Browsing Electrical & Electronics Engineering by Subject "Deep reinforcement learning"
Now showing items 1-3 of 3
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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 ... -
Joint lifetime-outage optimization in relay-enabled IoT networks—A deep reinforcement learning approach
(IEEE, 2023-01)Network lifetime maximization in Internet of things (IoT) is of paramount importance to ensure uninterrupted data transmission and reduce the frequency of battery replacement. This letter deals with the joint lifetime-outage ...
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