Performance Evaluation of Computationally Efficient Energy Detection Based Spectrum Sensing for Cognitive Radio Networks

The rapid growth of bandwidth demanding wireless technologies has led to the problem of spectrum scarcity. However, studies show that licensed spectrum is underutilized. Cognitive radio technology promises a solution to the problem by allowing unlicensed users, access to the licensed bands opportunistically. A prime component of the cognitive radio technology is spectrum sensing. Many spectrum sensing techniques have been developed to sense the presence or not of a licensed user. This paper evaluates the performance of the energy detection based spectrum sensing technique in noisy, fading, jamming, interference environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. The analytical results were varied by numerical computations using Monte Carlo method with MATLAB. The performance of the computationally efficient energy detection (CE-ED) techniques were evaluated by use of Receiver Operating Characteristics (ROC) curves over additive white Gaussian noise (AWGN) and fading (Rayleigh & Nakagami-m) channels. Results show that for single user detection, the energy detection technique performs better in AWGN channel than in the fading channel models. The performance of cooperative detection is better than single user detection in fading environments.