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We consider the channel selection problem in a cognitive radio network with heterogenous channel availabilities at different nodes. We formulate the maximum channel selection (MCS) problem as a binary integer nonlinear optimization problem, with an objective of maximizing the total channel utilization for all secondary nodes. We first prove that MCS problem is NP-complete. Then we design a centralized greedy channel selection (GCS) algorithm. The GCS algorithm is polynomial in computational complexity, and achieves a close-to-optimal (higher than 95%) numerical performance. We further propose a distributed priority order channel selection algorithm, which has significantly less signaling overhead compared with the GCS algorithm. We study the performance of the distributed algorithm both theoretically and numerically.
Date of Conference: 6-10 Dec. 2010