On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance

We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The problem is to design a sensing policy for channel selection to maximize the average reward, which can be formulated as a multi-arm restless bandit process. In this paper, we study the structure, optimality, and performance of the myopic sensing policy. We show that the myopic sensing policy has a simple robust structure that reduces channel selection to a round-robin procedure and obviates the need for knowing the channel transition probabilities. The optimality of this simple policy is established for the two-channel case and conjectured for the general case based on numerical results. The performance of the myopic sensing policy is analyzed, which, based on ...

• Type: Journal
• Year: 2008
• Where: TWC
• Authors: Qing Zhao, Bhaskar Krishnamachari, Keqin Liu
• Keywords: Channel Selection, Multi-channel Opportunistic Communication, Myopic Sensing Policy, TWC 2008