Paper Info
Title
RVFL-LQP: RVFL-Based Link Quality Prediction of Wireless Sensor Networks in Smart Grid
Abstract
In the application of wireless sensor networks (WSNs) to smart grid, real-time and accurate wireless link quality prediction (LQP) is important to determine which link is reliable enough to undertake the communication task. However, the existing LQP methods are neither suitable to describe the dynamic stochastic features of link quality nor to ensure the validity of prediction results. In this paper, a random-vector-functional-link-based LQP (RVFL-LQP) algorithm is proposed. The algorithm selects the signal-to-noise ratio (SNR) as the link quality metric and decomposes the raw SNR sequence into the time-varying sequence and the stochastic sequence according to the analysis of wireless link characteristics. Then, the RVFL network is used to establish the prediction model of the time-varying sequence and the variance of the stochastic sequence. Lastly, the probability-guaranteed interval boundary of SNR is predicted, and the validity and practicability of prediction results are evaluated by comparative experiments and real-world application, respectively.
Year
DOI
Venue
2020
10.1109/ACCESS.2020.2964319
IEEE ACCESS
Keywords
DocType
Volume
Wireless sensor networks,link quality prediction,RVFL network,probability-guaranteed interval boundary
Journal
8
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Xue Xue120.71
Wei Sun25012.99
Jianping Wang331.43
Qiyue Li45414.45
Guojun Luo501.35
Keping Yu612424.51