A Robust Fairness Resource Allocation Algorithm for SWIPT-Enabled Internet of Things with IRS
-
摘要: 针对6G物联网中信道误差影响与用户采集能量的公平性问题，该文在用户信干噪比受限、发射功率约束和反射相位模一约束的条件下，研究了智能反射面(IRS)辅助的信息与能量同传(SWIPT)系统中公平性采集能量最大化问题。为了解决该非凸问题，分别运用Schur-Complement和S-Procedure将无限维约束转换为有限维的矩阵线性不等式，然后利用罚函数和连续凸逼近的方法将难以求解的原问题转化为标准的凸优化问题，进而提出了一种迭代的鲁棒公平性能量采集算法。数值结果表明，所提鲁棒优化算法能够明显提升网络采集的公平性能量。Abstract: Focusing on examine the influence of channel errors and the fairness of energy collected by users in 6G internet of things, the problem of maximizing fairness energy for Intelligent Reflecting Surface (IRS)-aided Simultaneous Wireless Information and Power Transfer (SWIPT) is examined when the users have a limited signal-to-interference noise ratio, a transmission power constraint and a reflection phase mode one constraint. As part of the process of solving the nonconvex problem, Schur Complete and S-Process are used to convert the infinite dimensional constraint into a linear inequality involving a finite dimensional matrix, and then the original difficult-to-solve problem is transformed into a standard convex optimization problem using the penalty function and continuous convex approximation, and then an iterative robust fairness energy acquisition algorithm is proposed. Numerical results indicate that the proposed robust optimization algorithm improves the fairness of network harvested energy significantly compared to previous algorithms.
-
算法1 所提鲁棒优化算法 设置最大迭代次数$ {L_{\max }} $, $ m = 0 $，和$ {{\boldsymbol{q}}^{\left( 0 \right)}} $， (1) while $ m \le {L_{\max }} $ do (2) 固定$ {{\boldsymbol{q}}^{\left( m \right)}} $，求解子问题1，输出$ \left\{ {{\boldsymbol{w}}_k^ * ,\rho _k^{\left( * \right)}} \right\} $, $ {t^{\left( * \right)}} $和$ {\boldsymbol{V}}_e^ * $，更
新$ {\boldsymbol{w}}_k^{\left( {m + 1} \right)} = {\boldsymbol{w}}_k^ * $, $ {\boldsymbol{V}}_e^{\left( {m + 1} \right)} = {\boldsymbol{V}}_e^{\left( * \right)} $, $ \rho _k^{\left( {m + 1} \right)} = \rho _k^{\left( * \right)} $,
$ {t^{\left( {m + 1} \right)}} = {t^{\left( * \right)}} $(3) 给定$ {\boldsymbol{w}}_k^{\left( {m + 1} \right)} $, $ {\boldsymbol{V}}_e^{\left( {m + 1} \right)} $, $ \rho _k^{\left( {m + 1} \right)} $和$ {t^{\left( {m + 1} \right)}} $，求解子问题2，
输出$ {{\boldsymbol{q}}^{\left( {m + 1} \right)}} $(4) 令$ m = m + 1 $ (5) end while (6) 输出$ {\boldsymbol{w}}_k^ * $, $ {\boldsymbol{V}}_e^{\left( * \right)} $, $ \rho _k^{\left( * \right)} $, $ {t^{\left( * \right)}} $和$ {{\boldsymbol{q}}^{\left( * \right)}} $ 
下载: 导出CSV
-
[1] XU Yongjun, XIE Hao, LI Dong, et al. Energy-efficient beamforming for heterogeneous industrial IoT networks with phase and distortion noises[J]. IEEE Transactions on Industrial Informatics, 2022, 18(11): 7423–7434. doi: 10.1109/TII.2022.3158612 [2] XU Yongjun, GUI Guan, GACANIN H, 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 [3] WANG Dongming, ZHANG Chuan, DU Yongqiang, et al. Implementation of a cloud-based cell-free distributed massive MIMO system[J]. IEEE Communications Magazine, 2020, 58(8): 61–67. doi: 10.1109/MCOM.001.2000106 [4] ZHAI Chao, LI Yujun, LI Chunguo, et al. Cognitive relaying with wireless energy harvesting and accumulation[J]. IEEE Systems Journal, 2021, 15(1): 629–640. doi: 10.1109/JSYST.2020.2991235 [5] XU Yongjun, GAO Zhengnian, WANG Zhengqiang, et al. RIS-Enhanced WPCNs: Joint Radio Resource Allocation and Passive Beamforming Optimization[J]. IEEE Transactions on Vehicular Technology, 2021, 70(8): 7980–7991. doi: 10.1109/TVT.2021.3096603 [6] 徐勇军, 高正念, 王茜竹, 等. 基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法[J]. 