System-Level Assessment of Shaped Elevation Beam Patterns for Hybrid Beamforming in mm-Wave 5G Networks With Spatially Heterogeneous Traffic

Wenxu Chen, Yanki Aslan*, Remco Litjens, Alexander Yarovoy

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

23 Downloads (Pure)

Abstract

The throughput performance of intelligently shaped and fixed analog elevation beam patterns in millimeter-wave (mm-wave) base stations with hybrid beamforming (HBF) is assessed for the first time. Distinct spatially heterogeneous user distributions (i.e., uniform, near-site, cell-edge, and weighted uniform and near-site) and propagation environments (i.e., line-of-sight (LoS) with multipath and non-line-of-sight (NLoS) with multipath) are considered. The cosecant-squared and flat-top shaped beam patterns are compared to the benchmark pencil beam pattern with a straightforward electrical downtilt. The LoS simulation results show that in case of unknown weight of user distribution scenarios, the cosecant-squared pattern is the most robust, with a gain of up to 16% in the average system throughput and up to 34% in the 90th percentile user throughout compared to the benchmark. If the near-site case has a greater probability of occurrence than the uniform user distribution (e.g., due to daily events and festivals), the flat-top pattern becomes preferable. In the NLoS scenario, the considered HBF architectures with elevation beam pattern shaping do not bring any performance disadvantages compared to the benchmark HBF.

Original languageEnglish
Pages (from-to)125933-125943
Number of pages11
JournalIEEE Access
Volume13
DOIs
Publication statusPublished - 2025

Keywords

  • 5G
  • base station antennas
  • hybrid beamforming
  • millimeter-waves
  • phased arrays
  • throughput performance

Fingerprint

Dive into the research topics of 'System-Level Assessment of Shaped Elevation Beam Patterns for Hybrid Beamforming in mm-Wave 5G Networks With Spatially Heterogeneous Traffic'. Together they form a unique fingerprint.

Cite this