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Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks

Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks

Mahsa Derakhshani, Tho Le-Ngoc
Copyright: © 2015 |Pages: 34
ISBN13: 9781466665712|ISBN10: 1466665718|EISBN13: 9781466665729
DOI: 10.4018/978-1-4666-6571-2.ch027
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MLA

Derakhshani, Mahsa, and Tho Le-Ngoc. "Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks." Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, edited by Naima Kaabouch and Wen-Chen Hu, IGI Global, 2015, pp. 711-744. https://doi.org/10.4018/978-1-4666-6571-2.ch027

APA

Derakhshani, M. & Le-Ngoc, T. (2015). Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks. In N. Kaabouch & W. Hu (Eds.), Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management (pp. 711-744). IGI Global. https://doi.org/10.4018/978-1-4666-6571-2.ch027

Chicago

Derakhshani, Mahsa, and Tho Le-Ngoc. "Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks." In Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, edited by Naima Kaabouch and Wen-Chen Hu, 711-744. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6571-2.ch027

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Abstract

This chapter presents a study on the interference caused by Secondary Users (SUs) due to miss-detection errors and its effects on the capacity-outage performance of the Primary User (PU) in a cognitive radio network assuming Rayleigh and Nakagami fading channels. The effect of beacon transmitter placement on aggregate interference distribution and capacity-outage performance is studied considering two scenarios of beacon transmitter placement: a beacon transmitter located at a PU transmitter or at a PU receiver. Based on the developed statistical models for the interference distribution, closed-form expressions for the capacity-outage probability of the PU are derived to examine the effects of various system parameters on the performance of the PU in the presence of interference from SUs. Furthermore, the model is extended to investigate the cooperative sensing effect on aggregate interference statistical model and capacity-outage performance considering OR (i.e., logical OR operation) and Maximum Likelihood (ML) cooperative detection techniques.

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