Evolutionary algorithms for wireless network resource allocation

The advent of new generation of communication technologies has ushered in an era of high data rates, better quality and improved reliability. In order to exploit the full potential of next generation wireless networks, the available radio resources should be allocated and managed in an efficient manner. Orthogonal frequency division multiplexing (OFDM), with proven efficiency in transmission and capability in mitigating the ill effects of intersymbol interference innate in frequency selective environments, is regarded as a promising modulation scheme for broadband wireless applications. Multiuser OFDM taking advantage of channel diversity among different users can adaptively assign subcarriers to them depending on their channel conditions. Such an adaptive assignment of subcarriers and power to the users in accordance with their channel states results in increased throughput of the system. However, the problem of resource allocation in multiuser OFDM systems is known to be a nonpolynomial time hard (NP) problem. Evolutionary algorithms (EA) are typically used to provide good approximate solutions to such computationally intensive problems. However, EAs, by default, are designed to handle unconstrained optimization problems and need additional mechanics to handle constraints. In this chapter we present the use of some of the evolutionary algorithms and associated constrained handling techniques in order to handle resource allocation problems in emerging OFDMA-based wireless networks.