Application of reinforcement learning to admission control in CDMA network
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The paper describes an admission control algorithm for the CDMA networks which is able to adapt to the operating environment. The algorithm is based on the principle of reinforcement learning and it achieves near-optimal performance for various radio propagation conditions and network operator's objectives. The performance evaluation results for different state space alternatives and algorithm parameters are presented and compared with the conventional admission control based on the power thresholds.
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