SIR Estimation in Hexagonal Cellular Networks with Best Server Policy

Minelli, Mattia; Coupechoux, Marceau; Kélif, Jean-Marc; Godlewski, Philippe

doi:10.1007/s11277-012-0565-y

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…The main idea is to connect the user to a specific BS and then truncate the corresponding SINR distribution below a certain threshold because it is likely that the user connects to another BS. The work in [9] extends the model from [8] by shadowing cross-correlation and noise. Although the approaches in [8] and [9] are simple and sufficiently accurate for many purposes, e.g., estimating the 50 th percentile of the SINR, they are not capable to model the left tail of the SINR distribution with high accuracy.…”

Section: Introductionmentioning

confidence: 93%

“…The work in [9] extends the model from [8] by shadowing cross-correlation and noise. Although the approaches in [8] and [9] are simple and sufficiently accurate for many purposes, e.g., estimating the 50 th percentile of the SINR, they are not capable to model the left tail of the SINR distribution with high accuracy.…”

Section: Introductionmentioning

confidence: 93%

“…Furthermore, in [7], Kelif et al numerically evaluate the impact of the best server association and show that in certain scenarios it is sufficient to neglect shadowing and connect the users to the closest BS. Another related work can be found in [8], where an approximation of the SINR distribution for hexagonal cellular networks is presented. The main idea is to connect the user to a specific BS and then truncate the corresponding SINR distribution below a certain threshold because it is likely that the user connects to another BS.…”

Section: Introductionmentioning

confidence: 99%

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SINR Model With Best Server Association for High Availability Studies of Wireless Networks

Ohmann

Awada

Viering

et al. 2016

IEEE Wireless Commun. Lett.

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The signal-to-interference-and-noise ratio (SINR) is of key importance for the analysis and design of wireless networks. For addressing new requirements imposed on wireless communication, in particular high availability, a highly accurate modeling of the SINR is needed. We propose a stochastic model of the SINR distribution where shadow fading is characterized by random variables. Therein, the impact of shadow fading on the user association is incorporated by modification of the distributions involved.The SINR model is capable to describe all parts of the SINR distribution in detail, especially the left tail which is of interest for studies of high availability.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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SINR Model With Best Server Association for High Availability Studies of Wireless Networks

Ohmann

Awada

Viering

et al. 2016

IEEE Wireless Commun. Lett.

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“…Papers generally analyze the shadowing impact by considering users connected to their nearest BS [9] [10]. Recent papers [11] [12] analyze the impact of shadowing by considering users connected to the BS which offers the highest useful signal.…”

Section: Introductionmentioning

confidence: 99%

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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Best Server SINR Models for Single- and Multi-Point Transmission in Wireless Networks

Ohmann¹,

Awada²,

Viering³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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SIR Estimation in Hexagonal Cellular Networks with Best Server Policy

Abstract: International audienc

Cited by 5 publications

References 14 publications

SINR Model With Best Server Association for High Availability Studies of Wireless Networks

SINR Model With Best Server Association for High Availability Studies of Wireless Networks

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

Best Server SINR Models for Single- and Multi-Point Transmission in Wireless Networks

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