Meta Distribution of the SINR for mmWave Cellular Networks With Clusters

Shi, Minwei; Gao, Xiaozheng; Yang, Kai; Niyato, Dusit; Han, Zhu

doi:10.1109/tcomm.2021.3092771

Cited by 13 publications

(3 citation statements)

References 38 publications

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“…Note that due to the incorporation of multi-tier interference, the standard beta approximation is less accurate in the regime of small reliability and SINR threshold. In this case, the approximations with higher degrees of freedom will help to close the gap [21], [23]. In general, we observe that adopting the exact OBA distribution leads to accurate SINR coverage probability M 1 (γ) and SINR MD FP(γ) (x) for aerial networks, while the uniform OBA assumption underestimates both metrics.…”

Section: A Validationmentioning

confidence: 81%

“…To address this concern, the authors in [17] establish a framework to evaluate the meta distribution (MD) of signal-to-interference ratio (SIR) in Poisson bipolar and cellular networks, which quantifies the fraction of links that achieve the target SIR threshold above a required reliability level. Inspired by its sharpness, the metric of MD is widely analyzed in terrestrial networks [19]- [23]. However, only little literature has investigated this metric in aerial networks except [3], [24], where the MDs of signal-to-noise ratio (SNR) and SIR are evaluated in a singletier UAV network with Rayleigh fading.…”

Section: Introductionmentioning

confidence: 99%

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The Meta Distribution of SINR in UAV-Assisted Cellular Networks

Shi¹,

Yang²,

Niyato³

et al. 2023

Preprint

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Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a costeffective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic lineof-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when

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Section: A Validationmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

The Meta Distribution of SINR in UAV-Assisted Cellular Networks

Shi¹,

Yang²,

Niyato³

et al. 2023

Preprint

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show abstract

“…Therefore, the distance distributions, as well as system model, are way more complicated than downlink scenarios. While we only compute the SINR meta distribution in the downlink in this paper, uplink analysis, as well as some more complex system models, such as cluster distributed BSs [26] and [47], can be an interesting future research direction.…”

Section: Discussionmentioning

confidence: 99%

A Dominant Interferer Plus Mean Field-Based Approximation for SINR Meta Distribution in Wireless Networks

Qin

Kishk

Alouini

2023

IEEE Trans. Commun.

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This paper proposes a novel approach for computing the meta distribution of the signal-to-interferenceplus-noise ratio (SINR) for the downlink transmission in a wireless network with Rayleigh fading.The novel approach relies on an approximation mix of exact and mean-field analysis of interference (dominant interferer-based approximation) to reduce the complexity of analysis and enhance tractability.In particular, the proposed approximation omits the need to compute the first or the second moment of the SINR that is used in the beta approximation typically adopted in the literature but requires of computing the joint distance distributions. We first derive the proposed approximation based on a Poisson point process (PPP) network with a standard path-loss and Rayleigh fading and then illustrate its accuracy and operability in another four widely used point processes: Poisson bipolar network, Matérn cluster process (MCP), K-tier PPP and Poisson line Cox process (PLCP). Specifically, we obtain the SINR meta distribution for PLCP networks for the first time. Even though the proposed approximation looks simple but it shows good matching in comparison to the popular beta approximation as well as the Monte-Carlo simulations, which opens the door to adopting this approximation in more advanced network architectures.

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