Wireless Communications and Mobile Computing

AI-Driven Wireless Energy Harvesting in Massive IoT for 5G and Beyond


Publishing date
01 Feb 2023
Status
Closed
Submission deadline
07 Oct 2022

1Autonomous University of Zacatecas, Zacatecas, Mexico

2University of Kragujevac, Kragujevac, Serbia

3University of Information Science and Technology "St. Paul The Apostle", Ohrid, Macedonia

This issue is now closed for submissions.

AI-Driven Wireless Energy Harvesting in Massive IoT for 5G and Beyond

This issue is now closed for submissions.

Description

Massively data-intensive applications provided by the Internet of Things (IoT) necessitate technological improvements and wireless communications evolution beyond fifth-generation (5G) networks. In recent years, wireless techniques such as multiple-input and multiple-output (MIMO) and beaming have been used extensively to explore the benefits of future networks. Also, the trend of massive IoT, artificial intelligence (AI) and cognitive computing are used to restrict the spectrum utilization capability of 5G and beyond.

The energy issue with mobile terminals has posed substantial obstacles to IoT adoption in recent years. Wireless energy harvesting (EH) and transfer technology can effectively address this issue. The battery life is prolonged by harvesting the energy for mobile terminals. The choice of energy harvesting technique is dependent upon the type of application required for any wireless communication application. Wireless power transfer (WPT) eliminates the need for batteries by sending the required energy remotely, while energy harvesting provides limitless energy by transforming ambient resources into usable electricity. In the future, disposable batteries will likely be modified to rechargeable batteries using energy harvesting techniques. Wireless energy efficient (WEH) techniques are also critical to achieving battery-less operations in the near future. The future networks require intelligent sensing techniques to achieve accurate data modeling and analysis for 5G and beyond networks. Through AI and computing, future networks can achieve an optimized resource scheduling mechanism, senseless and immersive interaction and visualization. AI techniques could solve the challenges related to reliability and latency in wireless communications emerging from 5G networks, as a major bottleneck in practical deployments for 5G and beyond networks has been limited-capacity batteries running out of charge.

The aim of this Special Issue is to propose viable options to address these challenges, including EH, WPT, and energy-efficient/low-power communication. We encourage researchers to present their latest work on massive IoT and AI work together to address the energy and power transfer challenges of 5G and beyond networks using AI and computing techniques. Original research and review articles are welcomed.

Potential topics include but are not limited to the following:

  • Energy harvesting models based on machine learning
  • Energy harvesting techniques for extending battery life
  • Smart sensing and energy trade-offs in massive IoT
  • Network design with harvesting properties for 5G and beyond
  • Energy-autonomous massive IoT networks
  • Wireless-powered communications 5G and beyond
  • Optimal wireless energy transmission and harvesting control
  • Machine-to-machine (M2M) and device-to-device (D2D) communications via wireless power
  • AI-driven theory and WEH methods for 5G and beyond
  • Intelligent energy-efficient network architectures
  • Challenges and Solutions of WPT in massive IoT

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Wireless Communications and Mobile Computing
Wireless Communications and Mobile Computing
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