An Analytical Model for Wireless Networks with Stochastic Capacity

In wireless networks, the system capacity can vary unpredictably with time, due to mobility of users and dynamic channel assignment protocols. This variation in capacity with time, known as ‘stochastic capacity’, can have a major impact on the performance measures such as call blocking probability and queueing delay, of the wireless networks. The dependence of the stochastic capacity on the interaction between the input traffic and the wireless networks makes performance analysis for wireless networks a challenging task. In this paper, we present an analytical framework for the performance analysis of wireless networks with stochastic capacity variation. A capacity-traffic composite model is presented to reflect the interactions between the traffic process and the capacity variation process. With the assumption of general distributions for capacity variation process and exponential distributions for traffic process, the expressions for the performance measures are derived by using semi-Markov process and Markov regenerative theory. It is observed that high variance in the effective capacity of the underlying system degrades its performance. The analytical results are validated by extensive simulations.