Abstract
In this paper, we propose a channel allocation algorithm for heterogeneous multi-cell cognitive radio 5G networks. The proposed algorithm considers channel-availability and channel-demand heterogeneity across CR cells. We use the theory of continuous-time Markov chains to develop mathematical expressions for channel availability and channel demand. Both expressions are incorporated in a binary integer program to find the optimal channel allocation. Further, we equip the proposed channel allocation algorithm with a novel interference domain identification scheme to detect interference range overlaps between cognitive radio cells. This scheme is essential for channel allocation, as it plays an important role in avoiding inter-cell interference. Our simulation results show significant performance gains compared to existing algorithms overlooking channel-availability. Furthermore, we use the theory of Dantzig-Wolfe decomposition to develop a framework for transforming centralized channel allocation algorithms into distributed ones. Through simulation experiments, we demonstrate the efficacy of the proposed framework.
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