Markovian-based framework for cooperative channel selection in cognitive radio networks

The authors propose Markovian-based spectrum sensing policies in a cognitive radio system that leverages past sensing outcomes of several cooperating secondary users (SUs) to decide which channel (of primary users - PUs) should be sensed by each SU at a given time. These policies are based on a new finite-state channel model that captures the fading condition as well as the occupancy state for each primary channel. The multiuser extension of this model is useful when multiple spatially distributed SUs share their sensing outcomes. The proposed schemes allow the asynchronous sensing outcomes obtained by the SUs over different slots to be fused together and converted into a posteriori probabilities for the current states of the primary channels. As the detection threshold in a spectrum detector balances the trade-off between the false-alarm and miss probabilities for detecting primary signals in a single primary channel, a design parameter is introduced to allow the system designer to devise policies with different levels of aggressiveness. The authors evaluate the optimality and complexity of the proposed sensing policies and show that our schemes significantly increase secondary use of the spectrum and/or reduce interference with PUs compared to a random selection policy or a cooperative sensing policy based on a two-state channel model.