Approximate SIR Analysis in General Heterogeneous Cellular Networks

Wei, Haichao; Deng, Na; Zhou, Wuyang; Haenggi, Martin

doi:10.1109/tcomm.2015.2514085

Cited by 45 publications

(31 citation statements)

References 23 publications

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“…Interestingly, as observed in Figure. 4.6 as well as in the literature [8,13,[45][46][47][48], the coverage probability curves of different BS deployments appear to be a horizontally shifted version of each other. This shift is a difference in the SIR threshold (in dB)…”

Section: Introductionsupporting

confidence: 52%

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Lagum¹

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To meet the ever-increasing traffic demand in modern cellular networks, deploying more BSs has imposed is a vital solution. Cellular network (re-)planning is crucial to mitigate the interference and improve the network performance whenever more base stations (BSs) are deployed or some BSs are removed. Realistic spatial modelling for the locations of BSs and accurate quantification for their spatial relationship are prerequisites for effective network planning.In the first part of this thesis, we aim to describe the spatial structure of the BSs using two scalar measures: the density of the BSs and the amount of regularity. We investigate the use of three scalar metrics to measure the spatial relationships among the BSs in cellular networks. We propose a geometry-based scalar metric (the coefficient of variation (CoV) of the length of the corresponding edges of Delaunay triangulation) to quantify the spatial regularity of the repulsive wireless networks. This work develops new approaches for i) mapping between the internal parameters of different point processes commonly used to generate the BS locations, ii) approximating the performance of a repulsive network based on its amount of regularity, and iii) fitting point processes to the spatial deployment of BSs.In the second part, we develop a novel stochastic geometry-based cellular network planning technique that relies on the spatial structure of the network to determine the best deployment or removal locations of the BSs. First, we apply this technique for cell deactivation during the low demand periods. More specifically, cells are switched off so that the remaining active cells are as far away as possible from each other, which maximizes the spatial regularity of the network. The results show significant energy saving and network performance enhancement. Second, we exploit this approach for the strategic densification with UAV-BSs in cellular networks: The deployment of multiple UAV-BSs in the presence of a terrestrial network where the UAV-BSs provide on-demand capacity to the end users. This study provides supply-side estimation for how many UAV-BSs are needed to support a terrestrial network so as to achieve a iii particular quality-of-service and also demonstrate where these UAV-BSs should hover.iv Dedicated to whom this thesis matters most, My parents, Suliman and Saddina, my wife, Nisreen, and my childeren, Suliman and Rose.

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Section: Introductionsupporting

confidence: 52%

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Lagum¹

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“…In [20], a formula is derived to approximately calculate G 0 analytically for (stationary) non-Poisson point process models whenever the second moment of the contact distance is available. [21] showed that the ASAPPP approximation works very well for HCNs with non-Poisson deployment of BSs. First, [21] proposed the per-tier ASAPPPbased approximation for general HCNs, where the ASAPPP approximation was used to approximate the SIR distribution corresponding to each non-Poisson tier using the MISR-based deployment gain G 0 .…”

Section: B Related Workmentioning

confidence: 99%

Simple Approximations of the SIR Meta Distribution in General Cellular Networks

Kalamkar

Haenggi

2019

IEEE Trans. Commun.

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Compared to the standard success (coverage) probability, the meta distribution of the signal-to-interference ratio (SIR) provides much more fine-grained information about the network performance. We consider general heterogeneous cellular networks (HCNs) with base station tiers modeled by arbitrary stationary and ergodic non-Poisson point processes. The exact analysis of non-Poisson network models is notoriously difficult, even in terms of the standard success probability, let alone the meta distribution. Hence we propose a simple approach to approximate the SIR meta distribution for non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on the Poisson point process") method. We prove that the asymptotic horizontal gap G0 between its standard success probability and that for the Poisson point process exactly characterizes the gap between the bth moment of the conditional success probability, as the SIR threshold goes to 0. The gap G0 allows two simple approximations of the meta distribution for general HCNs: 1) the per-tier approximation by applying the shift G0 to each tier and 2) the effective gain approximation by directly shifting the meta distribution for the homogeneous independent Poisson network. Given the generality of the model considered and the finegrained nature of the meta distribution, these approximations work surprisingly well.Index Terms-Interference, heterogeneous cellular networks, meta distribution, Poisson point process, signal-to-interference ratio, stochastic geometry S. S. Kalamkar is with INRIA, Paris, France. M. Haenggi is with the

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“…It is worth mentioning, finally, the relevance that tractable but accurate approximations are recently gaining in the context of stochastic geometry analysis of realistic but intractable network models [22]. The IM-based approach provides a contribution to these research activities.…”

Section: Remark 11mentioning

confidence: 99%

“…The BSs are, however, still assumed to be distributed according to a PPP. Current research activities on modeling the locations of cellular BSs with the aid of point processes different from the PPP, e.g., [22], are complementary to the proposed IM-based approach. The generalization of the IM-based approach to account for non-PPP models for the locations of cellular BSs is a research issue currently being investigated by the authors.…”

Section: Remark 11mentioning

confidence: 99%

The Intensity Matching Approach: A Tractable Stochastic Geometry Approximation to System-Level Analysis of Cellular Networks

Renzo

Wei

Guan

2016

IEEE Trans. Wireless Commun.

110

120

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The intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as points of a Poisson point process and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the intensity measure of transformations of the underlaying spatial Poisson point process. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient intensity measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight and non-line-of-sight propagation, antenna radiation patterns, traffic load, practical cell associations, general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.

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Approximate SIR Analysis in General Heterogeneous Cellular Networks

Cited by 45 publications

References 23 publications

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Stochastic Geometry-Based Tools for Spatial Modeling and Planning of Future Cellular Networks: Opportunistic Cell Switch-off and Strategic Deployment of Flying Base Stations

Simple Approximations of the SIR Meta Distribution in General Cellular Networks

The Intensity Matching Approach: A Tractable Stochastic Geometry Approximation to System-Level Analysis of Cellular Networks

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