Cell design to maximize capacity in cellular code division multiple access networks

Traditional design rules for cellular networks are not directly applicable to CDMA networks where inter-cell interference is not mitigated by cell placement and careful frequency planning. For transmission quality requirements, a minimum signal to interference ratio must be achieved. The base station location, its pilot-signal power (which determines the size of the cell), and the transmission power of the mobiles, all affect the received signal to interference ratio. In addition, because of the need for power control in CDMA networks, large cells can cause a lot of interference to adjacent small cells posing another constraint to design. In order to maximize the network capacity associated with a design, we develop a methodology to calculate the sensitivity of capacity to base station location, pilot-signal power, and transmission power of each mobile. In order to alleviate the problem caused by different cell sizes, we introduce the power compensation factor (PCF), which is a factor by which the nominal power of the mobiles in every cell is adjusted. We then use the calculated sensitivities in an iterative algorithm to determine the optimal locations of the base stations, pilot-signal powers, and power compensation factors in order to maximize capacity.; Call admission control (CAC) deals with the question of whether or not a network can accept a new call while maintaining the quality of service of the calls that have been previously accepted. Designing a CAC algorithm that guarantees call blocking probabilities for arbitrary traffic distribution while meeting the above objective is difficult in CDMA cellular systems. Due to self interference in CDMA, the number of simultaneous calls that can be accepted within one cell depends on the number of simultaneous calls being carried in all the cells in the network. We define a set of admissible call configurations that results in a CAC algorithm that captures the effect of having an arbitrary traffic distribution and whose complexity scales linearly with the number of cells. In order to evaluate the performance of our design, we calculate the network throughput. We present several examples demonstrating that our cell design methodology and our CAC algorithm can guarantee blocking probabilities and achieve higher capacity and throughput than traditional techniques.