Journal of Guangdong University of Technology ›› 2024, Vol. 41 ›› Issue (03): 110-118.doi: 10.12052/gdutxb.230024

• Information and Communication Technology • Previous Articles     Next Articles

Double Reconfigurable Intelligent Surface-aided Green Internet of Things Edge Computing for Research on Computation Capacity

Chen Yan-Long, Zeng Xiang, Li Yu-Long, Wang Feng   

  1. School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2023-03-16 Online:2024-05-25 Published:2024-06-14

Abstract: In order to solve the micro battery energy problem of terminal Internet of Things user devices in computation-intensive applications, green renewable energy harvesting technology and double reconfigurable intelligent surfaces(RIS) technology enabling edge computing were studied and a green Internet of Things edge computing system assisted by double-RIS was constructed, effectively extending the computing life of terminal Internet of Things user devices and improving system computation capacity. Firstly, a multi-user cascade fading channel model assisted by double-RIS was established, and a multi-slot random arrival model of green renewable energy harvesting was established to model the causal constraints of energy supply and demand of Internet of Things terminal devices. Secondly, based on the maximization of system computation capacity, the joint optimization design problem of terminal local computing rate, edge computing offloading power and phase shift of RISs was modeled. This design problem belongs to a class of complex non-convex optimization problem. To this end, lightweight multi-stage optimization technology was adopted to rapidly and iteratively design variables such as local computation, computation offloading and phase shift of RISs, etc, to complete the design of green Internet of Things edge computing system. The experimental results show that the performance gains of the proposed scheme are better than the existing benchmark schemes, and the proposed scheme is equivalent to the scheme based on semidefinite relaxation algorithm under less system computing time.

Key words: edge computing, double reconfigurable intelligent surfaces, energy harvesting, computation offloading

CLC Number: 

  • F224.32
[1] WANG F, XING H, J XU. Real-time resource allocation for wireless powered multiuser mobile edge computing with energy and task causality [J]. IEEE Transactions on Communications, 2020, 68(11): 7140-7155.
[2] WANG F, XU J, CUI S. Optimal energy allocation and task offloading policy for wireless powered mobile edge computing systems [J]. IEEE Transactions on Wireless Communications, 2020, 19(4): 2443-2459.
[3] LIN Z, WANG F, LIU L. Computation rate maximization for multiuser mobile edge computing systems with dynamic energy arrivals[C]// 2021 IEEE/CIC International Conference on Communications in China (ICCC) , Xiamen: IEEE, 2021: 312-317.
[4] XU Y, ZHANG T, LIU Y et al. Computation capacity enhancement by joint UAV and RIS design in IoT [J]. IEEE Internet of Things Journal, 2022, 9(20): 20590-20603.
[5] YANG Y, HU Y, GURSOY M C. Energy efficiency analysis in RIS-aided MEC networks with finite blocklength codes[C]//2022 IEEE Wireless Communications and Networking Conference (WCNC) . Austin: IEEE, 2022: 423-428.
[6] WU Q, ZHANG R. Intelligent reflecting surface enhanced wireless network: joint active and passive beamforming design[C]//2018 IEEE Global Communications Conference (GLOBECOM) . A-bu Dhabi: IEEE, 2018: 1-6.
[7] CHEN G, WU Q. Computation rate maximization for IRS-aided wireless powered MEC systems [C]//2022 IEEE Wireless Communications and Networking Conference (WCNC) . Austin: IEEE, 2022: 417-422.
[8] LI A, LIU Y, LI M. Joint scheduling design in wireless powered MEC IoT networks aided by reconfigurable intelligent surface[C]//2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops) . Xiamen: IEEE, 2021: 159-164.
[9] ZHANG D, CHEN Z, AWAD M K. Utility- optimal resource management and allocation algorithm for energy harvesting cognitive radio sensor networks [J]. IEEE Journal on Selected Areas in Communications, 2016, 34(12): 3552-3565.
[10] LI H, XIONG K, DONG R, et al. Joint active and passive beamforming in IRS-enhanced wireless powered MEC networks [J]. IEEE Wireless Communications Letters, 2022, 11(11): 2285-2289.
[11] ARDAH K, GHEREKHLOO S, DEALMEIDA A L F, et al. Double-RIS versus single-RIS aided systems: tensor-based mimo channel estimation and design perspectives[C]// 2022 IEEE International Conference. Singapore: IEEE, 2022: 5183-5187.
[12] GUO S, HOU Y, MAO J, et al. Double RIS-based hybrid beamforming design for MU-MISO mmWave communication systems[C]// 2022 IEEE/CIC International Conference on Communications. Foshan, China: IEEE, 2022: 220-225.
[13] XIE W, LI B, XIONG Y, et al. Energy efficient collaborative computation for double-RIS assisted mobile edge networks [J]. Physical Communication, 2022, 53: 101774.
[14] 李斌, 刘文帅, 谢万城, 等. 智能超表面赋能移动边缘计算部分任务卸载策略[J]. 电子与信息学报, 2022, 44(7): 2309-2316.
LI B, LIU W S, XIE W C, et al. Partial computation offloading for double-RIS assisted multiuser mobile edge computing networks [J]. Journal of Electronics & Information Technology, 2022, 44(7): 2309-2316.
[15] 龙文尧. 基于AO-CCP的双智能反射面辅助的鲁棒性波束设计[J]. 无线电通信技术, 2022, 48(2): 276-283.
LONG W Y. Robust millimeter-wave wireless beamforming design assited by double Interlligent reflecting surfaces based on AO-CCP method [J]. Radio Communications Technology, 2022, 48(2): 276-283.
[16] 陈健锋, 崔苗, 张广驰, 等. 双智能反射平面辅助无线携能通信系统的安全通信优化[J]. 电信科学, 2022, 38(1): 47-60.
CHEN J F, CUI M, ZHANG G C, et al. Secure communication optimization for double-IRS assisted SWIPT system [J]. Telecommunications Science, 2022, 38(1): 47-60.
[17] LIU M, LI X, NING B, et al. Deep learning-based channel estimation for double-RIS aided massive MIMO system [J]. IEEE Wireless Communications Letters, 2023, 12(1): 70-74.
[18] 李岩, 李聪, 徐志豪. 智能反射面辅助无线通信系统的信道估计算法设计[J]. 现代信息科技, 2023, 7(1): 68-71.
LI Y, LI C, XU Z H. Channel estimation algorithm design for intelligent reflecting surface assisted wireless communication system [J]. Modern Information Technology, 2023, 7(1): 68-71.
[19] SUDEVALAYAM S, KULKAMNI P. Energy harvesting sensor nodes: survey and implications [J]. IEEE Communications Surveys & Tutorials, 2011, 13(3): 443-461.
[20] NING B Y, CHEN Z, CHEN W J, et al. Beam-forming optimization for intelligent reflecting surface assisted MIMO: a Sum-Path-Gain maximization approach [J]. IEEE Wireless Communications Letters, 2020, 9(7): 1105-1109.
[21] 谢万城, 李斌, 代玥玥. 空中智能反射面辅助边缘计算中基于PPO的任务卸载方案[J]. 计算机科学, 2022, 49(6): 3-11.
XIE W C, LI B, DAI Y Y. PPO base task offloading scheme in aerial reconfigurable intelligent surface assited edge computing [J]. Computer Science, 2022, 49(6): 3-11.
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