Quality of service and performance evaluation: A fluid approach for poisson wireless networks

Kélif, Jean-Marc; Sénécal, Stéphane; Bridon, Constant; Coupechoux, Marceau

doi:10.1109/nof.2014.7119773

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…where a = 3 and b = -6, for a wide range of values of η (ranging from 2.2 to 4.2, usual range for the path-loss exponent is comprised between 2.8 and 3.6) We observed that for η = 2.8, 3, 3.6, 3.8, the CDF of the SINR established by the modified Fluid model and by the Poisson model are very close: the differences between them are less than 0.4 dB [17].…”

Section: Comparison Of the Sinr Cdf For The Poisson And Fluid Modelsmentioning

confidence: 71%

“…In the following section, we remind that we established [17] a correspondence between a stochastic Poisson network and the Fluid network model.…”

Section: B Calculation Of the Sinrmentioning

confidence: 99%

“…Since the CDF of the SINR characterizes the performance and the quality of service of wireless systems, we established a modified expression of the SINR given by the fluid model, which allows to calculate the CDF of SINR for the Poisson network reminded hereafter [17]:…”

Section: Comparison Of the Sinr Cdf For The Poisson And Fluid Modelsmentioning

confidence: 99%

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Analytical performance model for Poisson wireless networks with pathloss and shadowing propagation

Kélif

Sénécal

Coupechoux

et al. 2014

2014 IEEE Globecom Workshops (GC Wkshps)

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Abstract-The SINR (signal to interference plus noise ratio) is a key factor for wireless networks analysis. Indeed, the SINR distribution allows the derivation of performance and quality of service (QoS) evaluation. Moreover, it also enables the analysis of radio resources allocation and scheduling policies, since they depend on the SINR reached by a UE (User Equipment). Therefore, it is particularly interesting to develop an analytical method which allows to evaluate the SINR, in a simple and quick way, for a realistic environment. Considering a stochastic Poisson network model, we establish the CDF (cumulative distributed function) of the SINR. We show that the shadowing can be neglected, in many cases, as long as mobiles are connected to their best serving base station (BS), i.e. the BS which offers them the most powerful useful signal. As a consequence, the analysis of performance and quality of service, directly derived from the CDF of SINR, can be established by using a propagation model which takes into account only the pathloss. Moreover, we establish that the Fluid network model we have proposed can be used to analyze stochastic Poisson distributed network. Therefore, the analysis of stochastic Poisson network can be done in an easy and quick way, by using the analytical expression of the SINR established thanks to the Fluid network model.

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Section: Comparison Of the Sinr Cdf For The Poisson And Fluid Modelsmentioning

confidence: 71%

“…In the following section, we remind that we established [17] a correspondence between a stochastic Poisson network and the Fluid network model.…”

Section: B Calculation Of the Sinrmentioning

confidence: 99%

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Analytical performance model for Poisson wireless networks with pathloss and shadowing propagation

Kélif

Sénécal

Coupechoux

et al. 2014

2014 IEEE Globecom Workshops (GC Wkshps)

Self Cite

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“…We point out that the computational complexity of the model is out of the paper scope, as well as the comparison to the spatial Poisson process. In the latter case, some results can be found in [21].…”

Section: Introductionmentioning

confidence: 84%

Performance evaluation of JT CoMP approach: Tractable model using spatial fluid modeling

Zitoune

Cerovic

Cerović

et al. 2016

2016 IFIP Networking Conference (IFIP Networking) and Workshops

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Inter-cell interference is a major issue in OFDMA networks, due to the increasing density of Low Power Nodes (LPN) used to offload the macro base stations. Coordination between these nodes also called Coordination MultiPoint (CoMP), is identified as a promising solution to improve the signal quality and the achievable throughput while ensuring spectral efficiency over the network. Joint Transmission (JT) mode of CoMP consists to jointly transmit the useful signal from more than one BS, typically the best serving one, and one or several other base stations. In dense networks, the performance evaluation and the analysis of JT CoMP approach become a hard task which needs lot of time and huge resources to conduct simulations. In this paper, we present a new mathematical framework based on spatial fluid modeling which reduces the analysis complexity and provides a macroscopic evaluation of the performance, quite faithful to those obtained using Monte Carlo simulations. The key idea is to consider a continuum of nodes rather than a fixed finite number, and to derive the mean impact of a density of nodes in a certain region of the network. The closed-form formulas of the downlink interference factor are defined for three scenarios depending on the number of coordinated nodes. Then, they are used to evaluate the signal quality improvement, particularly at the cell edge.

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Effect of Shadowing on Energy Efficiency in Small Cellular Networks

Hou

Zitoune

2019

2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS

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Quality of service and performance evaluation: A fluid approach for poisson wireless networks

Cited by 3 publications

References 13 publications

Analytical performance model for Poisson wireless networks with pathloss and shadowing propagation

Analytical performance model for Poisson wireless networks with pathloss and shadowing propagation

Performance evaluation of JT CoMP approach: Tractable model using spatial fluid modeling

Effect of Shadowing on Energy Efficiency in Small Cellular Networks

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