{"title":"A Graph-Based ABS-Assisted TBS Sleep Scheme","authors":"Huan Li;Daosen Zhai;Renli Zhu;Ruonan Zhang;Bin Li","doi":"10.1109/LWC.2024.3481467","DOIUrl":null,"url":null,"abstract":"The large-scale deployment of 5G base stations has led to a significant increase in energy consumption. To enable green communication, we propose a graph-based aerial base stations (ABS)-assisted terrestrial base station (TBS) deep sleep scheme. In this scheme, TBSs in cells during low-traffic-demand periods turn off most of their communication devices and go to the sleep mode with less power consumption. As a substitute, the offloaded traffic demands are taken over by the on-demand deployed ABSs. When the predicted traffic in the cells is low, an ABS can be deployed in advance to cover and serve multiple cells. Thus, we jointly optimize the cell clustering and ABS deployment. Specifically, we first propose a convex optimization based search algorithm to obtain all feasible cell clusters. To reduce the computational complexity, a randomized incremental based search algorithm is designed for the homogeneous networks. Then, the primal problem is recast as the maximum weight independent set problem in graph theory, and an efficient algorithm is adopted to solve it. Numerical simulation results demonstrate that our algorithm is superior to the comparison schemes and significantly degrades the computation time.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"13 12","pages":"3593-3597"},"PeriodicalIF":4.6000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10720117/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The large-scale deployment of 5G base stations has led to a significant increase in energy consumption. To enable green communication, we propose a graph-based aerial base stations (ABS)-assisted terrestrial base station (TBS) deep sleep scheme. In this scheme, TBSs in cells during low-traffic-demand periods turn off most of their communication devices and go to the sleep mode with less power consumption. As a substitute, the offloaded traffic demands are taken over by the on-demand deployed ABSs. When the predicted traffic in the cells is low, an ABS can be deployed in advance to cover and serve multiple cells. Thus, we jointly optimize the cell clustering and ABS deployment. Specifically, we first propose a convex optimization based search algorithm to obtain all feasible cell clusters. To reduce the computational complexity, a randomized incremental based search algorithm is designed for the homogeneous networks. Then, the primal problem is recast as the maximum weight independent set problem in graph theory, and an efficient algorithm is adopted to solve it. Numerical simulation results demonstrate that our algorithm is superior to the comparison schemes and significantly degrades the computation time.
期刊介绍:
IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.