We consider a wireless OFDMA cellular network and address the problem of jointly allocating power to frequencies (subbands) and assigning users to cells, for a variety of elastic and inelastic services. The goal is to maximize the sum of the users’ throughput utility functions subject to various constraints, such as minimum throughput requirements. The problem naturally ¿ts into a Network Utility Maximization (NUM) framework with a mixture of concave (e.g., data rates) and nonconcave (e.g., voice/video streaming) utilities. The hardness of this nonconvex, mixed integer program prohibits the use of standard convex optimization algorithms, or ef¿cient combinatorial approximation techniques. We devise a randomized algorithm for the said NUM problem, whose proof of asymptotic optimality is derived from the classical framework of interacting particle systems, via a judiciously selected neighborhood structure. The proposed algorithm is highly distributed, asynchronous, requires limited computational effort per node/iteration, and yields provable convergence in the limit. Several numerical experiments are presented to illustrate the convergence speed and performance of the proposed method.
|Title of host publication||49th Annual Allerton Conference on Communication, Control, and Computing (Monticello IL, USA, September 28-30, 2011)|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 2011|