Efficient Spectrum Utilization in Cognitive Radio Through Reinforcement Learning

Provided by: Creative Commons
Topic: Mobility
Format: PDF
Machine learning schemes can be employed in cognitive radio systems to intelligently locate the spectrum holes with some knowledge about the operating environment. In this paper, the authors formulate a variation of actor critic learning algorithm known as Continuous Actor Critic Learning Automaton (CACLA) and compare this scheme with actor critic Learning scheme and existing Q - learning scheme. Simulation results show that their CACLA scheme has lesser execution time and achieves higher throughput compared to other two schemes.

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