Scholarlink

<p>5G wireless networks have paved the way for intelligent, reliable communication networks with extremely high data rates, ultra-low latency, and highly reliable connectivity. With 6G wireless networks expected to offer up to 1 Tbps data rates with near-zero latency, wireless communication networks are expected to get smarter than ever. As a result, ultra-fast intelligent wireless networks are expected to power the hyper-connected intelligent world of tomorrow. Towards this direction, this paper provides a comprehensive overview of how machine learning (ML) techniques can be employed in Wireless Sensor Networks (WSNs) and Internet of Things (IoT) networks over futuristic 6G wireless networks. Machine learning would enable 6G-enabled IoT/WSNs to operate autonomously, detect anomalies, optimize energy use, and respond to real-time data they sense and collect. Enabling technologies such as edge Artificial Intelligence (AI), satellite-assisted 6G, Intelligent Reflecting Surfaces (IRS), and terahertz communications are discussed. Furthermore, a novel architecture employing federated and distributed learning for IoT communication is presented to demonstrate low-latency, energy-efficient, and secure communication for distributed ML tasks. Results indicate the superiority of the proposed architecture over contemporary 5G-based architectures in terms of network intelligence, latency, and reliability. Finally, the paper discusses major challenges and future directions for realizing the promise of 6G for ML-powered IoT and WSNs.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An ML-augmented framework for WSN and IoT in 6G networks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月3日

查看全文
  • Gulista Khan,
  • Wajid Ali,
  • Gopal Kumar Gupta,
  • Kamal Kumar Gola

摘要

5G wireless networks have paved the way for intelligent, reliable communication networks with extremely high data rates, ultra-low latency, and highly reliable connectivity. With 6G wireless networks expected to offer up to 1 Tbps data rates with near-zero latency, wireless communication networks are expected to get smarter than ever. As a result, ultra-fast intelligent wireless networks are expected to power the hyper-connected intelligent world of tomorrow. Towards this direction, this paper provides a comprehensive overview of how machine learning (ML) techniques can be employed in Wireless Sensor Networks (WSNs) and Internet of Things (IoT) networks over futuristic 6G wireless networks. Machine learning would enable 6G-enabled IoT/WSNs to operate autonomously, detect anomalies, optimize energy use, and respond to real-time data they sense and collect. Enabling technologies such as edge Artificial Intelligence (AI), satellite-assisted 6G, Intelligent Reflecting Surfaces (IRS), and terahertz communications are discussed. Furthermore, a novel architecture employing federated and distributed learning for IoT communication is presented to demonstrate low-latency, energy-efficient, and secure communication for distributed ML tasks. Results indicate the superiority of the proposed architecture over contemporary 5G-based architectures in terms of network intelligence, latency, and reliability. Finally, the paper discusses major challenges and future directions for realizing the promise of 6G for ML-powered IoT and WSNs.