Chen Chen, Yan Jiang, Jiliang Zhang, Xiaoli Chu, J. Zhang
{"title":"Parameter Optimization for Energy Efficient Indoor Massive MIMO Small Cell Networks","authors":"Chen Chen, Yan Jiang, Jiliang Zhang, Xiaoli Chu, J. Zhang","doi":"10.1109/VTC2020-Spring48590.2020.9129437","DOIUrl":null,"url":null,"abstract":"To better characterize indoor small cell networks (SCN), we consider the blockages caused by interior walls and employ the bounded path loss model to derive the expression for energy efficiency (EE) of a downlink massive multiple-input multiple-output (MIMO) SCN. Our EE expression demonstrates that a higher penetration loss of interior walls leads to a higher EE. For the purpose of maximizing EE, we propose a novel genetic algorithm (GA) based scheme to jointly optimize the number of antennas per base station (BS), the number of users per cell, and the transmission power per antenna. Numerical results show that our proposed scheme can achieve almost the identical EE as the optimal greedy search algorithm, while significantly reducing the computational time.","PeriodicalId":348099,"journal":{"name":"2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VTC2020-Spring48590.2020.9129437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To better characterize indoor small cell networks (SCN), we consider the blockages caused by interior walls and employ the bounded path loss model to derive the expression for energy efficiency (EE) of a downlink massive multiple-input multiple-output (MIMO) SCN. Our EE expression demonstrates that a higher penetration loss of interior walls leads to a higher EE. For the purpose of maximizing EE, we propose a novel genetic algorithm (GA) based scheme to jointly optimize the number of antennas per base station (BS), the number of users per cell, and the transmission power per antenna. Numerical results show that our proposed scheme can achieve almost the identical EE as the optimal greedy search algorithm, while significantly reducing the computational time.