A unified optimization framework for design of CDMA cellular networks with uplink and downlink rate guarantees

There is an ever increasing need for the users to be able to communicate and exchange data with each other regardless of their physical locations. The cellular systems currently used provide mobile users with high speed data services at rates much higher than those of the voice channels. Designing a code division multiple access network is a complicated task requiring the selection of the locations(sites) for the base stations, the analysis of the customer demand and assurance of minimum quality-of service in terms of a minimum signal-to-interference ratio requirements. In these networks the system capacity and quality of service are related through the signal-to-interference-ratio measures.; A set of net revenue maximization models is presented in this thesis that can assist a network planner with the selection of tower sites and calculation of service capacity. These models take as input a set of candidate tower locations with the corresponding costs, a number of customer locations with the corresponding demand for service and the revenue potential for each unit of capacity allocated to each demand point. Based on this data and the requisite uplink and downlink quality of service requirements, the models can be used to determine the selection of towers and the resulting capacity of the network. These models consider the network from both the uplink and downlink perspective and allow the network provider a tradeoff between the total power used in the network and the net revenue. The numerical results of optimization suggest the following unconventional design guidelines: (i) The selection of base stations could be different if the design considers the uplink and downlink QoS constraints separately. (ii) A mobile user might receive service from different base stations in the uplink and downlink, and (iii) If there are multiple mobile users at a given location, they may all not receive service from the same base station. The framework directly extends to allow periodic reoptimization of existing cellular networks to meet dynamic demand variations.