Optimal dynamic pricing strategies for mobile communication networks.

Techniques from engineering, economics and control theory are used in this thesis to investigate the effectiveness of dynamic pricing for demand control and capacity optimisation in cellular mobile networks. The scope is extended to include pricing strategies that can provide a certain target revenue for the network operator. Algorithms for the application of dynamic pricing in voice and data networks are suggested. Mathematical models are developed to predict the effect of dynamic pricing on the network operator's market share and the overall user demand, including the effect of variable tariffs on user mobility. The question of setting the optimal tariff for a given system load is addressed and three dynamic price setting methods suggested. The first, competition driven ad hoc pricing, is used to identify the most sensitive parameters in the model, namely the revenue generated and the level of call blocking in the network. Two further tariffs (linear revenue attainment and optimal revenue attainment) are then developed for controlling the system and ensuring optimal behaviour. The tariffs are tested using a seven-cell cellular model developed with OPNET TM. Simulation results show that the performance of the competition driven ad hoc and linear revenue attainment linear pricing strategies is varied and they lead to either a significant reduction in the revenue of the network operator or the welfare of users. The optimal revenue attainment price setting strategy, on the other hand, is shown to be an effective tool for generating the desired revenue, while decreasing the average price in the network and increasing the number of successful calls. In addition, it is suggested that the optimal dynamic pricing strategy could potentially increase a network operator's market share by up to 10% compared to traditional pricing policies, thus offering a viable pricing alternative