Energy-Efficient Task Offloading in RIS-Aided HetNets With Wireless Backhaul
Energy-Efficient Task Offloading in RIS-Aided HetNets With Wireless Backhaul
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DOI：
10.1109/lcomm.2023.3299380
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发表时间：
2023-09
期刊：
影响因子：
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通讯作者：
Li Zhang;Jinping Niu;Yiyao Wang;Gaojie Chen;Tao Gu;Yanyan Li
中科院分区：
文献类型：
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作者：
Li Zhang;Jinping Niu;Yiyao Wang;Gaojie Chen;Tao Gu;Yanyan Li
这封信通过无线回程利用了异质网络（HETNETS）中可重构的智能表面（RIS），以提高任务计算能源效率。为了最大程度地减少所有用户的整体能耗，我们通过共同优化用户和小型单元基站的发射功率，用户和基站的计算能力，用户的任务卸载率以及RIS的无源光束成形矩阵，将问题作为组合优化问题。这个问题是NP坚硬的，难以直接解决。我们将问题分别分解为用户和基站的两个亚问题，分别考虑到无线回程容量。迭代解决两个子问题以找到最终解决方案。仿真结果表明，与基准相比，所提出的方案可以大大减少能源消耗。
This letter exploits reconfigurable intelligent surface (RIS) in the heterogeneous networks (HetNets) with wireless backhaul to improve the task computing energy efficiency. To minimize the overall energy consumption of all users, we formulate the problem as a combinatorial optimization problem by jointly optimizing the transmit power of users and small cell base stations, computational capacity of users and base stations, task offloading rate of users, and passive beamforming matrix at RIS. The problem is NP-hard and difficult to solve directly. We decompose the problem into two sub-problems of energy consumption optimization at users and base stations, respectively, taking into account of wireless backhaul capacity. The two sub-problems are solved iteratively to find the final solution. Simulation results demonstrate that the proposed scheme can greatly reduce the energy consumption compared with the baselines.