Distributed Opportunistic Spectrum Access With Unknown Population

Provided by: Institute of Electrical & Electronic Engineers
Topic: Mobility
Format: PDF
The authors consider a cognitive radio network where M secondary users compete with each other to access one of the N available channels. Channel availability statistics are assumed to evolve as i.i.d. Bernoulli random processes with means unknown to the secondary users. In addition, the number of secondary users M is unknown to each user. The main objective here is to design a distributed online learning and access policy which maximizes the total throughput of the secondary users. It has previously been shown that this problem can elegantly be modeled as a Decentralized Multi-Armed Bandit (DMAB) problem when M is known.

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