Departmental Papers (ESE)


Ergodic stochastic optimization (ESO) algorithms are proposed to solve resource allocation problems that involve a random state and where optimality criteria are expressed in terms of long term averages. A policy that observes the state and decides on a resource allocation is proposed and shown to almost surely satisfy problem constraints and optimality criteria. Salient features of ESO algorithms are that they do not require access to the state’s probability distribution, that they can handle nonconvex constraints in the resource allocation variables, and that convergence to optimal operating points holds almost surely. The proposed algorithm is applied to determine operating points of an orthogonal frequency division multiplexing broadcast channel that maximize a given rate utility.

Document Type

Journal Article

Date of this Version



Suggested Citation:
Ribeiro, A. (2010). "Ergodc Stochastic Optimization Algorithms for Wireless Communication and Networking." IEEE Transactions on Signal Processing Vol. 58(12). pp. 6369 - 6386

©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.


Adaptive signal processing, cross-layer design, gradient methods, OFDM, optimization, wireless communications, wireless networks



Date Posted: 22 December 2010

This document has been peer reviewed.