Thant Zin Oo, Nguyen H. Tran, Tuan LeAnh, S. M. Ahsan Kazmi, T. Ho, C. Hong
{"title":"Traffic offloading under outage QoS constraint in heterogeneous cellular networks","authors":"Thant Zin Oo, Nguyen H. Tran, Tuan LeAnh, S. M. Ahsan Kazmi, T. Ho, C. Hong","doi":"10.1109/APNOMS.2015.7275382","DOIUrl":null,"url":null,"abstract":"Heterogeneous cellular networks offload the mobile data traffic to small cell base stations to reduce the workload on the macro base stations. Our objective is to maximize the sum rate of the down-links for the whole network under outage QoS constraint. To achieve the objective, we have to jointly solve the user association problem and resource allocation problem. We formulate the two problems into a joint optimization problem and convert it into an equivalent game theoretic formulation. We employ payoff based log linear learning and propose an algorithm that converges to one of the existing Nash equilibrium. We then provide extensive simulation results to verify the performance of our proposed algorithm.","PeriodicalId":269263,"journal":{"name":"2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APNOMS.2015.7275382","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
Heterogeneous cellular networks offload the mobile data traffic to small cell base stations to reduce the workload on the macro base stations. Our objective is to maximize the sum rate of the down-links for the whole network under outage QoS constraint. To achieve the objective, we have to jointly solve the user association problem and resource allocation problem. We formulate the two problems into a joint optimization problem and convert it into an equivalent game theoretic formulation. We employ payoff based log linear learning and propose an algorithm that converges to one of the existing Nash equilibrium. We then provide extensive simulation results to verify the performance of our proposed algorithm.