A Novel Approach in Hidden Markov Model for Spectrum Sensing On Cognitive Radio

Abstract – Cognitive radio is an emerging technology for sensing the spectrum in wireless communication networks. It helps the secondary users (unlicensed users) in detecting the under-utilized spectrum of primary users (licensed users) and utilizing the spectrum without causing any interference to the primary users. Most of the techniques proposed in the literature are based on the current state of the primary users. So transmission pattern of the primary users is based on the current measurement taken at the cognitive radio. Thus sensing performance can be improved by considering the measurement history into the sensing decision. Moreover, utilising all the available data to predict the state of the primary user will allow the secondary user to better plan for efficient utilization of spectrum. In this project, spectrum sensing based on hidden Markov model is discussed. Using this model, subcarrier allocation can be determined through which prediction accuracy can be increased. In future, the same work can be extended using other spectrum sensing techniques and the results can also be optimized.

Keywords- Cognitive Radio, Hidden Markov Model (HMM), Markov Chain,Prediction Accuracy,Spectrum Sensing, Sub- band utilization.