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Advanced MIMO Antenna Technologies for Intelligent Sensing Networks

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

Deadline for manuscript submissions: 31 March 2026 | Viewed by 603

Special Issue Editors


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Guest Editor
iTEAM Research Institute, Universitat Politècnica de València, Valencia, Spain
Interests: ISAC; massive MIMO; 6G system design
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Cyber Science and Technology, Beihang University, Beijing 100191, China
Interests: security of communication systems; broadband wireless ad hoc networks; UAV communication systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of sensing and communication is expected to play a central role in future wireless systems. Antenna technologies, in this context, are required not only to support data transmission but also to enable environmental awareness, localization, and imaging. This Special Issue is dedicated to research on Multiple-Input Multiple-Output (MIMO) antenna architectures addressing these combined requirements. Contributions may include work on the use of massive MIMO for target detection, as well as studies on fluid antennas that offer flexible beamforming in dynamic environments. Other topics of interest are methods for reducing signaling overhead in joint communication and sensing (JC&S) systems, solutions for radio-to-fiber interfaces supporting distributed antenna deployments, and signal processing approaches for data fusion. This Special Issue will provide a broad overview of current advances in hardware and algorithms for MIMO-based sensing networks, with potential applications in areas such as smart cities, autonomous systems, and industrial IoT.

Dr. Jose F. Monserrat
Prof. Dr. Lin Bai
Guest Editors

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Keywords

  • massive MIMO
  • fluid antennas
  • reduced signaling
  • radio-to-fiber interfaces
  • joint communication and sensing (JC&S)

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Published Papers (1 paper)

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Research

32 pages, 11810 KB  
Article
Butler-Matrix Beamspace Front-Ends for Massive MIMO: Architecture, Loss Budget, and Capacity Impact
by Felipe Vico, Jose F. Monserrat and Yiqun Ge
Sensors 2025, 25(23), 7170; https://doi.org/10.3390/s25237170 - 24 Nov 2025
Viewed by 445
Abstract
Massive Multiple-Input Multiple-Output (MIMO) systems with hundreds or thousands of antenna elements are fundamental to next-generation wireless networks, promising unprecedented spectral efficiency through spatial multiplexing and beamforming. However, the computational burden of channel state information (CSI) acquisition and processing scales dramatically with array [...] Read more.
Massive Multiple-Input Multiple-Output (MIMO) systems with hundreds or thousands of antenna elements are fundamental to next-generation wireless networks, promising unprecedented spectral efficiency through spatial multiplexing and beamforming. However, the computational burden of channel state information (CSI) acquisition and processing scales dramatically with array size, creating a critical bottleneck for practical deployments. While previous works demonstrated that Fast Fourier Transform (FFT)-based beamspace processing can exploit the inherent angular sparsity of wireless channels to compress CSI feedback, the digital implementation requires intensive computations that become prohibitive for ultra-large arrays. This paper presents an analog alternative using Butler matrices—passive beamforming networks that realize the Discrete Fourier Transform in hardware—combined with RF switching circuits to select only dominant angular components. We provide a comprehensive analysis of Butler matrix architectures for arrays up to 32 × 32 elements, characterizing insertion losses across different technologies (microstrip, substrate-integrated waveguide, and waveguide) and operating frequencies (10–30 GHz). The proposed system incorporates parallel power sensing with Winner-Take-All circuits for sub-microsecond beam selection, drastically reducing the number of active RF chains. Full-wave simulations and capacity evaluations at 12 and 30 GHz demonstrate that the Butler-based approach achieves comparable performance to FFT methods while offering significant advantages in power consumption and processing latency. For a 256 × 256 array, FFT computation requires 0.36 ms compared to near-instantaneous analog processing, making Butler matrices particularly attractive for real-time massive MIMO systems. These findings establish Butler matrix front-ends as a practical pathway toward scalable, energy-efficient beamspace processing in 6G networks. Full article
(This article belongs to the Special Issue Advanced MIMO Antenna Technologies for Intelligent Sensing Networks)
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