860985. [20] ZHOU Gui, PAN Cunhua, REN Hong, et al. A framework of robust transmission design for IRS-aided MISO communications with imperfect cascaded channels[J]. IEEE Transactions on Signal Processing, 2020, 68: 5092–5106. doi: 10.1109/TSP.2020.3019666. [21] XU Yongjun, JIANG Siqiao, XUE Qing, et al. Throughput maximization for NOMA-based cognitive backscatter communication networks with imperfect CSI[J]. IEEE Internet of Things Journal, 2023, 10(22): 19595–19606. doi: 10.1109/JIOT.2023.3289181. [22] YU Xianghao, XU Dongfang, SUN Ying, et al. Robust and secure wireless communications via intelligent reflecting surfaces[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(11): 2637–2652. doi: 10.1109/JSAC.2020.3007043. [23] LI Xingwang, ZHAO Mengle, ZENG Ming, et al. Hardware impaired ambient backscatter NOMA systems: Reliability and security[J]. IEEE Transactions on Communications, 2021, 69(4): 2723–2736. doi: 10.1109/TCOMM.2021.3050503. [24] LI Xingwang, WANG Qunshu, ZENG Ming, et al. Physical-layer authentication for ambient backscatter-aided NOMA symbiotic systems[J]. IEEE Transactions on Communications, 2023, 71(4): 2288–2303. doi: 10.1109/TCOMM.2023.3245659. [25] ZHANG Yu, LI Bin, GAO Feifei, et al. A robust design for ultra reliable ambient backscatter communication systems[J]. IEEE Internet of Things Journal, 2019, 6(5): 8989–8999. doi: 10.1109/JIOT.2019.2925843. -
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