Intelligent Transmission Control Scheme for 5G mmWave Networks Employing Hybrid Beamforming

Hazem (Moh’d Said) Hatamleh (), As’ad Mahmoud As’ad Alnaser, Roba Mahmoud Ali Aloglah, Tomader Jamil Bani Ata, Awad Mohamed Ramadan and Omar Radhi Aqeel Alzoubi
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Hazem (Moh’d Said) Hatamleh: Applied Science Department, Al-Balqa Applied University, Ajloun 26816, Jordan
As’ad Mahmoud As’ad Alnaser: Applied Science Department, Al-Balqa Applied University, Ajloun 26816, Jordan
Roba Mahmoud Ali Aloglah: Management Information Science Department, Al-Balqa Applied University, Amman 11910, Jordan
Tomader Jamil Bani Ata: Management Information Science Department, Al-Balqa Applied University, Amman 11910, Jordan
Awad Mohamed Ramadan: Computing Department, College of Engineering and Computing in Al-Qunfudah, Umm Al-Qura University, Makkah 21955, Saudi Arabia
Omar Radhi Aqeel Alzoubi: Computing Department, College of Engineering and Computing in Al-Qunfudah, Umm Al-Qura University, Makkah 21955, Saudi Arabia

Future Internet, 2025, vol. 17, issue 7, 1-35

Abstract: Hybrid beamforming plays a critical role in evaluating wireless communication technology, particularly for millimeter-wave (mmWave) multiple-input multiple-out (MIMO) communication. Several hybrid beamforming systems are investigated for millimeter-wave multiple-input multiple-output (MIMO) communication. The deployment of huge grant-free transmission in the millimeter-wave (mmWave) band is required due to the growing demands for spectrum resources in upcoming enormous machine-type communication applications. Ultra-high data speed, reduced latency, and improved connection are all promised by the development of 5G mmWave networks. Yet, due to severe route loss and directional communication requirements, there are substantial obstacles to transmission reliability and energy efficiency. To address this limitation in this research we present an intelligent transmission control scheme tailored to 5G mmWave networks. Transport control protocol (TCP) performance over mmWave links can be enhanced for network protocols by utilizing the mmWave scalable (mmS)-TCP. To ensure that users have the stronger average power, we suggest a novel method called row compression two-stage learning-based accurate multi-path processing network with received signal strength indicator-based association strategy (RCTS-AMP-RSSI-AS) for an estimate of both the direct and indirect channels. To change user scenarios and maintain effective communication constantly, we utilize the innovative method known as multi-user scenario-based MATD3 (Mu-MATD3). To improve performance, we introduce the novel method of “digital and analog beam training with long-short term memory (DAH-BT-LSTM)”. Finally, as optimizing network performance requires bottleneck-aware congestion reduction, the low-latency congestion control schemes (LLCCS) are proposed. The overall proposed method improves the performance of 5G mmWave networks.

Keywords: digital and analog beam training with long-short term memory (DAH-BT-LSTM); low-latency congestion control schemes (LLCCS); 5G mmWave; hybrid beamforming (HB) (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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