Stochastic Geometry-Based Modeling and Analysis of Beam Management in 5G

TL;DR

This paper develops a stochastic geometry model to analyze beam management in 5G networks, balancing spectral efficiency gains against overhead costs across different frequency bands.

Contribution

It introduces a comprehensive system-level model for beam management in 5G, providing analytical tools to optimize the number of beams per cell considering various network scenarios.

Findings

Optimal number of beams varies with network scenario.

Millimeter wave and sub-6 GHz deployments show different trade-offs.

Analytical expression for effective area spectral efficiency.

Abstract

Beam management is central in the operation of dense 5G cellular networks. Focusing the energy radiated to mobile terminals (MTs) by increasing the number of beams per cell increases signal power and decreases interference, and has hence the potential to bring major improvements on area spectral efficiency (ASE). This benefit, however, comes with unavoidable overheads that increase with the number of beams and the MT speed. This paper proposes a first system-level stochastic geometry model encompassing major aspects of the beam management problem: frequencies, antennas, and propagation; physical layer, wireless links, and coding; network geometry, interference, and resource sharing; sensing, signaling, and mobility management. This model leads to a simple analytical expression for the effective ASE that the typical user gets in this context. This in turn allows one to find, for a wide variety of 5G network scenarios including millimeter wave (mmWave) and sub-6 GHz, the number of beams per cell that offers the best global trade-off between these benefits and costs. We finally provide numerical results that discuss the effects of different systemic trade-offs and performances of mmWave and sub-6 GHz 5G deployments.