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Efficient design of wireless networks requires implementation of cross-layer algorithms that exploit channel state information. Capitalizing on convex optimization and stochastic approximation tools, this paper develops a stochastic algorithm that allocates resources at network, link, and physical layers so that a sum-utility of the average end-to-end rates is maximized. Focus is placed on networks where interference is strong and nodes transmit orthogonally over a set of parallel channels. Convergence of the developed stochastic schemes is characterized, and the average queue delays are obtained in closed form.
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