Optimal Distributed Power Control and Routing in Wireless Networks

We present a unified analytical framework within which power control and routing for wireless networks can be optimized on a node-by-node basis. We consider a multicommodity flow model for an interference-limited wireless network in which power control and routing variables are chosen to minimize convex link costs. Distributed scaled gradient projection algorithms are developed to iteratively adjust power control and routing schemes at individual nodes. We specify appropriate scaling matrices with which the algorithms quickly converge to the global optimum from any initial point. These scaling matrices can be computed locally at each node with limited control message overhead

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