| Related citation: | Lin-Lan Liu,Chao Zang,Jian Shu,Lin-Xin Zeng,Sarah Morrison.S3LQA: A Link Quality Assessment Metric for WSNs Based on Symbol Error and Received Signal Strength[J].Journal of Harbin Institute Of Technology(New Series),2013,20(2):33-39.DOI:10.11916/j.issn.1005-9113.2013.02.007. |
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| Author Name | Affiliation | | Lin-Lan Liu | Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China | | Chao Zang | Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China | | Jian Shu | Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China | | Lin-Xin Zeng | Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China | | Sarah Morrison | Wheaton College, Traverse 56296, America |
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| Abstract: |
| With the rapid evolution of WSNs technology, it is very important to evaluate link quality quickly and accurately, so that the routing protocols can take relevant strategies in time to keep the entire network working steadily and efficiently. However, the issue of improving link quality assessment methods on physical layer is still open to research. To tackle this issue, a novel link quality assessment metric called S3LQA is proposed, which estimates the link quality of wireless sensor networks by CC2420 wireless radio frequency transceiver principles and free space propagation theory. The metric adopts both complete and incomplete packages to improve the evaluation performance effectively based on IEEE802.15.4 frame format and DSSS-O-QPSK mechanism. The experimental results show that the proposed method can improve energy cost and achieves better real-timing performance than traditional counting-based (PRR) link quality assessment metric. |
| Key words: wireless sensor networks link quality assessment symbol error received signal strength |
| DOI：10.11916/j.issn.1005-9113.2013.02.007 |
| Clc Number:TN91 |
| Fund: |
