{"title":"Uplink distributed power and receiver optimization across multiple cells","authors":"Changxin Shi, M. Honig, S. Nagaraj, P. Fleming","doi":"10.1109/WCNC.2012.6214039","DOIUrl":null,"url":null,"abstract":"Interference mitigation approaches in the presence of multiple receive antennas in the uplink of a multi-cell wireless communications system are studied in this paper. A formulation based on interference pricing is proposed, where it is shown that a single price per base-station can be computed and exchanged, in order to set the mobile transmit powers per cell. The work is premised on a decentralized network architecture where schedulers make decisions on users connected to their cell, and there is a low-rate inter-cell communication link to enable distributed interference mitigation. The proposed utility maximization approach provides a general framework for multi-user multiple-input multiple-output (MIMO) systems on the uplink and accommodates both optimal (MMSE) and sub-optimal (MRC) multi-antenna receivers.","PeriodicalId":329194,"journal":{"name":"2012 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2012.6214039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Interference mitigation approaches in the presence of multiple receive antennas in the uplink of a multi-cell wireless communications system are studied in this paper. A formulation based on interference pricing is proposed, where it is shown that a single price per base-station can be computed and exchanged, in order to set the mobile transmit powers per cell. The work is premised on a decentralized network architecture where schedulers make decisions on users connected to their cell, and there is a low-rate inter-cell communication link to enable distributed interference mitigation. The proposed utility maximization approach provides a general framework for multi-user multiple-input multiple-output (MIMO) systems on the uplink and accommodates both optimal (MMSE) and sub-optimal (MRC) multi-antenna receivers.