Citation: | SU Jian, QIAN Zhen, LI Bin. Digital Twin Empowered Task Offloading for RIS-Assisted Edge Computing Networks[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2416-2424. doi: 10.11999/JEIT220180 |
[1] |
ZHANG Jiayi, LIU Heng, WU Qingqing, et al. RIS-aided next-generation high-speed train communications: Challenges, solutions, and future directions[J]. IEEE Wireless Communications, 2021, 28(6): 145–151. doi: 10.1109/MWC.001.2100170
|
[2] |
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, 待发表.
XU 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, To be published.
|
[3] |
MAO Yuyi, YOU Changsheng, ZHANG Jun, et al. A survey on mobile edge computing: The communication perspective[J]. IEEE Communications Surveys & Tutorials, 2017, 19(4): 2322–2358. doi: 10.1109/COMST.2017.2745201
|
[4] |
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
|
[5] |
XU Yongjun, GU Bowen, HU R Q, et al. Joint computation offloading and radio resource allocation in MEC-based wireless-powered backscatter communication networks[J]. IEEE Transactions on Vehicular Technology, 2021, 70(6): 6200–6205. doi: 10.1109/TVT.2021.3077094
|
[6] |
CHEN Yuanbin, WANG Ying, ZHANG Jiayi, et al. QoS-driven spectrum sharing for reconfigurable intelligent surfaces (RISs) aided vehicular networks[J]. IEEE Transactions on Wireless Communications, 2021, 20(9): 5969–5985. doi: 10.1109/TWC.2021.3071332
|
[7] |
SHI Enyu, ZHANG Jiayi, CHEN Shuaifei, et al. Wireless energy transfer in RIS-aided cell-free massive MIMO systems: Opportunities and challenges[J]. IEEE Communications Magazine, 2022, 60(3): 26–32. doi: 10.1109/MCOM.001.2100671
|
[8] |
ZHANG Yan, ZHANG Jiayi, DI RENZO M, et al. Reconfigurable intelligent surfaces with outdated channel state Information: Centralized vs. distributed deployments[J]. IEEE Transactions on Communications, 2022, 70(4): 2742–2756. doi: 10.1109/TCOMM.2022.3146344
|
[9] |
JIN Yu, ZHANG Jiayi, HUANG Chongwen, et al. Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation[J]. IEEE Transactions on Vehicular Technology, 2022, 71(2): 2134–2139. doi: 10.1109/TVT.2021.3132305
|
[10] |
JIN Yu, ZHANG Jiayi, ZHANG Xiaodan, et al. Channel estimation for semi-passive reconfigurable intelligent surfaces with enhanced deep residual networks[J]. IEEE Transactions on Vehicular Technology, 2021, 70(10): 11083–11088. doi: 10.1109/TVT.2021.3109937
|
[11] |
YANG Zhaohui, XU Wei, HUANG Chongwen, et al. Beamforming design for multiuser transmission through reconfigurable intelligent surface[J]. IEEE Transactions on Communications, 2021, 69(1): 589–601. doi: 10.1109/TCOMM.2020.3028309
|
[12] |
HUANG Chongwen, ZAPPONE A, ALEXANDROPOULOS G C, et al. Reconfigurable intelligent surfaces for energy efficiency in wireless communication[J]. IEEE Transactions on Wireless Communications, 2019, 18(8): 4157–4170. doi: 10.1109/TWC.2019.2922609
|
[13] |
BAI Tong, PAN Cunhua, DENG Yansha, et al. Latency minimization for intelligent reflecting surface aided mobile edge computing[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(11): 2666–2682. doi: 10.1109/JSAC.2020.3007035
|
[14] |
CHU Zheng, XIAO Pei, SHOJAFAR M, et al. Intelligent reflecting surface assisted mobile edge computing for internet of things[J]. IEEE Wireless Communications Letters, 2021, 10(3): 619–623. doi: 10.1109/LWC.2020.3040607
|
[15] |
WANG Qun, ZHOU Fuhui, HU Han, et al. Energy-efficient design for IRS-assisted MEC networks with NOMA[C]. 2021 13th International Conference on Wireless Communications and Signal Processing (WCSP), Changsha, China, 2021: 1–6.
|
[16] |
LI Zhiyang, CHEN Ming, YANG Zhaohui, et al. Energy efficient reconfigurable intelligent surface enabled mobile edge computing networks with NOMA[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(2): 427–440. doi: 10.1109/TCCN.2021.3068750
|
[17] |
HUANG Shanfeng, WANG Shuai, WANG Rui, et al. Reconfigurable intelligent surface assisted mobile edge computing with heterogeneous learning tasks[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(2): 369–382. doi: 10.1109/TCCN.2021.3056707
|
[18] |
WU Yiwen, ZHANG Ke, and ZHANG Yan. Digital twin networks: A survey[J]. IEEE Internet of Things Journal, 2021, 8(18): 13789–13804. doi: 10.1109/JIOT.2021.3079510
|
[19] |
DAI Yueyue, ZHANG Ke, MAHARJAN S, et al. Deep reinforcement learning for stochastic computation offloading in digital twin networks[J]. IEEE Transactions on Industrial Informatics, 2020, 17(7): 4968–4977. doi: 10.1109/TII.2020.3016320
|
[20] |
LU Yunlong, HUANG Xiaohong, ZHANG Ke, et al. Low-latency federated learning and blockchain for edge association in digital twin empowered 6G networks[J]. IEEE Transactions on Industrial Informatics, 2020, 17(7): 5098–5107. doi: 10.1109/TII.2020.3017668
|
[21] |
SUN Wen, ZHANG Haibin, WANG Rong, et al. Reducing offloading latency for digital twin edge networks in 6G[J]. IEEE Transactions on Vehicular Technology, 2020, 69(10): 12240–12251. doi: 10.1109/TVT.2020.3018817
|
[22] |
LIU Tong, TANG Lun, WANG Weili, et al. Digital-twin-assisted task offloading based on edge collaboration in the digital twin edge network[J]. IEEE Internet of Things Journal, 2022, 9(2): 1427–1444. doi: 10.1109/JIOT.2021.3086961
|
[23] |
WU Qingqing and ZHANG Rui. Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming[J]. IEEE Transactions on Wireless Communications, 2019, 18(11): 5394–5409. doi: 10.1109/TWC.2019.2936025
|
[24] |
HU Xiaoyan, MASOUROS C, WONG K K, et al. Reconfigurable intelligent surface aided mobile edge computing: From optimization-based to location-only learning-based solutions[J]. IEEE Transactions on Communications, 2021, 69(6): 3709–3725. doi: 10.1109/TCOMM.2021.3066495
|