Efficient Approximation of SINR and Throughput in 5G NR via Sparsity and Interference Aggregation

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

This paper presents a novel approach to scheduling resources in a multi-beam next-generation Node B (gNB) that enables efficient resource reuse across beams within a transmission time interval (TTI). Unlike traditional medium access control (MAC) scheduling, which focuses on resource allocation within a single beam, our approach considers the simultaneous scheduling of multiple beams. We leverage a recently introduced sparse model and propose an algorithm that avoids exhaustive Monte Carlo (MC) simulation while approximating signal-to-interference-plus-noise ratio (SINR) and achievable throughput parameters in snapshot-based simulations. This approximation significantly reduces computational complexity while maintaining negligible error. We validate our approach through extensive simulations, demonstrating its effectiveness in approximating SINR and achievable throughput.

Details

OriginalspracheEnglisch
Titel2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
Herausgeber (Verlag)IEEE
Seiten1-7
Seitenumfang7
ISBN (elektronisch)9781665464833
ISBN (Print)978-1-6654-6484-0
PublikationsstatusVeröffentlicht - 8 Sept. 2023
Peer-Review-StatusJa

Konferenz

Titel2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications
KurztitelPIMRC 2023
Veranstaltungsnummer34
Dauer5 - 8 September 2023
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtThe Westin Harbour Castle
StadtToronto
LandKanada

Externe IDs

Scopus 85174984897

Schlagworte

Schlagwörter

  • 5G mobile communication, Approximation algorithms, Interference, Monte Carlo methods, Processor scheduling, Radio frequency, Throughput