Joint coded caching and BS sleeping strategy to reduce energy consumption in 6G edge networks

被引:6
作者
Yang, Liming [1 ,2 ]
Hu, Honglin [1 ]
Zhou, Ting [3 ,4 ]
Xu, Tianheng [1 ,4 ]
机构
[1] Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai 201210, Peoples R China
[2] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 100049, Peoples R China
[3] Shanghai Univ, Sch Microelect, Shanghai, Peoples R China
[4] Shanghai Frontier Innovat Res Inst, Shanghai, Peoples R China
关键词
Coded caching; Base station sleeping; Energy consumption; Mixed integer nonlinear programming; Discrete particle swarm optimization; POWER OPTIMIZATION; WIRELESS NETWORKS; ALLOCATION; SPECTRUM; MIMO;
D O I
10.1016/j.iot.2023.100915
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the coming sixth-generation mobile communication era, the intensive deployment of Internet of Things (IoT) devices and cellular networks is an irresistible trend, leading to system energy consumption and network traffic increasing sharply. Fortunately, edge caching as a promising technology to reduce system energy consumption and transmission latency is attracting wide attention. Although simply deploying cache in edge network and merely shutting down the idle base stations (BSs) during the idle periods can save certain energy to a certain extent, in this case, the contents with important mission cached in idle BSs cannot be accessed by users that will affect users' experience. In this paper, we employ coded caching encoded by maximum distance separable (MDS) codes at the network edge, and we propose a joint coded caching and BS sleeping strategy, which utilizes the reconstruction feature of MDS codes to alleviate the impact of BS sleeping. Furthermore, the problem of minimizing energy consumption is studied, and we also design a discrete particle swarm optimization (DPSO) algorithm that is suitable to solve this mixed integer nonlinear programming problem. Simulation results reveal that energy consumption of the joint coded caching and BS sleeping strategy can be significantly decreased over 15.2% when compared with the current state-of-art strategy. Meanwhile, our proposed strategy can also improve the cache hit rate up to a maximum 11.1% compared with the existing strategies.
引用
收藏
页数:13
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