Methods and Algorithms for Radio Channel Assignment

Radio channel assignment has attracted considerable interest over many years, spanning disciplines that include radio engineering, electrical engineering, physics, mathematics, computer science and economics. Over the last few years, there has been a rapid growth in the demand for wireless communications services, which has in turn created a need for Governments and industry to develop sound theory, methods, and computational tools for the effective and efficient management of the spectrum. This book contains a collection of contributions from those working in the field, which explore the various aspects of current research in channel radio assignment. The collection includes several chapters concerned with developing a sound theoretical framework for channel assignment. Other chapters are concerned with developing state-of-the-art computational algorithms for solving channel assignment problems, and two chapters discuss the regulatory aspects of spectrum management and its history. Also included are the modelling and efficient solution of network design problems, which are becoming increasingly important in wireless networks. Finally a chapter bridging the regulatory and mathematical issues describes the benefit of economic modelling in radio spectrum management. This book illustrates a range of mathematical and computational tools, including graph colouring, graph labelling, linear and nonlinear optimization, meta-heuristics, constraint satisfaction and multidisciplinary optimization. It is aimed at practising engineers, university academics with an interest in the area, and Government agencies responsible for the management of the radio spectrum. This title is the latest in the Oxford Lecture Series in Mathematics and its Applications, which aims to publish short books aimed at first-year graduates and academics in mathematics and related subjects. The Series focuses on future directions of research with emphasis on attractive genuine applications of the subject, particularly topics in the natural sciences.