Estimation of Channel State Transition Probabilities Based on Markov Chains in Cognitive Radio

Provided by: Journal of Communications
Topic: Mobility
Format: PDF
Prediction of spectrum sensing and access is one of the keys in Cognitive Radio (CR). It is necessary to know the channel state transition probabilities to predict the spectrum. By the use of the model of Partially Observable Markov Decision Process (POMDP), this paper addressed the spectrum sensing and access in cognitive radio and proposed an estimation algorithm of channel state transition probabilities. In this algorithm, the historical statistics information of channel is used to estimate the channel state transition probabilities, and the Least Square (LS) criterion is used to minimize the fitting error.

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