Dynamic resource allocation in CDMA cellular communications systems

Abstract

Efficient resource utilization is the primary problem in cellular communication systems. In this thesis, we combine the main resource issues for CDMA systems, admission control and power control, in a single framework. The framework uses a formulation that is general enough to incorporate all significant parameters of a system, yet tractable to compute. We formulate the resource allocation problem as a Markov decision process. Due to the enormous size of the state space, applying the traditional solution technique, dynamic programming, is impractical. We therefore consider approximation techniques. As a first step towards simplification, we divide the problem into two subproblems: optimal admission control with heuristic power control and optimal power control with heuristic admission control. We formulate the problem of optimal admission control as a Markov decision process and consider several approximate dynamic programming techniques. We apply these techniques to a simulated system and obtain results that improve significantly upon two commonly used policies, the greedy policy and the reservation policy. We then consider the minimization of the total power transmitted over given discrete sets of available power levels subject to maintaining an acceptable signal quality for each mobile. We develop sequential and distributed iterative algorithms for solving a more general version of this integer programming problem and show that they find the optimal solution in a finite number of iterations which is polynomial in the number of power levels and the number of mobiles.