Next-Generation 6G Wireless Networks: Challenges and Opportunities in Terahertz (THz) Communication and AI-Driven Signal Processing

The advent of 6G wireless networks promises to revolutionize communication by leveraging terahertz (THz) frequencies (0.1–10 THz) and artificial intelligence (AI) to achieve terabit-per-second (Tbps) speeds, ultra-low latency, and ubiquitous connectivity. However, THz communication faces critical challenges, including severe propagation losses, molecular absorption, and hardware limitations, which demand innovative solutions. This paper explores the synergistic role of AI-driven signal processing in overcoming these barriers, focusing on adaptive beamforming, channel estimation, and resource allocation. We present a comprehensive survey of THz channel characteristics and analyze state-of-the-art AI techniques—such as deep reinforcement learning (DRL) for beam alignment and federated learning for distributed optimization—that enhance the efficiency and reliability of THz networks. Furthermore, we identify open research challenges, including energy-efficient AI deployment, security vulnerabilities, and standardization gaps. By bridging theoretical models with practical implementations, this work provides a roadmap for realizing 6G’s potential, emphasizing the need for interdisciplinary collaboration across wireless engineering, AI, and materials science. Our findings underscore AI as a pivotal enabler for scalable and intelligent THz-based 6G networks, while highlighting future directions for industry and academia.

Authors

Hamzah Abdullah Faraj

Published

Apr 30, 2025

Journal or venue

International Journal for Research in Applied Science and Engineering Technology

DOI

10.22214/ijraset.2025.69864

Paper type

journal article

Source

Crossref