Adaptive Uniform Fractional Channel Algorithms

Dropping probability of handoff calls and blocking probability of new calls are two important QoS measures for cellular networks. Since the dropping probability of handoff calls is more important, call admission policies are used to maintain the upper bound of dropping probability of handoff calls. The fractional guard channel policy (FG) is a general call admission policy and includes most prioritized channel allocation schemes such as guard channel (GC), limited fractional guard channel (LFG), and uniform fractional channel policy (UFC) policies. Since the input traffic is not a stationary process and its parameters are unknown a priori, the optimal value of UFC parameter is not known in advance and possibly varies as traffic conditions change. In thi~ paper, we propose two adaptive algorithms based on learning automata for finding the optimal value of UFC parameter. To evaluate the proposed algorithms, the computer simulations are conducted. The simulation results show that for some range of input traffic, the performance of the proposed algorithms is close to the performance of the uniform fractional channel policy which knows the traffic parameters a priori.