Publication record · 2025
A novel DRL-transformer framework for maximizing the sum rate in reconfigurable intelligent surface-assisted THz communication systems
- Authors
- Year
- 2025
- Publisher
- MDPI
- Journal or publication
- Applied Sciences
- Google Scholar citations
- 4
Journal indicators
CiteScore 2025 (Scopus)6.1
Best quartileQ1
Top 10% in any categoryNo
Positions by category
- Fluid Flow and Transfer Processes18/99 · Q1 · percentile 82
- Instrumentation37/206 · Q1 · percentile 82
- Engineering (all)66/351 · Q1 · percentile 81
- Computer Science Applications297/1022 · Q2 · percentile 70
- Materials Science (all)151/475 · Q2 · percentile 68
- Process Chemistry and Technology33/84 · Q2 · percentile 61
JCR (Clarivate): Not verified: the supplied ranking file is Scopus CiteScore, not JCR.
Included in the supplied report on non-standard bibliometric behaviour (2017–2019).
The report is an independent analysis published in 2021; it is not an official ANECA ban or endorsement list.Research summary
An optimized DRL-Transformer controls beamforming and phase shifts in RIS-assisted terahertz communications. Transformer channel representations, adaptive reinforcement learning and biogeography-based tuning target higher sum rate, faster convergence and robustness for 6G networks.
Original description prepared for this website; consult the publication for its authoritative abstract.DOI 10.3390/app15179435 ↗ · Open-access version ↗ · View Google Scholar record ↗