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Extremely Large-Scale MIMO Technologies for 6G Near-Field Communications

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

Deadline for manuscript submissions: 15 December 2025 | Viewed by 980

Special Issue Editors


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Guest Editor
School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China
Interests: 6G near-field communications; MIMO communication and signal processing

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Guest Editor
Department of Information and Communication Engineering, Hefei University of Technology, Hefei, China
Interests: XL-MIMO communications; millimetre wave/terahertz communications; machine learning

Special Issue Information

Dear Colleagues,

Extremely large-scale multiple-input and multiple-output (XL-MIMO) is recognized as one of the key physical-layer technologies for 6G mobile communication systems. XL antenna arrays, deploying hundreds or even thousands of antennas at the transceiver, can significantly enhance the key performance indicators (KPIs) of 6G systems. However, in such networks, near-field communication with spherical wavefronts becomes crucial, as conventional far-field propagation with planar wavefronts is no longer applicable. The utilization of spherical waves in the near-field region offers several advantages over traditional far-field communications. One of the primary benefits is that the wavefront in the radiating near-field region provides additional degrees of freedom and high resolution with distance-dependent beamwidth, which can be leveraged to improve wireless operations. Moreover, the spherical nature of the wavefront of the transmitted signal allows for more precise localization of the receiver based on the phase and amplitude of the received signal.  This Special Issue focuses on the latest research achievements from academia and industry and discusses related research directions for near-field XL-MIMO systems. The submissions can cover, but are not limited to, the following topics:

  • Channel measurement and channel modelling in near-field communication;
  • Electromagnetic information theory for near-field communication;
  • Channel estimation and channel tracking for near-field XL-MIMO systems;
  • Low-complexity beamforming design for near-field wireless communication;
  • Holographic MIMO/RIS for near-field operations;
  • Near-field simultaneous wireless information and power transfer (SWIPT);
  • Near-field and mmWave/THz communications, localization, and sensing;
  • Near-field integrated sensing and communications;
  • AI-assisted near-field

Dr. Haiyang Zhang
Dr. Wei Huang
Guest Editors

Manuscript Submission Information

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Keywords

  • MIMO
  • near-field communications
  • 6G mobile communication systems

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Published Papers (1 paper)

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Research

16 pages, 419 KiB  
Article
Energy-Efficient Resource Allocation for Near-Field MIMO Communication Networks
by Tong Lin, Jianyue Zhu, Junfan Zhu, Yaqin Xie, Yao Xu and Xiao Chen
Sensors 2025, 25(14), 4293; https://doi.org/10.3390/s25144293 - 10 Jul 2025
Viewed by 363
Abstract
With the rapid development of sixth-generation (6G) wireless networks and large-scale multiple-input multiple-output (MIMO) technology, the number of antennas deployed at base stations (BSs) has increased significantly, resulting in a high probability that users are in the near-field region. Note that it is [...] Read more.
With the rapid development of sixth-generation (6G) wireless networks and large-scale multiple-input multiple-output (MIMO) technology, the number of antennas deployed at base stations (BSs) has increased significantly, resulting in a high probability that users are in the near-field region. Note that it is difficult for the traditional far-field plane-wave model to meet the demand for high-precision beamforming in the near-field region. In this paper, we jointly optimize the power and the number of antennas to achieve the maximum energy efficiency for the users located in the near-field region. Particularly, this paper considers the resolution constraint in the formulated optimization problem, which is designed to guarantee that interference between users can be neglected. A low-complexity optimization algorithm is proposed to realize the joint optimization of power and antenna number. Specifically, the near-field resolution constraint is first simplified to a polynomial inequality using the Fresnel approximation. Then the fractional objective of maximizing energy efficiency is transformed into a convex optimization subproblem via the Dinkelbach algorithm, and the power allocation is solved for a fixed number of antennas. Finally, the number of antennas is integrally optimized with monotonicity analysis. The simulation results show that the proposed method can significantly improve the system energy efficiency and reduce the antenna overhead under different resolution thresholds, user angles, and distance configurations, which provides a practical reference for the design of green and low-carbon near-field communication systems. Full article
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