802.11 Link Quality and Its Prediction – An Experimental Study

Gaertner, G.; O'Nuallain, Eamonn Pol; Butterly, Andrew; Singh, Kulpreet; Cahill, Vinny

doi:10.1007/978-3-540-30199-8_13

Cited by 24 publications

(6 citation statements)

References 20 publications

(80 reference statements)

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“…For this reason we suggest a simple predictor that does not rely on node speed measurements. We observed in our real-world evaluation of LQP algorithms [32] that algorithms based only on the signal-power trend performed much more poorly than algorithms that relied on the local average signal power values only. We therefore propose simply using the most recent estimate of the local mean power as the signal-power prediction i.e.…”

Section: -97)mentioning

confidence: 81%

Link Quality Prediction for 802.11 MANETs in Urban Microcells

Gaertner¹,

Nuallain²

2016

JCC

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In this paper we derive the optimal link quality predictor (LQPR) whose parameters are estimated from signal power and node speed samples. We propose a fast estimator for these parameters whose computational complexity is three orders lower than that of the optimal estimator with only a slight loss in accuracy thus enabling realtime execution. We show that using the most recent local mean of the signal as a predictor of future signal strength is also a very close approximation to the optimal predictor. This is the central result of this paper. It obviates the need for complex and/or computationally intensive link quality predictors for 802.11 in urban microcells and has the advantage of not requiring node speed information. The LQPRs are evaluated against the lower error bound. We show that the LQPR based on the most recent local mean of the signal predicts the packet reception probability for pedestrians in urban microcells on average with a mean absolute error of 13.47%, 16.54%, 18.21% and 19.38% for 1 s, 2 s, 3 s and 4 s into the future respectively. This LQP accuracy resembles closely the lower error bound with, for example, a difference of only 2.47% at 2 s into the future.

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Section: -97)mentioning

confidence: 81%

Link Quality Prediction for 802.11 MANETs in Urban Microcells

Gaertner¹,

Nuallain²

2016

JCC

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“…The further the transmitter is, the lower is the received power. This assumes we are in a free space (without obstacles) (for dense urban areas, the parameters of the protocol will need to be adjusted since shadowing plays an important role as discussed in [8]). The received power measure is delivered by the wireless interface, and should be transmitted to the routing protocol.…”

Section: Assumptionsmentioning

confidence: 99%

Signal strength based link sensing for mobile ad-hoc networks

Ali¹,

Naimi²,

Busson³

2009

Telecommun Syst

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Mobility causes frequent link failures in ad-hoc networks. This results in a severe degradation of performance specially in case of high mobility of nodes. This is because the routing protocols for ad-hoc networks are not equipped to handle high mobility. In this paper, we have presented a new link management algorithm to locally manage links. This new mechanism is based on signal strength measurements. Researchers over the years have presented approaches which use signal strength measurements but their focus has been on re-active protocols while our algorithm is aimed at pro-active protocols. Pro-active protocols are used since they provide greater flexibility to take advantage of the mesh configuration. We develop the hysteresis mechanism provided by OLSR, based on hello packets, to include signal strength measurements. The mechanism in OLSR uses Hello packets received/lost to decide to establish link or not. The problem with this approach arises when there is high mobility in which case the time to break the link and use a new path becomes significant. To overcome this, we propose to use signal strength to determine if the link-quality This work is supported by the French government funded project ANR RNRT R2M (Reseaux Mesh et Mobilite-Mesh networks and mobility).

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“…All of the reviewed protocols were evaluated in their proposing papers 5, 7–12 via simulations in which deterministic transmission ranges were assumed and only path loss (according to the two‐ray ground model) was assumed to affect received signal powers. This can be realistic for simulations of an open field environment 15, but in a suburban or urban setting, shadowing, caused by buildings, cars and people can have a significant effect on the received signal strength 15. As the obstacles causing shadowing in a receiver's environment move, or the receiving node itself moves, the received signal strength fluctuates.…”

Section: Background On Qar and Ac Protocolsmentioning

confidence: 99%

The effects of shadow‐fading on QoS‐aware routing and admission control protocols designed for multi‐hop MANETs

Hanzo¹,

Tafazolli²

2011

Wireless Communications

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Providing quality‐of‐service (QoS) assurances in a mobile ad hoc network (MANET) is difficult due to node mobility, contention for channel access, a lack of centralised coordination, and the unreliable nature of the wireless channel. QoS‐aware routing (QAR) and admission control (AC) protocols comprise two of the most important components of a system attempting to provide QoS guarantees in the face of the above‐mentioned difficulties. This paper presents a comparative study, utilising a realistic shadow fading channel, of the performance of several state‐of‐the‐art amalgamated QAR‐AC protocols, which are designed for providing throughput guarantees to applications. The advantages and drawbacks of their particular features are highlighted. For an environment where link quality varies rapidly, the results of the study highlight the ineffectiveness of previously‐proposed methods of relying merely on the success of route discovery to perform AC, of relying on the exceeding of the MAC layer retransmission count for link failure detection, of existing congestion detection schemes and of careful re‐admission of data sessions rather than fast re‐routing after shadowing‐induced link failures. Based on the lessons learnt, design guidelines for future QAR and AC protocols operating in a mobile shadow‐fading‐afflicted environment are presented. Copyright © 2010 John Wiley & Sons, Ltd.

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802.11 Link Quality and Its Prediction – An Experimental Study

Cited by 24 publications

References 20 publications

Link Quality Prediction for 802.11 MANETs in Urban Microcells

Link Quality Prediction for 802.11 MANETs in Urban Microcells

Signal strength based link sensing for mobile ad-hoc networks

The effects of shadow‐fading on QoS‐aware routing and admission control protocols designed for multi‐hop MANETs

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