Huidong Liu, Jin Chen, Guoru Ding, T. Tsiftsis, C. Rowell
{"title":"认知无线电网络中能量收集的天线波束形成","authors":"Huidong Liu, Jin Chen, Guoru Ding, T. Tsiftsis, C. Rowell","doi":"10.1109/IEEE-IWS.2016.7585472","DOIUrl":null,"url":null,"abstract":"In this paper, a cooperative cognitive radio network (CRN) with energy harvesting capabilities of its secondary users is considered. Specifically, cooperative spectrum sensing and multi-antenna beamforming are employed to improve the sensing performance and the energy transfer efficiency, respectively. In our approach, a homogeneous CRN scenario is studied where the optimal sensing probability of each second user (SU) is obtained to maximize the control center (CC) throughput while satisfying the energy causality and primary user (PU) collision constraints. An iterative algorithm is proposed to obtain the optimal charging time. Numerical results depict that in an energy constrained scenario, cooperative spectrum sensing with beamforming performs much better than cooperative spectrum sensing without beamforming in terms of increased system throughput.","PeriodicalId":185971,"journal":{"name":"2016 IEEE MTT-S International Wireless Symposium (IWS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Antenna beamforming for energy harvesting in cognitive radio networks\",\"authors\":\"Huidong Liu, Jin Chen, Guoru Ding, T. Tsiftsis, C. Rowell\",\"doi\":\"10.1109/IEEE-IWS.2016.7585472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a cooperative cognitive radio network (CRN) with energy harvesting capabilities of its secondary users is considered. Specifically, cooperative spectrum sensing and multi-antenna beamforming are employed to improve the sensing performance and the energy transfer efficiency, respectively. In our approach, a homogeneous CRN scenario is studied where the optimal sensing probability of each second user (SU) is obtained to maximize the control center (CC) throughput while satisfying the energy causality and primary user (PU) collision constraints. An iterative algorithm is proposed to obtain the optimal charging time. Numerical results depict that in an energy constrained scenario, cooperative spectrum sensing with beamforming performs much better than cooperative spectrum sensing without beamforming in terms of increased system throughput.\",\"PeriodicalId\":185971,\"journal\":{\"name\":\"2016 IEEE MTT-S International Wireless Symposium (IWS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE MTT-S International Wireless Symposium (IWS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEE-IWS.2016.7585472\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE MTT-S International Wireless Symposium (IWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEE-IWS.2016.7585472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Antenna beamforming for energy harvesting in cognitive radio networks
In this paper, a cooperative cognitive radio network (CRN) with energy harvesting capabilities of its secondary users is considered. Specifically, cooperative spectrum sensing and multi-antenna beamforming are employed to improve the sensing performance and the energy transfer efficiency, respectively. In our approach, a homogeneous CRN scenario is studied where the optimal sensing probability of each second user (SU) is obtained to maximize the control center (CC) throughput while satisfying the energy causality and primary user (PU) collision constraints. An iterative algorithm is proposed to obtain the optimal charging time. Numerical results depict that in an energy constrained scenario, cooperative spectrum sensing with beamforming performs much better than cooperative spectrum sensing without beamforming in terms of increased system throughput.