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Deep Q-learning based optimization of VLC systems with dynamic time-division multiplexing
(IEEE, 2020)
The traditional method to solve nondeterministic-polynomial-time (NP)-hard optimization problems is to apply meta-heuristic algorithms. In contrast, Deep Q Learning (DQL) uses memory of experience and deep neural network ...
Deep reinforcement based power allocation for the max-min optimization in non-orthogonal multiple access
(IEEE, 2020)
NOMA is a radio access technique that multiplexes several users over the frequency resource and provides high throughput and fairness among different users. The maximization of the minimum the data-rate, also known as ...
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