An Estimation Algorithm of Channel State Transition Probabilities for Cognitive Radio Systems

Abstract

In this paper, an estimation algorithm of channel state transition probabilities in Markov channel model for cognitive radio systems is proposed. The framework of POMDP is adopted to solve the problem of channel selection. Maximum likelihood method is used to estimate the channel state transition probabilities, which is crucial to POMDP. Central Limit Theorem is introduced to get the relationship between the precision, sample times and the channel state transition probability values. The simulation results show the reliability of the estimation results.