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SNR-Based Link Quality Estimation

Authors: Wee Lum Tan; Peizhao Hu; Marius Portmann;

SNR-Based Link Quality Estimation

Abstract

The ability to accurately estimate wireless link quality is critical to the performance of routing protocols and rate adaptation algorithms in wireless mesh networks. Current link quality estimation methods utilize the packet delivery ratio (PDR) measurement of periodic broadcast probes sent at the lowest transmission rate. However, the estimated link quality does not readily translate to the performance of unicast data traffic at higher transmission rates. In this paper, we propose the use of a measurement-based signal-to-noise ratio (SNR) model to estimate wireless link quality in terms of its PDR performance. Using broadcast traffic measurements at the lowest transmission rate, we construct an "SNR profile'' that characterizes the relationship between the PDR metric and the SNR values computed at a node. We show how we can use the SNR profile to predict the PDR performance at different transmission rates. More importantly, we argue that the frame delivery ratio (FDR) at the MAC layer is a better link quality metric compared to PDR, and show that our proposed approach can use an SNR profile generated with broadcast traffic, to accurately estimate the FDR performance of unicast data traffic at different transmission rates. This then allows us to also accurately estimate the maximum achievable throughput of the wireless link at those rates.

Related Organizations
Keywords

Measurement, Signal to noise ratio, 2604 Applied Mathematics, 2208 Electrical and Electronic Engineering, 1706 Computer Science Applications, Probes, Receivers

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
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