scholarly journals Radio Link Quality Estimation in Low-Power Wireless Networks

2013 ◽  
Author(s):  
Nouha Baccour ◽  
Anis Koubâa ◽  
Claro Noda ◽  
Hossein Fotouhi ◽  
Mário Alves ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Low Power ◽  
Link Quality ◽  
Radio Link ◽  
Quality Estimation ◽  
Low Power Wireless Networks ◽  
Link Quality Estimation

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

2015 ◽  
Vol 27 ◽  
pp. 1-25 ◽  
Author(s):  
Nouha Baccour ◽  
Anis Koubâa ◽  
Habib Youssef ◽  
Mário Alves
Keyword(s):  
Wireless Networks ◽  
Low Power ◽  
Link Quality ◽  
Quality Estimation ◽  
Tree Routing ◽  
Low Power Wireless Networks ◽  
Link Quality Estimation

scholarly journals Radio link quality estimation in wireless sensor networks

2012 ◽  
Vol 8 (4) ◽  
pp. 1-33 ◽  
Author(s):  
Nouha Baccour ◽  
Anis Koubâa ◽  
Luca Mottola ◽  
Marco Antonio Zúñiga ◽  
Habib Youssef ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Link Quality ◽  
Wireless Sensor ◽  
Radio Link ◽  
Quality Estimation ◽  
Link Quality Estimation

scholarly journals A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jie Li ◽  
Yang Pan ◽  
Shijian Ni ◽  
Feng Wang
Keyword(s):  
Wireless Networks ◽  
Routing Algorithm ◽  
Link Quality ◽  
Quality Estimation ◽  
Received Signal Strength Indicator ◽  
Industrial Environment ◽  
Reliable Routing ◽  
Industrial Wireless Networks ◽  
Link Quality Indicator ◽  
Link Quality Estimation

In Industrial Wireless Networks (IWNs), the communication through Machine-to-Machine (M2M) is often affected by the noise in the industrial environment, which leads to the decline of communication reliability. In this paper, we investigate how to improve route stability through M2M in an industrial environment. We first compare different link quality estimations, such as Signal-Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Packet Reception Ratio (PRR), and Expected Transmission Count (ETX). We then propose a link quality estimation combining LQI and PRR. Finally, we propose a Hybrid Link Quality Estimation-Based Reliable Routing (HLQEBRR) algorithm for IWNs, with the object of maximizing link stability. In addition, HLQEBRR provides a recovery mechanism to detect node failure, which improves the speed and accuracy of node recovery. OMNeT++-based simulation results demonstrate that our HLQEBRR algorithm significantly outperforms the Collection Tree Protocol (CTP) algorithm in terms of end-to-end transmission delay and packet loss ratio, and the HLQEBRR algorithm achieves higher reliability at a small additional cost.

scholarly journals Machine Learning for Wireless Link Quality Estimation: A Survey

2021 ◽  
pp. 1-1
Author(s):  
Gregor Cerar ◽  
Halil Yetgin ◽  
Mihael Mohorcic ◽  
Carolina Fortuna
Keyword(s):  
Machine Learning ◽  
Link Quality ◽  
Wireless Link ◽  
Quality Estimation ◽  
Link Quality Estimation

scholarly journals Accurate and Generic Sender Selection for Bulk Data Dissemination in Low-Power Wireless Networks

2017 ◽  
Vol 25 (2) ◽  
pp. 948-959 ◽  
Author(s):  
Zhiwei Zhao ◽  
Wei Dong ◽  
Jiajun Bu ◽  
Tao Gu ◽  
Geyong Min
Keyword(s):  
Wireless Networks ◽  
Low Power ◽  
Data Dissemination ◽  
Bulk Data ◽  
Selection For ◽  
Low Power Wireless Networks
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