Name
Title | ||
|---|---|---|
Deep Reinforcement Learning Optimal Transmission Policy for Communication Systems with Energy Harvesting and Adaptive MQAM |
Abstract | ||
|---|---|---|
In this paper, we study an optimal transmission problem in a point-to-point wireless communication system with energy harvesting and limited battery at its transmitter. Considering the non-availability of prior information about distribution on energy arrival process and channel coefficient, we propose a deep reinforcement learning (DRL) based optimal policy to allocate transmission power and adap... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TVT.2019.2911544 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Wireless communication,Modulation,Throughput,Energy harvesting,Data models,Markov processes | Mathematical optimization,Markov process,Computer science,Communication channel,Markov decision process,Communications system,Electronic engineering,Throughput,Optimization problem,State space,Reinforcement learning | Journal |
Volume | Issue | ISSN |
68 | 6 | 0018-9545 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyu Li | 1 | 20 | 8.37 |
| Xiaohui Zhao | 2 | 87 | 15.89 |
| Hui Liang | 3 | 14 | 8.24 |
| Fengye Hu | 4 | 71 | 20.07 |