Modeling and Analyzing Millimeter Wave Cellular Systems

TL;DR

This paper reviews mathematical models and analytical techniques for millimeter wave cellular systems, highlighting their unique physical challenges, and provides a stochastic geometry-based approach to evaluate system performance and implications.

Contribution

It introduces a baseline analytical framework for mmWave systems considering blockage and directionality, and discusses key system behaviors and future research directions.

Findings

mmWave systems are more noise-limited than Sub-6GHz systems

initial access in mmWave is more challenging

spectrum sharing can benefit operators despite interference

Abstract

We provide a comprehensive overview of mathematical models and analytical techniques for millimeter wave (mmWave) cellular systems. The two fundamental physical differences from conventional Sub-6GHz cellular systems are (i) vulnerability to blocking, and (ii) the need for significant directionality at the transmitter and/or receiver, which is achieved through the use of large antenna arrays of small individual elements. We overview and compare models for both of these factors, and present a baseline analytical approach based on stochastic geometry that allows the computation of the statistical distributions of the downlink signal-to-interference-plus-noise ratio (SINR) and also the per link data rate, which depends on the SINR as well as the average load. There are many implications of the models and analysis: (a) mmWave systems are significantly more noise-limited than at Sub-6GHz for most parameter configurations; (b) initial access is much more difficult in mmWave; (c) self-backhauling is more viable than in Sub-6GHz systems which makes ultra-dense deployments more viable, but this leads to increasingly interference-limited behavior; and (d) in sharp contrast to Sub-6GHz systems cellular operators can mutually benefit by sharing their spectrum licenses despite the uncontrolled interference that results from doing so. We conclude by outlining several important extensions of the baseline model, many of which are promising avenues for future research.