Coverage, Handoff and cost optimization for 5G Heterogeneous Network

Ouamri, Mohamed Amine; Oteşteanu, Marius-Emil; Isar, Alexandru; Azni, Mohamed

doi:10.1016/j.phycom.2020.101037

Cited by 39 publications

(34 citation statements)

References 17 publications

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“…Theorem 1: The conditional coverage probability for 5G-Hetnet, when the link between UE and BS follows a LOS\NLOS propagation can be expressed as (see (15)) , where…”

Section: Signal-to-interference-plus-noise Ratiomentioning

confidence: 99%

“…By modelling the placement of BSs as

β

‐GPP in mmWave Hetnet, SINR coverage probability is computed and analysed, based on target threshold [12]. Recently, in our prior work [15], coverage and handoff analysis in two‐tier 5G‐Hetnet have been provided taking into consideration the distribution of macro‐BS and micro‐BS as homogeneous Poisson point process (HPPP), where directional beamforming was incorporated. Regarding performance analysis of cellular mobile network [16], coverage analysis in small cell Hetnet based on stochastic geometry is proposed by examining the impact of distance‐dependent Ricien fading channel model.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast to the work in [19], this paper investigates coverage performance under Nakagami fading with β‐GPP. In [15, 20], all nodes are equipped with single antenna and use traditional path loss model to evaluate coverage probability, however, this work assumes single antenna with beamforming and Tow‐ball path loss model. Our analysis shows that the convergence of the coverage probability is significant compared to [12, 19] by varying the parameters such as antenna main lobe gain and biasing factors.…”

Section: Related Workmentioning

confidence: 99%

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Coverage and rate analysis for 5G‐heterogeneous network: β‐Ginibre point process

Ouamri

2020

IET Communications

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Stochastic geometry is emerging as tractable solution and attractive approach to evaluate the performance of 5G heterogeneous network (5G-Hetnet) such as coverage, outage and rate probability. The base stations (BSs) and fading distribution in 5G-Hetnet are an almost ubiquitous assumption for analytical study, requiring flexible and scalable approaches. However, the β-Ginibre point process (β-GPP) has been proposed as a new method to model wireless network. This study provides a general framework to analyse downlink mmWave cellular network with Nakagami-m fading and directional beamforming. First, cell association scheme in both line-of-site and non-line-of-site is considered based on the strongest average received power. After deriving cell association probability between user equipment and BS, the computationally coverage probability expression is obtained depending on signal-to-interference-plus-noise ratio. Furthermore, the impact of biasing factor on rate coverage probability is investigated. Finally, considering inter-cell-interference coordination, most performances metrics will be re-evaluated to determine their influence on the network. Recommended approaches produce satisfactory results when biasing factor and antenna beamforming are used.

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“…Theorem 1: The conditional coverage probability for 5G-Hetnet, when the link between UE and BS follows a LOS\NLOS propagation can be expressed as (see (15)) , where…”

Section: Signal-to-interference-plus-noise Ratiomentioning

confidence: 99%

“…By modelling the placement of BSs as

β

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Coverage and rate analysis for 5G‐heterogeneous network: β‐Ginibre point process

Ouamri

2020

IET Communications

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“…SG cellular models that end up with coverage probability expressions involving the BS density, λ , abound. Examples of such models for DL are [ElSawy et al, 2017, Liu et al, 2020b, Liu and Zhang, 2020, Kouzayha et al, 2021, Bai and Heath, 2015, Chen and Yuan, 2019, Liu et al, 2020a, Ouamri et al, 2020, Lei et al, 2018, Fadouol, 2020, Gao et al, 2019, Ali et al, 2019, Andrews et al, 2016, Kundu et al, 2020, Sadeghabadi et al, 2020, Wang and Gursoy, 2019. On the other hand, examples of such models for DL are [ElSawy et al, 2017, Liu et al, 2020b, Haroon et al, 2021, Herath et al, 2018, Kouzayha et al, 2018, Mariam et al, 2021, Andrews et al, 2016, Jia et al, 2019, Gao et al, 2019, Ali et al, 2019, Kundu et al, 2020, Sadeghabadi et al, 2020, Wang and Gursoy, 2019.…”

Section: Introductionmentioning

confidence: 99%

Cellular Coverage Probability Is Independent of Base Station Density under Stochastic Geometric Models

2021

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Stochastic geometry (SG) has been extensively used to model cellular communications, under the assumption that the base stations (BS) are deployed as a Poisson point process in the Euclidean plane. This use has spawned a huge number of articles over the past years for different scenarios, culminating in an equally huge number of expressions for the coverage probability in both the uplink (UL) and downink (DL) cellular directions. The problem is that those expressions include the BS density, λ , which we prove irrelevant in this article. We start by developing a SG model for a baseline cellular scenario, then prove that its coverage probability is independent of λ , contrary to popular belief.

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“…These models are developed for different scenarios, but have in common the consideration that the coverage probability is dependent on 𝜆. Examples of such models for DL are [2], [4], [6], [8], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23]. On the other hand, examples of such models for DL are [2], [4], [7], [24], [25], [26], [20], [27], [18], [19], [21], [22], [23].…”

Section: Introductionmentioning

confidence: 99%

Cellular coverage probability is independent of base station density under stochastic geometric models

Nassar¹

2021

Preprint

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Stochastic geometry (SG) has been extensively used to model cellular communications, under the assumption that the base stations (BS) are deployed as a Poisson point process in the Euclidean plane. This has spawned a huge number of articles over the past years for different scenarios, culminating in an equally huge number of expressions for the coverage probability in both the uplink (UL) and downink (DL) directions. The trouble is that those expressions include the BS density, $\lambda$, which we prove irrelevant in this article. We start by developing a SG model for a baseline cellular scenario, then prove that the coverage probability is independent of $\lambda$, contrary to popular belief.

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Coverage, Handoff and cost optimization for 5G Heterogeneous Network

Cited by 39 publications

References 17 publications

Coverage and rate analysis for 5G‐heterogeneous network: β‐Ginibre point process

Coverage and rate analysis for 5G‐heterogeneous network: β‐Ginibre point process

Cellular Coverage Probability Is Independent of Base Station Density under Stochastic Geometric Models

Cellular coverage probability is independent of base station density under stochastic geometric models

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