{"title":"Fair resource allocation in downlink OFDM-based cognitive radio networks","authors":"Xu Wang, S. Ekin, K. Qaraqe, E. Serpedin","doi":"10.1109/ISSCS.2017.8034871","DOIUrl":null,"url":null,"abstract":"This work investigates the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio networks. The objective of this work is to develop a fair RA-algorithm that maximizes the capacity of secondary users (SUs) and in the same time limits the interference caused to the primary users. The fairness condition is formulated as a minimal data condition at SUs. A relaxed version of the RA-problem is first reviewed without adopting the fairness and then a heuristic algorithm is proposed based on the results obtained for the relaxed problem. Computer simulation results illustrate that the proposed heuristic algorithm can achieve near-optimal performance.","PeriodicalId":338255,"journal":{"name":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2017.8034871","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
This work investigates the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio networks. The objective of this work is to develop a fair RA-algorithm that maximizes the capacity of secondary users (SUs) and in the same time limits the interference caused to the primary users. The fairness condition is formulated as a minimal data condition at SUs. A relaxed version of the RA-problem is first reviewed without adopting the fairness and then a heuristic algorithm is proposed based on the results obtained for the relaxed problem. Computer simulation results illustrate that the proposed heuristic algorithm can achieve near-optimal performance.