Browsing Faculty Contributions by Subject "DRL"
Now showing items 1-2 of 2
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A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ... -
Joint resource allocation and power control for D2D communication with deep reinforcement learning in MCC
( Elsevier B.V. , 2021 , Article)Mission-critical communication (MCC) is one of the main goals in 5G, which can leverage multiple device-to-device (D2D) connections to enhance reliability for mission-critical communication. In MCC, D2D users can reuses ...