The cellular telephone success story has prompted the wireless communications community to turn its attention to other information services, many of them in the category of "wireless data" communica5ions. One lesson of cellular telephone network operation is that effective radio resource management (power control, channel assignment and handoffs) is essential to promote the quality and efficiency of a system. Radio resource management will be equally, if not more, critical in systems that include high-speed data signals. This research focuses on developing a new framework for radio resource management in wireless data networks. The new approach considered here relies on using microeconomic theories that take into account notions utility (level of satisfaction of a user) and pricing (cost charged to a user) in developing distributed radio resource management algorithms for wireless data services. This research will make fundamental contributions that impact knowledge and technology in the currently evolving third generation of wireless systems.
A model for the utility of a data user is developed that is based on the number of useful bits that a wireless terminal can transfer over the lifetime of its battery. Based on such a model for the utility wireless data user derives from using the system, distributed power control algorithms that maximize utility are considered. Formulating these algorithms as noncooperative games, conditions for feasibility of such power control as well as existence and uniqueness of the Nash equilibrium achieved by the non-cooperative game are investigated. The resulting equilibria are shown to be Pareto inefficient, thereby motivating the introduction of pricing to achieve Pareto improvements in efficiency. The goals of this research are to investigate utility and pricing functions that will drive distributed resource management schemes (optimization algorithms) to Pareto efficient operating points. Specific issues to be considered include noncooperative games based on power and rate optimization, utility maximization under delay constraints, information theoretic notions of utility and corresponding games, and dynamic pricing under energy-constrained transmission. The educational objectives of the investigator include: (i) a multidisciplinary course in wireless communications with graduate students from electrical engineering, computer science and mass communications; (ii) a wireless communications technology course discussing theoretical aspects of wireless and its relations to practical standards; (iii) special undergraduate research initiatives focusing on the wireless internet and applications.
