Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel. Issue 16 (1st October 2019)

• Record Type: Journal Article
• Authors: Nallagonda, Srinivas; Kumar, Godugu Kiran; Nallagonda, Ashok Kumar
• Is Part Of: IET communications. Volume 13:Issue 16(2019)
• Page Start: 2558
• Page End: 2566
• Publication Date: 2019-10-01
• Subjects: radio networks -- radio spectrum management -- cooperative communication -- sensor fusion -- fading channels -- cognitive radio; HDCSs -- optimal sensing threshold -- comprehensive performance analysis -- cognitive radio -- radio spectrum -- licensed primary user -- PU -- CR network -- sensing information -- fusion centre -- channel parameters -- hard‐decision combining schemes -- CRU -- sensing data fusion -- SDCSs -- data‐fusion aided cooperative cognitive radio network -- η−μ fading channel -- analytical performance -- efficient soft‐data combining schemes -- mathematical expressions -- receiver operating characteristics -- average error rate -- optimal detection threshold -- computer‐based simulations; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.0298
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this paper, analytical performance of efficient soft‐data combining schemes (SDCSs) for cognitive radio network (CRN) is investigated. The performance is investigated in the presence of noise and generalized η − μ fading. In more detail, each CRU senses the PU and reports its sensing information to the fusion center (FC). At FC, different SDCSs, which differ in process of fusing the sensing data, are implemented to make the global decision on the status of a PU. In the present work, first the novel mathematical expressions, subject to SDCS and η − μ fading are derived. Next, the performance is evaluated through receiver operating characteristics (ROC) and average error rate (AER), considering the significant impact of network and channel parameters. The performance of hard‐decision combining schemes (HDCSs) is also studied for comparison purpose. The analysis presented in this paper eliminates the need of analysis of SDCSs over individual fading channels. An optimal sensing threshold and an optimal number of CRUs where AER attains its minimum value are also determined for all HDCSs and SDCSs. Finally, the derived expressions are validated by computer based simulations for several parameter values of the network.