Title
Adaptive relaying for full-duplex energy harvesting enabled cooperative communication in harsh environments.
Abstract
Energy harvesting (EH) enabled relaying has attracted considerable attentions as an effective way to prolong the operation time of energy-constrained networks and extend coverage beside desired survivability and rate of transmission. In most existing literatures, the Harvest-Store-Use (HSU) model is utilized to describe the energy flow behavior of the EH system. However, the half-duplex (HD) constraint of HSU that harvested energy can only be used after being temporally stored in energy storage unit may reduce effective transmission time. Thus, we first construct the full-duplex (FD) energy flow behavior model of the EH system where the harvested energy can be tuned to power load and being stored simultaneously, and then prove the FD model is equivalent to the HSU model when time interval is small enough. Considering some key physical variabilities, e.g., the wireless channel and the amount of harvested energy, we further study the transmission optimization problem to improve the utilization of the harvested energy by optimizing the short-term throughput. Finally, to numerically obtain the optimized short-term throughput, we propose the adaptive relaying algorithm, including power control for source and relay nodes, relay selection and dynamic switching among four relay transmission modes, namely, HD amplify-and-forward (AF), HD decode-and-forward (DF), FD AF and FD DF. Results show that short-term throughput of the system can be improved through adaptive relaying in the proposed algorithm.
Year
Venue
Field
2016
IEEE Military Communications Conference
Energy storage,Computer science,Power control,Computer network,Energy harvesting,Electronic engineering,Real-time computing,Throughput,Transmission time,Energy consumption,Relay,Duplex (telecommunications)
DocType
ISSN
Citations 
Conference
2155-7578
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Zejue Wang1244.75
Hongjia Li242.81
Dan Wang312.04
Liming Wang4138.75
Song Ci51086106.10