Steve Blandino, C. Desset, A. Chiumento, A. Bourdoux, L. Perre, S. Pollin
{"title":"Link adaptation in massive MIMO: Throughput-fairness trade-off","authors":"Steve Blandino, C. Desset, A. Chiumento, A. Bourdoux, L. Perre, S. Pollin","doi":"10.1109/SCVT.2017.8240314","DOIUrl":null,"url":null,"abstract":"The fifth-generation cellular networks aim to provide uniform and very high throughput. Massive MIMO is widely seen as the most promising 5G radio technology as it promises very high throughput to many users while also guaranteeing fairness, thanks to the channel hardening effect limiting the small-scale fading. A key question though is to what extent this achieved throughput is homogeneous among users, and what degrees of freedom exist to improve fairness. A promising option to provide uniform throughput using Massive MIMO would be a proper power control, based on long-term channel statistics. This paper studies the trade-off between throughput and fairness and it compares different power-allocation schemes. Assuming users affected by log-normal large-scale fading, simulations show that the trade-off is critical. as user-dependent differences caused by large-scale fading are causing unfairness in the system and fairness is achieved at the price of throughput reduction. In a limited large-scale fading scenario, throughput or fairness optimization is possible without incurring huge losses on the other dimension. For heavy large-scale fading scenarios the cost of enforcing fairness is very large: more than 50% of throughput reduction is observed. Despite the critical trade-off, Massive MIMO is shown to be less sensitive to throughput losses when enforcing fairness, compared with traditional communication systems.","PeriodicalId":226008,"journal":{"name":"2017 IEEE Symposium on Communications and Vehicular Technology (SCVT)","volume":"426 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Symposium on Communications and Vehicular Technology (SCVT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCVT.2017.8240314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The fifth-generation cellular networks aim to provide uniform and very high throughput. Massive MIMO is widely seen as the most promising 5G radio technology as it promises very high throughput to many users while also guaranteeing fairness, thanks to the channel hardening effect limiting the small-scale fading. A key question though is to what extent this achieved throughput is homogeneous among users, and what degrees of freedom exist to improve fairness. A promising option to provide uniform throughput using Massive MIMO would be a proper power control, based on long-term channel statistics. This paper studies the trade-off between throughput and fairness and it compares different power-allocation schemes. Assuming users affected by log-normal large-scale fading, simulations show that the trade-off is critical. as user-dependent differences caused by large-scale fading are causing unfairness in the system and fairness is achieved at the price of throughput reduction. In a limited large-scale fading scenario, throughput or fairness optimization is possible without incurring huge losses on the other dimension. For heavy large-scale fading scenarios the cost of enforcing fairness is very large: more than 50% of throughput reduction is observed. Despite the critical trade-off, Massive MIMO is shown to be less sensitive to throughput losses when enforcing fairness, compared with traditional communication systems.