Load Balancing Potentials in 5G NR FR2

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

With the use of millimeter waves (mmWaves) in high carrier frequencies, massive bandwidth is available in the fifth-generation (5G) of cellular networks and upcoming 6G. However, at such high frequencies, the radio propagation suffers from higher free space path loss, which is compensated by the use of beamforming at the transmitter and the receiver sides. With a high number of beams at the base station, the user equipment (UE) has multiple candidate serving cells to connect to, which in turn offers new opportunities to achieve high load balancing gains. In this paper we introduce an optimal load balancing approach with respect to conventional initial access (IA) based on maximum reference signal received power (RSRP). It is followed by simulation for urban micro (UMi) hexagonal scenario with multi-beam at next generation node base station (gNB). It is shown that on average 8.5% gain, not to mention over 40% gain for some realizations, is achievable for New Radio (NR) (single radio frequency (RF)-chain) while this gain is on average less than 0.4% for Long-Term Evolution (LTE).

Details

Original languageEnglish
Title of host publication2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
PublisherIEEE
Pages1393-1399
Number of pages7
ISBN (electronic)9781665480536
ISBN (print)978-1-6654-8054-3
Publication statusPublished - 15 Sept 2022
Peer-reviewedYes

Conference

Title2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
Duration12 - 15 September 2022
LocationKyoto, Japan

External IDs

Scopus 85145662735

Keywords

ASJC Scopus subject areas

Keywords

  • Array signal processing, Base stations, Load management, Radio propagation, Radio transmitters, Receivers, Simulation, load balancing, New Radio (NR), fifth-generation (5G), scheduler, multi-beam, optimization