{"title":"多主网络认知无线网络中的协同感知调度","authors":"Ye Wang, Xiaodong Lin","doi":"10.1109/GLOCOM.2014.7036910","DOIUrl":null,"url":null,"abstract":"With the emergence of secondary spectrum markets, it is envisioned that multiple Primary Networks (PRNs) with non-overlapping spectrum pools will be incorporated into Cognitive Radio Networks (CRNs). As a result, CRNs will have a greatly enhanced choice of accessible spectrum resources available to them, which, in turn, brings a significant increase in the diversity of available PRNs; this can greatly increase reliability and stability in the system performance experienced by secondary users (SUs) on the network. However, due to the nature of dynamic network environments, it is hard to meet the requirements of sensing task when the sensing resources, such as the number of participating SUs and A/D sampling capability, are limited. In this paper, we address this issue by studying the problem of cooperative sensing scheduling of CRNs for a dynamic multi-PRN environment. By jointly considering the dynamics of spectrum usage, and the channel conditions of SUs, cooperative spectrum sensing scheduling is formulated as two optimization problems, from the perspectives of primary users (PUs) and SUs, respectively. To solve these problems, two straightforward scheduling schemes are discussed: Random Scheduling and SNR-based Greedy Scheduling. To further improve the sensing performance, a cross entropy (CE) method-based sensing scheduling scheme is proposed. At last, simulation results validate the effectiveness of the proposed CE-based sensing scheduling scheme.","PeriodicalId":6492,"journal":{"name":"2014 IEEE Global Communications Conference","volume":"16 1","pages":"822-827"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cooperative sensing scheduling in Cognitive Radio Networks with multiple Primary Networks\",\"authors\":\"Ye Wang, Xiaodong Lin\",\"doi\":\"10.1109/GLOCOM.2014.7036910\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the emergence of secondary spectrum markets, it is envisioned that multiple Primary Networks (PRNs) with non-overlapping spectrum pools will be incorporated into Cognitive Radio Networks (CRNs). As a result, CRNs will have a greatly enhanced choice of accessible spectrum resources available to them, which, in turn, brings a significant increase in the diversity of available PRNs; this can greatly increase reliability and stability in the system performance experienced by secondary users (SUs) on the network. However, due to the nature of dynamic network environments, it is hard to meet the requirements of sensing task when the sensing resources, such as the number of participating SUs and A/D sampling capability, are limited. In this paper, we address this issue by studying the problem of cooperative sensing scheduling of CRNs for a dynamic multi-PRN environment. By jointly considering the dynamics of spectrum usage, and the channel conditions of SUs, cooperative spectrum sensing scheduling is formulated as two optimization problems, from the perspectives of primary users (PUs) and SUs, respectively. To solve these problems, two straightforward scheduling schemes are discussed: Random Scheduling and SNR-based Greedy Scheduling. To further improve the sensing performance, a cross entropy (CE) method-based sensing scheduling scheme is proposed. At last, simulation results validate the effectiveness of the proposed CE-based sensing scheduling scheme.\",\"PeriodicalId\":6492,\"journal\":{\"name\":\"2014 IEEE Global Communications Conference\",\"volume\":\"16 1\",\"pages\":\"822-827\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Global Communications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOCOM.2014.7036910\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Global Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2014.7036910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cooperative sensing scheduling in Cognitive Radio Networks with multiple Primary Networks
With the emergence of secondary spectrum markets, it is envisioned that multiple Primary Networks (PRNs) with non-overlapping spectrum pools will be incorporated into Cognitive Radio Networks (CRNs). As a result, CRNs will have a greatly enhanced choice of accessible spectrum resources available to them, which, in turn, brings a significant increase in the diversity of available PRNs; this can greatly increase reliability and stability in the system performance experienced by secondary users (SUs) on the network. However, due to the nature of dynamic network environments, it is hard to meet the requirements of sensing task when the sensing resources, such as the number of participating SUs and A/D sampling capability, are limited. In this paper, we address this issue by studying the problem of cooperative sensing scheduling of CRNs for a dynamic multi-PRN environment. By jointly considering the dynamics of spectrum usage, and the channel conditions of SUs, cooperative spectrum sensing scheduling is formulated as two optimization problems, from the perspectives of primary users (PUs) and SUs, respectively. To solve these problems, two straightforward scheduling schemes are discussed: Random Scheduling and SNR-based Greedy Scheduling. To further improve the sensing performance, a cross entropy (CE) method-based sensing scheduling scheme is proposed. At last, simulation results validate the effectiveness of the proposed CE-based sensing scheduling scheme.