Random access in wireless Ad hoc networks for throughput maximization

We consider the distributed random access algorithms for wireless ad hoc networks in which each node needs to tune its persistent probability so as to optimize its own the total throughput. First, we present an asynchronous algorithm for updating persistent probabilities and prices to avoid collision using local coordination. By casting this algorithm as a best response in a cooperative game, we characterize its convergence analytically. We further model that each node attempts to maximize a selfish local payoff function. We characterize the Nash equilibrium (NE) of the non-cooperative game and prove the convergence of a best response algorithm to the unique NE. Then we study the energy efficient throughput maximization problem when the wireless nodes are constrained by their battery power. Despite the inherent difficulty of non-separability of the constraint set, we propose a distributed primal-based algorithm. Its convergence is studied numerically.