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A Self-Learning Call Admission Control Scheme for CDMA Cellular Networks
2005
IEEE Transactions on Neural Networks
In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call
doi:10.1109/tnn.2005.853408
pmid:16252828
fatcat:qfe5fsnhubg5bpmpij5u2a4qbi