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6G Empowered IoT Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 2159

Special Issue Editor

School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: scheduling of mobile edge computing; design and optimization of next-generation wireless networks; Internet of Things

Special Issue Information

Dear Colleagues,

Along with the commercial adoption of 5G cellular technology that profoundly changes the world’s communications landscape, 6G, as the successor to 5G, has emerged on the horizon and attracted widespread attention. 6G is expected to substantially improve communication capacity, dramatically reduce costs, enable micro-second latency, and harness trillions of connected IoT devices. While there is already much investigation on 6G-enabled IoT networks, some key issues and fundamental questions are still largely unexplored—for instance, how to incorporate artificial intelligence into power-constrained sensor networks to manage pervasive sensing, handle data processing, and schedule 6G resources. Moreover, for large-scale distributed and highly mobile IoT devices, the way to achieve 6G resilient coverage and terabit transmission remains a critical challenge. To fill these technical gaps, this Special Issue solicits the latest works, insights, and perspectives on the area of 6G empowered IoT networks and applications.

Dr. Ke Zhang
Guest Editor

Manuscript Submission Information

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Keywords

  • Intelligent sensing and communication for 6G IoT networks
  • AI-driven resource management for 6G IoT networks
  • Edge intelligence for 6G IoT networks
  • Green 6G IoT networks
  • 6G-enabled new IoT applications
  • Case studies and implementations for 6G IoT applications

Published Papers (1 paper)

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Research

19 pages, 437 KiB  
Article
Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
by Bowen Cai, Qianqian Zhang, Jungang Ge and Weiliang Xie
Sensors 2023, 23(8), 3875; https://doi.org/10.3390/s23083875 - 11 Apr 2023
Cited by 3 | Viewed by 1682
Abstract
Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of [...] Read more.
Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designing satellites, it is difficult to launch a dedicated satellite for IoT communications. To facilitate IoT communications over LEO SatCom, in this paper, we propose the cognitive LEO satellite system, where the IoT users act as the secondary user to access the legacy LEO satellites and cognitively use the spectrum of the legacy LEO users. Due to the flexibility of code division multiple access (CDMA) in multiple access and the wide use of CDMA in LEO SatCom, we apply CDMA to support cognitive satellite IoT communications. For the cognitive LEO satellite system, we are interested in the achievable rate analysis and resource allocation. Specifically, considering the randomness of spreading codes, we use the random matrix theory to analyze the asymptotic signal-to-interference-plus-noise ratios (SINRs) and accordingly obtain the achievable rates for both legacy and IoT systems. The power of the legacy and IoT transmissions at the receiver are jointly allocated to maximize the sum rate of the IoT transmission subject to the legacy satellite system performance requirement and the maximum received power constraints. We prove that the sum rate of the IoT users is quasi-concave over the satellite terminal receive power, based on which the optimal receive powers for these two systems are derived. Finally, the resource allocation scheme proposed in this paper has been verified by extensive simulations. Full article
(This article belongs to the Special Issue 6G Empowered IoT Networks)
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