4.7 Article

Beam Management in 5G: A Stochastic Geometry Analysis

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 21, Issue 4, Pages 2275-2290

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2021.3110785

Keywords

Handover; 5G mobile communication; Geometry; Switches; Measurement; Interference; Stochastic processes; 5G NR; beam management; handover; interference; Poisson point process; stochastic geometry

Funding

  1. European Research Council (ERC) under the European Union [788851]

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This paper proposes a system-level model for beam management in 5G networks, which aims to increase signal power and decrease interference by increasing the number of beams. The model provides insights into the optimal number of beams that maximize the area spectral efficiency, considering tradeoffs between beamforming gains and management costs. Numerical results demonstrate the performance optimizations of mmWave and sub-6 GHz deployments under different systemic tradeoffs.
Beam management is central in the operation of beamformed wireless cellular systems such as 5G New Radio (NR) 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 paper proposes a first system-level stochastic geometry model encompassing major aspects of the beam management problem: frequencies, antenna configurations, 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 rate that the typical user gets in this context. This in turn allows one to find the number of beams per cell and per MT that maximizes the effective ASE by offering the best tradeoff between beamforming gains and beam management operational overheads and costs, for a wide variety of 5G network scenarios including millimeter wave (mmWave) and sub-6 GHz. As part of the system-level analysis, we define and analyze several underlying new and fundamental performance metrics that are of independent interest. The numerical results discuss the effects of different systemic tradeoffs and performance optimizations of mmWave and sub-6 GHz 5G deployments.

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