Analysis and optimization of cooperative spectrum sensing in cognitive radio networks with multiple antennas nodes

Abstract

The need for efficient utilization of spectrum has become a fundamental requirement in modern wireless networks. This is mainly due to spectrum scarcity and the ever-increasing demand for higher data rate applications and Internet services. Cognitive Radio (CR) has been proposed to solve the spectrum scarcity issue by opportunistically accessing the licensed bands when the primary users (PUs) are absent. Spectrum sensing is utilized in order to detect the presence or absence of the PU. Energy detection (ED) is one of the most common detection techniques due its low implementation complexity. However, ED performance is degraded in fading and/or shadowing environments; therefore, cooperative spectrum sensing (CSS) is utilized to enhance the performance of ED. In this research, the performance of a CSS scheme over imperfect feedback channels is studied, where each CR node is equipped with multiple antennas. First, the optimal fusion rule is derived to reduce the total error rate (TER) under Bayesian criterion. Further- more, Quasi-Newton method is used to obtain the optimal number of antennas for a given SNR and vice versa. Second, the CSS over generalized fading channels is investigated. In particular, the mixture gamma (MG) distribution is used to model the probability density function (PDF) of the signal-to-noise ratio (SNR) under the assumption of generalized fading channels. Subsequently, a generalized closed-form expression for the probability of energy detection is derived. Finally, the optimal number of nodes to mitigate the composite effect of fading and shadowing scenarios is derived in cooperative spectrum sensing. It is demonstrated that as the number of antennas of the CR nodes is increased, there will be a TER wall, which happens only if the feedback channels are erroneous.

Date of Award	2015
Original language	American English
Supervisor	Sami Muhaidat (Supervisor)