On the performance of heterogeneous wireless networks with heavy tail traffic

The performance metrics are very important for performance evaluation and system design. In the literature, their analyses are given only when the traffic with classical exponential distribution under time invariant channels. In this paper, using multidimensional Markov model, we analyze the performance of heterogeneous wireless networks with heavy tail traffic under the time variant channels. Some specific network selection strategies, such as load balancing based network selection policy, random network selection policy and greedy network selection policy, are analyzed in terms of blocking probability, average number of users, throughput and delay. Among them, greedy network selection policy achieves the lowest blocking probability, the minimum average number of users and the lowest delay. Numerical results demonstrate that our theoretical values are coincide with the simulation results.