Throughput analysis of cooperative cognitive radio network over generalized κ–μ and η–μ fading channels

• Published in: Wireless networks Vol. 25; no. 8; pp. 4625 - 4638
• Main Authors: Balam, Suresh Kumar, Siddaiah, P., Nallagonda, Srinivas
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2019; Springer Nature B.V
• Subjects: Channels; Codes; Cognitive radio; Communications Engineering; Computer Communication Networks; Computer simulation; Decision analysis; Electrical Engineering; Engineering; Error analysis; Error detection; Fading; IT in Business; Monte Carlo simulation; Networks; Parameters; Radio networks; Wireless networks; Generalized fading model; Throughput; Cognitive radio; Cooperative sensing; Total error rate
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-018-1758-4

In this paper, we propose a cooperative cognitive radio network (CCRN) based on energy detection and hard-decision fusion. The performance characteristics are investigated analytically in the presence of noise plus generalized fading channels. In particular, scenarios with κ – μ and η – μ fading channels affecting the sensing channels are considered. More precisely, Each cognitive radio user (CRU) relies on an energy detector (ED). The signal from the primary user (PU), received by a CRU, is fed to the ED, and the energy of signal is used to make a local decision. At the fusion center (FC), the decisions received at the FC are fused, using hard-decision fusion, to obtain a final decision on the status of the PU. The performance of CCRN, through total error rate and throughput is evaluated considering the impact of relevant network parameters. Towards that, first we derive the novel mathematical expressions for probability of detection, subject to generalized fading. Also, Monte Carlo simulation is performed to validate the derived expressions. Next, the analytical frame works based on derived expression for evaluating total error rate and throughput performances for any network and channel conditions are developed. Further, the impact of an erroneous sensing (S) and reporting (R) channels on overall performance of CCRN is also investigated. Finally, the impact of the generalized fading parameters, the signal-to-noise ratio, the time-bandwidth product, the number of CRUs, the detection threshold, and the channel error probability on the total error rate and throughput performances is investigated.