In this paper, we represent the whole cellular network as a multi-dimensional Markov chain model, and present how to calculate upper and lower bounds of various performance measures. When we evaluate performances in a base station or local network, we select some base stations around it and aggregate the others by the aggregation method. Hence, we reduce the amount of calculation to a practical size. We formulate the aggregated model as a Markov decision process. We calculate upper and lower bounds of the accurate performance measures to the whole networks by the policy iteration method. Considering them, the accuracy of them is quite obvious. This accuracy becomes better by increasing the number of the selected base stations.
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