Several dynamic call admission control (CAC) schemes for cellular networks have been proposed in the literature to reserve resources adaptively to provide the desired quality of service (QoS) to not only high priority calls but also to low priority ones. Efficient adaptive reservations depend on reliable and up-to-date system status feedback provided to the CAC mechanism. However exact analysis of these schemes using multidimensional Markov chain models are intractable in real time due to the need to solve large sets of flow equations. Hence performance metrics such as call blocking probabilities of various QoS classes are generally evaluated using one dimensional Markov chain models assuming that channel occupancy times for all QoS classes have equal mean values and all arriving calls have equal capacity requirements. In this paper we re-evaluate the analytical methods to compute call blocking probabilities of various QoS classes for several widely known CAC schemes by relaxing these assumptions, and propose a novel approximation method for performance evaluation with low computational complexity. Numerical results show that proposed method provides results that match well with the exact solutions.
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