Cluster‐based distributed cooperative spectrum sensing over Nakagami fading using diversity reception. Issue 3 (1st May 2019)

• Record Type: Journal Article
• Authors: Sharma, Girraj; Sharma, Ritu
• Is Part Of: IET networks. Volume 8:Issue 3(2019)
• Page Start: 211
• Page End: 217
• Publication Date: 2019-05-01
• Subjects: Nakagami channels -- radio spectrum management -- probability -- signal detection -- cognitive radio -- cooperative communication; centralised CSS -- wireless networking -- detection probability -- false alarm probability -- Nakagami fading channel -- cluster‐based distributed cooperative spectrum sensing -- cognitive radio -- OR–OR fusion rule; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2018.5002
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : Cooperative spectrum sensing (CSS) can solve the problem of hidden terminal in cognitive radio (CR). CSS can be employed in two ways distributed and centralised. In wireless networking, clustering can provide network scalability, better resource allocation, and energy efficiency. Here, cluster‐based distributed CSS is investigated over Nakagami channel. In the proposed scheme, four fusion policies OR–OR, OR–AND, AND–OR, and AND–AND are investigated. An analytical framework has been presented to evaluate different parameters related to spectrum sensing, i.e. detection probability, false alarm probability, and missed detection probability for Nakagami fading channel. On the basis of the developed framework, the performance of cluster‐based distributed CSS has been compared with the centralised CSS. Results show that OR–OR fusion rule of the cluster‐based distributed CSS outperforms other fusion rules and centralised CSS. To achieve 80% probability of detection, SNR required is <10 dB in OR–OR fusion, whereas it is >10 dB for other fusion schemes. Further performance improvement is achieved by using square law selection and maximum ratio combining diversity schemes.