Dynamic bandwidth allocation in wireless networks using a Shahshahani gradient based extremum seeking control

In this paper we propose an extremum seeking approach based on evolutionary game theory, to solve the dynamic bandwidth allocation problem in wireless networks. The algorithm proposed aims to maximize a general utility function associated to the network, defined as the sum of the individual utilities of the agents (users) that belong to the network. Due to the complex time-varying nature of the available bandwidth, the quality of the links across the population of agents, and the parameters and structure of the utilities of the agents, a non-model based control is required. In this context, the extremum seeking algorithm proposed allows the optimal on-line bandwidth allocation, based only on the individual measurements of the utility function of each agent. We show how the extremum seeking control converges to a neighborhood of the optimal allocation, maximizing the general utility function of the network. This function can be externally manipulated by a network manager aiming to achieve a tradeoff between a “throughput” and a “fairness” behavior in the resource allocation solution.