Graph-theoretic cooperative spectrum allocation in distributed cognitive networks using bipartite matching

In this paper, a novel method using bipartite graph matching is proposed to allocate the spectrum in cognitive networks, where users cooperatively optimize spectrum allocation to get the maximal system utility while avoiding interference with its neighbors. A feasible method for distributed cognitive networks is presented; experimental results show that proposed algorithm dramatically maximizes spectrum utilization together with reducing allocation conflictions among users, which minimize the number of starved users during the allocation.