Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject DQN
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| Issue Date | Title | Author(s) |
|---|---|---|
| 6-Nov-2023 | Simplified Deep Reinforcement Learning Approach for Channel Prediction in Power Domain NOMA System | Gaballa, M; Abbod, M |