Fengming Cao, Zhenzhe Zhong, Zhong Fan, M. Sooriyabandara, S. Armour, A. Ganesh
{"title":"User association for load balancing with uneven user distribution in IEEE 802.11ax networks","authors":"Fengming Cao, Zhenzhe Zhong, Zhong Fan, M. Sooriyabandara, S. Armour, A. Ganesh","doi":"10.1109/CCNC.2016.7444828","DOIUrl":null,"url":null,"abstract":"This paper proposes a dynamic user association method to address the load balancing problem in dense IEEE 802.11ax networks with uneven user distribution, where a user determines which AP to connect to taking into consideration of multiple factors such as RSS, potential relative capacity, achievable data rate and location of users. The method is user-centric and does not incur much signaling overhead, while performance optimization can be achieved without inter-AP coordination. Simulation results have been presented to show that the proposed solution can improve load balancing and have higher average throughput for 10% worst users as well as maintain the maximal total system throughput. Our evaluation also suggests that the location-awareness of users considered in the proposed solution plays an important role to improve the performance.","PeriodicalId":399247,"journal":{"name":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2016.7444828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper proposes a dynamic user association method to address the load balancing problem in dense IEEE 802.11ax networks with uneven user distribution, where a user determines which AP to connect to taking into consideration of multiple factors such as RSS, potential relative capacity, achievable data rate and location of users. The method is user-centric and does not incur much signaling overhead, while performance optimization can be achieved without inter-AP coordination. Simulation results have been presented to show that the proposed solution can improve load balancing and have higher average throughput for 10% worst users as well as maintain the maximal total system throughput. Our evaluation also suggests that the location-awareness of users considered in the proposed solution plays an important role to improve the performance.