Beamforming Based on a SSS Angle Estimation Algorithm for 5G NR Networks

Author:

Andrade Daniel12,Magueta Roberto2,Silva Adão1ORCID,Marques Paulo23

Affiliation:

1. Instituto de Telecomunicações (IT) and Departamento de Eletrónica, Telecomunicações e Informática (DETI), University of Aveiro, 3810-193 Aveiro, Portugal

2. Allbesmart LDA, Avenida do Empresário, Centro de Empresas Inovadoras 1, 6000-767 Castelo Branco, Portugal

3. Instituto Politécnico de Castelo Branco (IPCB), Avenida Pedro Álvares Cabral 12, 6000-084 Castelo Branco, Portugal

Abstract

The current 5G-NR standard includes the transmission of multiple synchronization signal blocks (SSBs) in different directions to be exploited in beamforming techniques. However, choosing a pair of these beams leads to performance degradation, mainly for the cases where the transmit and receive beams are not aligned, because it considers that only few fixed directions among wide beams are established. Therefore, in this article, we design a new 3GPP-standard- compliant beam pair selection algorithm based on secondary synchronization signal (SSS) angle estimation (BSAE) that makes use of multiple synchronization signal blocks (SSBs) to maximize the reference signal received power (RSRP) value at the receiver. This optimization is performed using the SSSs present in each SSB to perform channel estimation in the digital domain. Afterwards, the combination of those estimations is used to perform equivalent channel propagation matrix estimation without the analog processing effects. Finally, through the estimated channel propagation matrix, the angle that maximizes the RSRP is determined to compute the most suitable beam. The proposed algorithm was evaluated and compared with a conventional beam pair selection algorithm. Ours has better performance results. Furthermore, the proposed algorithm achieved performance close to the optimal performance, where all channel state information (CSI) is available, emphasizing the interest of the proposed approach for practical 5G mmWave mMIMO implementations.

Funder

FCT/MCTES

Fundo Europeu de Desenvolvimento Regional

Publisher

MDPI AG

Subject

Computer Networks and Communications

Reference33 articles.

1. 3GPP (2022, December 08). TR 22.861: Massive Internet of Things; v14.1.0. Tech. Spec. 2016. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3013.

2. A Comprehensive Survey on Interneet of Things (IoT) Toward 5G Wireless Systems;Chettri;IEEE Internet Things J.,2020

3. Mobile network architecture evolution toward 5G;Rost;IEEE Commun. Mag.,2016

4. ITU-R (2022, December 08). Detailed specifications of the terrestrial radio interfaces of International Mobile Tellecomunications-2020 (IMT-2020). Recommendation ITU-R M.2150-1, February 2022. Available online: https://www.itu.int/dms_pubrec/itu-r/rec/m/R-REC-M.2150-1-202202-I!!PDF-E.pdf.

5. ITU-R (2022, December 08). IMT Vision- Framework and overall objectives of the future development of IMT for 2020 and beyond. M Series 2083-0, September 2015. Available online: https://www.itu.int/dms_pubrec/itu-r/rec/m/R-REC-M.2083-0-201509-I!!PDF-E.pdf.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3