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We propose a distributed asynchronous spectrum allocation algorithm that achieves performance close to that of a centralized optimal algorithm. In our network model, nodes are grouped into a number of clusters. Each cluster chooses its transmission frequency band based on its knowledge of the interference that it experiences. The convergence of the proposed distributed algorithm to a sub-optimal spectrum assignment strategy is proved. Moreover, asymptotic bounds on the performance of the algorithm are derived for one dimensional spatial distribution of the clusters in the network. These analytic results and additional simulation studies verify performance close to that of an optimum centralized frequency allocation algorithm. It is demonstrated that the algorithm achieves about 90% of the Shannon capacities corresponding to the optimum centralized frequency band assignments.