Modeling iCAR via Multi-Dimensional Markov Chains

iCAR is a new wireless system architecture based on the integration of cellular and modern ad hoc relaying technologies. It addresses the congestion problem due to limited channel access in a cellular system and provides interoperability for heterogeneous networks. The iCAR system can efficiently balance traffic loads and share channel resource between cells by using ad hoc relaying stations (ARS) to relay traffic from one cell to another dynamically. Analyzing the performance of iCAR is nontrivial as the classic Erlang-B formula no longer applies when relaying is used. In this paper, we build multi-dimensional Markov chains to analyze the performance of the iCAR system in terms of the call blocking probability. In particular, we develop an approximate model as well as an accurate model. While it can be time-consuming and tedious to obtain the solutions of the accurate model, the approximate model yields analytical results that are close to the simulation results we obtained previously. Our results show that with a limited number of ARSs, the call blocking probability in a congested cell as well as the overall system can be reduced.