Abstract:In this paper, we propose a new Dynamic Spectrum Access (DSA) method for multi-channel wireless networks. We assume that DSA nodes do not have prior knowledge of the system dynamics, and have only partial observability of the channels. Thus, the problem is formulated as a Partially Observable Markov Decision Process (POMDP) with exponential time complexity. We have developed a novel Deep Reinforcement Learning (DRL) based DSA method which combines a double deep Q-learning architecture with a recurrent neural n… Show more
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