Spatio-Temporal Analysis of SINR Meta Distribution for mmWave Heterogeneous Networks Under Geo/G/1 Queues

TL;DR

This paper provides a detailed spatio-temporal analysis of SINR meta distribution in mmWave heterogeneous networks, incorporating stochastic geometry, queueing theory, and mmWave-specific characteristics to evaluate network performance.

Contribution

It introduces a novel framework combining stochastic geometry and queueing theory to analyze SINR meta distribution in mmWave HetNets with temporal traffic dynamics.

Findings

Higher SINR thresholds reduce successful transmission probability.

Blockage parameters significantly affect network performance.

Recursive method efficiently computes the SINR meta distribution.

Abstract

A fine-grained analysis of network performance is crucial for system design. In this paper, we focus on the meta distribution of the signal-to-interference-plus-noise-ratio (SINR) in the mmWave heterogeneous networks where the base stations (BS) in each tier are modeled as a Poisson point process (PPP). By utilizing stochastic geometry and queueing theory, we characterize the spatial and temporal randomness while the special characteristics of mmWave communications, including different path loss laws for line-of-sight and non-line-of-sight links and directional beamforming, are incorporated into the analysis. We derive the moments of the conditional successful transmission probability (STP). By taking the temporal random arrival of traffic into consideration, an equation is formulated to derive the meta distribution and the meta distribution can be obtained in a recursive manner. The numerical results reveal the impact of the key network parameters, such as the SINR threshold and the blockage parameter, on the network performance.