Title
Shallow Reinforcement Learning for Energy Harvesting Communications With Imperfect Channel Knowledge
Abstract
This study aims to address the power allocation problem to maximize the sum of the generalized mutual information, which refers to the achievable rate with imperfect channel state information, through a reinforcement learning (RL) approach in energy harvesting communications. In contrast to the conventional deep RL applications, which incur a large computational load on the devices due to the use ...
Year
DOI
Venue
2021
10.1109/JSTSP.2021.3091842
IEEE Journal of Selected Topics in Signal Processing
Keywords
DocType
Volume
Resource management,Transmitters,Neural networks,Energy harvesting,Batteries,Mutual information,Computer architecture
Journal
15
Issue
ISSN
Citations 
5
1932-4553
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Heasung Kim100.34
Jungwoo Lee21467156.34
Wonjae Shin354.49
H. V. Poor4254111951.66