We develop a distributed
throughput-optimal power allocation algorithm in wireless networks. The study
of this problem has been limited due to the nonconvexity of the underlying
optimization problems that prohibits an efficient solution even in a
centralized setting. By generalizing the randomization framework originally
proposed for input queued switches to SINR rate-based interference model, we
characterize the throughput-optimality conditions that enable efficient and
distributed implementation. Using gossiping algorithm, we develop a distributed
power allocation algorithm that satisfies the optimality conditions, thereby
achieving (nearly) 100 percent throughput. We illustrate the performance of our
power allocation solution through numerical simulation.
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