On Myopic Sensing for Multi-Channel Opportunistic Access

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 objective is to design a sensing policy for channel selection to maximize the average reward. 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 counting 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 extensive simulations. The performance of the myopic sensing policy is analyzed, which, based on the optimality of myopic sensing, characterizes the maximum t...

• Type: Journal
• Year: 2007
• Where: CORR
• Authors: Qing Zhao, Bhaskar Krishnamachari, Keqin Liu
• Keywords: Channel Selection, CORR 2007, Education, Multi-channel Opportunistic Communication, Myopic Sensing Policy