Name
Title | ||
|---|---|---|
Learning-Based Multi-Channel Access in 5G and Beyond Networks with Fast Time-Varying Channels |
Abstract | ||
|---|---|---|
We propose a learning-based scheme to investigate the dynamic multi-channel access (DMCA) problem in the fifth generation (5G) and beyond networks with fast time-varying channels wherein the channel parameters are unknown. The proposed learning-based scheme can maintain near-optimal performance for a long time, even in the sharp changing channels. This scheme greatly reduces processing delay, and ... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TVT.2020.2980861 | IEEE Transactions on Vehicular Technology |
Keywords | DocType | Volume |
Delays,Time-varying channels,Markov processes,5G mobile communication,Wireless communication,Quality of service,Optimization | Journal | 69 |
Issue | ISSN | Citations |
5 | 0018-9545 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shaoyang Wang | 1 | 3 | 2.74 |
| Tiejun Lv | 2 | 669 | 97.19 |
| Xuewei Zhang | 3 | 18 | 10.14 |
| Zhipeng Lin | 4 | 42 | 13.17 |
| Pingmu Huang | 5 | 7 | 1.23 |