Abstract
Dynamic allocation of power, rate and channel access is a critical task in wireless networks. Capitalizing on convex optimization and stochastic approximation tools, this paper develops a stochastic resource allocation algorithm that minimizes
average transmit power under individual average rate constraints. Focus is placed on networks where users transmit orthogonally over a set of parallel channels and transmissions are adapted based on quantized channel state information (CSI) allowing even channel statistics to be unknown.
Convergence of the developed stochastic scheme is characterized and the average queue delays are obtained in closed form.
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