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Neural-Network-Based Power Control Prediction for Solar-Powered Energy Harvesting Communications
Meng Lin Ku
, Ting Jui Lin
通訊工程學系
研究成果
:
雜誌貢獻
›
期刊論文
›
同行評審
11
引文 斯高帕斯（Scopus）
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深入研究「Neural-Network-Based Power Control Prediction for Solar-Powered Energy Harvesting Communications」主題。共同形成了獨特的指紋。
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Keyphrases
Neural Network
100%
Power Control
100%
Single User
100%
Solar Power
100%
Energy Harvesting Communications
100%
Channel State Information
50%
Multi-user
50%
Energy State
50%
State Information
50%
Solar Radiation Data
50%
Transmit Power
33%
Multi-user Setting
33%
State Energy
33%
Information State
33%
State Knowledge
33%
User Scenario
33%
Directional Water-filling
33%
Transmitter
16%
Centralized Controller
16%
Minimum Mean Square Error
16%
Prediction Scheme
16%
Full State
16%
Value-based
16%
Control Problem
16%
Multi-user Interference
16%
Weighted Sums
16%
Signaling Overhead
16%
Transmission Power Control
16%
Nonconvex
16%
Iterative Algorithm
16%
Sum-rate Performance
16%
User Pairing
16%
Power Values
16%
User Cases
16%
Information Energy
16%
Distributed Scheme
16%
Centralized Scheme
16%
Engineering
Energy Harvesting
100%
Multiuser
100%
Power Control
100%
Single User
100%
Channel State Information
50%
Energy State
50%
State Information
50%
Directional
33%
Knowledge State
33%
Simulation Result
16%
Mean Square Error
16%
Iterative Algorithm
16%
Signaling Overhead
16%
Optimal Scheme
16%
Central Controller
16%
Computer Science
Neural Network
100%
Channel State Information
100%
State Information
100%
Knowledge State
66%
Iterative Algorithm
33%
multiuser interference
33%
sum rate
33%
Chemical Engineering
Neural Network
100%