Extending Wireless Network Simulators to Support Realistic Simulations of 802.11 MANETs

Gaertner, G.; Nuallain, Eamonn O.; Cahill, Vinny

doi:10.1109/wicom.2008.650

Cited by 1 publication

(3 citation statements)

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“…This we achieve using an extended NS Simulator [11]. In this paper we use two mobility models (the Random Waypoint Mobility Model (RWP) and the Random Waypoint Mobility Model City Section (CITY).…”

Section: Augmenting the Ns Simulatormentioning

confidence: 99%

“…We examine the effect of some of the factors that affect predictive accuracy. A brief summary of the extensions we made to the simulator [11] is given here: a) Augmenting the Path-Loss Model in the NS Simulator:…”

Section: Augmenting the Ns Simulatormentioning

confidence: 99%

“…The results given by this predictor are very close to those given by the optimal predictor and so obviate the need for complex/computationally intensive predictors. We assess the accuracy of the DES and LLM predictors against the THEO baseline by simulations in an enhanced NS simulator [11]. This is done over a comprehensive range of scenarios with respect to various factors which we expect may influence LQP accuracy i.e.…”

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confidence: 99%

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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: Augmenting the Ns Simulatormentioning

confidence: 99%

Section: Augmenting the Ns Simulatormentioning

confidence: 99%

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confidence: 99%

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