[PDF][PDF] Investigation of 5G Wireless Communication with Dust and Sand Storms.

ZS Hammed, SY Ameen, SRM Zeebaree - J. Commun., 2023 - researchgate.net
The demands for higher throughput, data rate, low latency, and capacity in 5G
communication systems prompt the use of millimeter-wave frequencies that range from 3 …

Machine learning based time domain millimeter-wave beam prediction for 5G-advanced and beyond: design, analysis, and over-the-air experiments

Q Li, P Sisk, A Kannan, T Yoo, T Luo… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) or machine learning (ML) based beam prediction is currently
studied in the 3rd Generation Partnership Project (3GPP) fifth generation (5G)-Advanced …

Empirical blockage characterization and detection in indoor sub-THz communications

A Shurakov, D Moltchanov, A Prikhodko… - Computer …, 2023 - Elsevier
The next step in the last mile wireless access is utilization of the terahertz (THz) frequency
band spanning from 0.1 to 3 THz, specifically, its lower part (up to 300 GHz) also known as …

Beam Foreseeing in Millimeter-Wave Systems with Situational Awareness: Fundamental Limits via Cramér-Rao Lower Bound

WT Shih, CK Wen, SH Tsai, S Jin… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Millimeter-wave (mmWave) networks offer the potential for high-speed data transfer and
precise localization, leveraging large antenna arrays and extensive bandwidths. However …

Predicting Channel Delay State Information in 5GTSN Systems Using Extreme Learning Machine Auto-Encoder (ELM-AE) Model Based on Intelligent Deep Extreme …

C Zhang, J Wang, M Fu - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
This paper investigates the joint scheduling of cross-channel traffic resources in 5G-Time-
Sensitive Networks (TSN) and proposes an adaptive prediction method suitable for cross …

Early warning of mmWave signal blockage using diffraction properties and machine learning

AF Dizche, A Duel-Hallen… - IEEE Communications …, 2022 - ieeexplore.ieee.org
Sensitivity to blockage challenges performance of millimeter-wave (mmWave)
communication systems. We apply the MiniRocket machine learning (ML) method to provide …

Deep Learning-Based Beam Pair Prediction With Finite Beam Quality Information

S Wang, W Chen, X Chen, Y Zhang… - 2023 IEEE 23rd …, 2023 - ieeexplore.ieee.org
With the development of 5G/B5G wireless communication technology, millimeter wave is the
key to achieve ultra-high data transmission rate, and beam management is an effective …

Enhancing Reliability in Federated mmWave Networks: A Practical and Scalable Solution using Radar-Aided Dynamic Blockage Recognition

M Al-Quraan, A Zoha, A Centeno… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
This article introduces a new method to improve the dependability of millimeter-wave
(mmWave) and terahertz (THz) network services in dynamic outdoor environments. In these …

Spectral-Based Proactive Blockage Detection for Sub-THz Communications

F Zhinuk, A Gaydamaka, D Moltchanov… - IEEE …, 2024 - ieeexplore.ieee.org
Human body blockage is one of the main reasons prohibiting the adoption of modern
millimeter wave (mmWave, 30-70 GHz) and future sub-terahertz (sub-THz, 100-300 GHz) …

User-side proactive blockage prediction and fast beam switching in 5G NR systems

H Xie, H Wang - … IEEE 33rd Annual International Symposium on …, 2022 - ieeexplore.ieee.org
Beam management under blockage has been challenging for millimeter wave
communication relying on directional links. The baseline beam management protocols in 5G …