Markov Model Bank for heterogenous cognitive radio networks with multiple dissimilar users and channels

In this paper, we develop a Markov Model Bank (MMB) to analyze the heterogeneous cognitive radio networks (CRN) with a large number of dissimilar secondary users (SU) coexisting and competing for multiple dissimilar channels. The MMB consists of a separate Markov chain for each SU. The Markov chains are connected implicitly by a few state transitional probabilities that can be derived by analyzing the mutual interference among the SUs. We first develop the expressions of the transitional probabilities and the throughput in the general heterogeneous users setting. Then, by exploiting some special advantages of the MMB in spatial, channel and user de-correlation, we reduce the complexity of evaluating such expressions to a great extent so as to make it feasible to analyze the throughput of large heterogeneous CRNs under various channel access strategies. Simulations are conducted to verify the proposed approaches.