Function approximation based energy detection in cognitive radio using radial basis function network. Issue 3 (3rd July 2017)

• Record Type: Journal Article
• Authors: Dey, Barnali; Hossain, A.; Bhattacharjee, A.; Dey, Rajeeb; Bera, R.
• Is Part Of: Intelligent automation & soft computing. Volume 23:Issue 3(2017)
• Page Start: 393
• Page End: 403
• Publication Date: 2017-07-03
• Subjects: Words -- Cognitive-radio (CR) -- Spectrum sensing -- Energy-detection -- Function approximation -- Radial basis function (RBF) network -- Neural network; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2016.1217632
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: In this paper an attempt has been made to evolve a computationally intelligent energy detection method for spectrum sensing in Cognitive Radio (CR). The proposed method utilizes the function approximation capability of radial basis function (RBF) network to learn the threshold function for a pre-determined range of probability of false alarm and number of samples. The receiver operating characteristic (ROC) results obtained by the proposed method have been compared with the conventional energy detection scheme. It is validated from the results that, the proposed method provides enhanced probability of detection in some cases compared to the conventional one due to its inherent shortcoming in terms of computational intelligence.