电子与信息学报, 2022, 44(7): 2317–2324. doi: 10.11999/JEIT210714XU Yongjun, GAO Zhengnian, WANG Qianzhu, et al. Robust energy efficiency maximization algorithm for intelligent reflecting surface-aided wireless powered-communication networks[J]. Journal of Electronics &Information Technology, 2022, 44(7): 2317–2324. doi: 10.11999/JEIT210714 [7] GAO Zhengnian, XU Yongjun, WANG Qianzhu, et al. Outage-constrained energy efficiency maximization for RIS-assisted WPCNs[J]. IEEE Communications Letters, 2021, 25(10): 3370–3374. doi: 10.1109/LCOMM.2021.3101657 [8] JI Taotao, HUA Meng, LI Chunguo, et al. A robust IRS-aided wireless information surveillance design with bounded channel errors[J]. IEEE Wireless Communications Letters, 2022, 11(10): 2210–2214. doi: 10.1109/LWC.2022.3197228 [9] 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 [10] MENSI N and RAWAT D B. On the performance of partial RIS selection vs. Partial relay selection for vehicular communications[J]. IEEE Transactions on Vehicular Technology, 2022, 71(9): 9475–9489. doi: 10.1109/TVT.2022.3177130 [11] XU Wangyang, AN Jiancheng, XU Yongjun, et al. Time-varying channel prediction for RIS-assisted MU-MISO networks via deep learning[J]. IEEE Transactions on Cognitive Communications and Networking, 2022, 8(4): 1802–1815. doi: 10.1109/TCCN.2022.3188153 [12] AGRAWAL N, BANSAL A, SINGH K, et al. Performance evaluation of RIS-assisted UAV-enabled vehicular communication system with multiple non-identical interferers[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 9883–9894. doi: 10.1109/TITS.2021.3123072 [13] JI Baofeng, WANG Yanan, XING Ling, et al. IRS-driven cybersecurity of healthcare cyber physical systems[J] IEEE Transactions on Network Science and Engineering, 2022. [14] KISSELEFF S, MARTINS W A, AI-HRAISHAWI H, et al. Reconfigurable intelligent surfaces for smart cities: Research challenges and opportunities[J]. IEEE Open Journal of the Communications Society, 2020, 1: 1781–1797. doi: 10.1109/OJCOMS.2020.3036839 [15] HOANG T M, DINH-VAN S, BARN B, et al. RIS-aided smart manufacturing: Information transmission and machine health monitoring[J]. IEEE Internet of Things Journal, 2022, 9(22): 22930–22943. doi: 10.1109/JIOT.2022.3187189 [16] SONG Kang, NIE Mengyun, JIANG Jing, et al. On the secrecy for relay-aided SWIPT internet of things system with cooperative eavesdroppers[J]. IEEE Access, 2021, 9: 28204–28212. doi: 10.1109/ACCESS.2021.3058504 [17] KRIKIDIS I. SWIPT in 3-D bipolar Ad hoc networks with sectorized antennas[J]. IEEE Communications Letters, 2016, 20(6): 1267–1270. doi: 10.1109/LCOMM.2016.2557319 [18] WEN Zhigang, GUO Zhimei, BEAULIEU N C, et al. Robust beamforming design for multi-user MISO full-duplex SWIPT system with channel state information uncertainty[J]. IEEE Transactions on Vehicular Technology, 2019, 68(2): 1942–1947. doi: 10.1109/TVT.2018.2884514 [19] JANG S, LEE H, KANG S, et al. Energy efficient SWIPT systems in multi-cell MISO networks[J]. IEEE Transactions on Wireless Communications, 2018, 17(12): 8180–8194. doi: 10.1109/TWC.2018.2874646 [20] WU Qingqing and ZHANG Rui. Weighted sum power maximization for intelligent reflecting surface aided SWIPT[J]. IEEE Wireless Communications Letters, 2020, 9(5): 586–590. doi: 10.1109/LWC.2019.2961656 [21] WU Qingqing and ZHANG Rui. Beamforming optimization for wireless network aided by intelligent reflecting surface with discrete phase shifts[J]. IEEE Transactions on Communications, 2020, 68(3): 1838–1851. doi: 10.1109/TCOMM.2019.2958916 [22] TANG Yizheng, MA Ganggang, XIE Hailiang, et al. Joint transmit and reflective beamforming design for IRS-assisted multiuser MISO SWIPT systems[C]. ICC 2020 – 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020: 1–6. [23] PAN Cunhua, REN Hong, WANG Kezhi, et al. Intelligent reflecting surface aided MIMO broadcasting for simultaneous wireless information and power transfer[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(8): 1719–1734. doi: 10.1109/JSAC.2020.3000802 [24] LIU Jingxian, XIONG Ke, LU Yang, et al. Energy efficiency in secure IRS-aided SWIPT[J]. IEEE Wireless Communications Letters, 2020, 9(11): 1884–1888. doi: 10.1109/LWC.2020.3006837 [25] BOYD S and VANDENBERGHE L. Convex Optimization[M]. Cambridge: Cambridge University Press, 2004: 387–389. -
图(4) / 表(1)
计量
- 文章访问数: 353
- HTML全文浏览量: 174
- PDF下载量: 95
- 被引次数: 0
下载:
