Spectrum management for wireless networks using adaptive control and game theory

Abstract

Radio frequency spectrum in wireless communication is a common resource shared by all collocated devices. Most spectrum management schemes rely on a centralized base station-receiver station relaying architecture. In contrast, infrastructure-less systems including wireless ad hoc networks require a scalable, distributed methodology. Moreover, the access has to be coordinated among the nodes in the network in the aspects which include power and rate adaptation. The challenge is to find an optimal tradeoff between such parameters not only for a particular link but also for an entire multi-hop network. Several existing schemes address power, throughput and Signal-to-Interference ratio (SIR) control on a link level. In contrast, the proposed work performs optimization for the entire network. The game theory methodology is employed to solve the distribution of the radio resources while the adaptive power and rate control estimates the required but unknown radio interface parameters online. Moreover, the adaptive power and rate control scheme optimizes the local channel access. The resulting spectrum channel management scheme becomes a hybrid of adaptive controls and game theory approaches that guarantees a fair and efficient channel sharing and maximizes the overall performance. The results are shown analytically and through simulations.