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Applications of Wireless Communication Network Based on MIMO in Sensors

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

Deadline for manuscript submissions: closed (28 February 2026) | Viewed by 1246

Special Issue Editors


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Guest Editor
College of Information and Communication Engineering Harbin Engineering University Harbin, Harbin 150001, China
Interests: wireless energy harvesting communications; intelligent computing; software radio; radio signal recognition and classification; cognitive radio; LTE-Unlicensed; HetNets in 5G; communication theory and image processing; and massive MIMO

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Guest Editor
Research Assistant, North Automatic Control Technology Institute, Taiyuan 030006, China
Interests: wireless communication; massive MIMO; physical layer security; resource management; intelligent computing; network slicing; intelligent reflecting surface; 6G communication technologies

Special Issue Information

Dear Colleagues,

The digital landscape has been significantly shaped by the evolution of wireless communication networks. Multiple-input multiple-output (MIMO) technology has emerged as a pivotal innovation to enhance data transmission rates and communication quality through multiple antennas at both the transmitter and receiver ends, which is regarded as a cornerstone of next-generation wireless communication systems. Sensors, the eyes and ears of the digital world, collect and transmit data critical for various applications ranging from environmental monitoring to industrial automation. Integrating MIMO technology into these sensor networks allows for a significant increase in the volume of data that can be processed, the speed at which it can be transmitted, and the resilience against interference and noise. This leads to the enablement of more complex applications, enhanced decision-making, and increased automation.

This Special Issue is dedicated to exploring the cutting-edge applications of MIMO in sensor-based wireless communication networks, focusing on real-world implementations, theoretical advancements, and the future of wireless sensor technology. By bringing together a diverse array of research, we hope to foster interdisciplinary collaboration and inspire innovative solutions in MIMO and sensors that will drive the advancements in wireless communication technology.

Dr. Hongyuan Gao
Dr. Yumeng Su
Guest Editors

Manuscript Submission Information

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Keywords

  • MIMO technology
  • wireless communication networks
  • sensor networks
  • data transmission
  • signal processing
  • resource allocation and scheduling
  • reliability and robustness
  • secure communication mechanisms
  • environmental monitoring
  • advanced wireless applications

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Published Papers (1 paper)

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Research

23 pages, 677 KB  
Article
Hierarchical MAB Framework for Energy-Aware Beam Training for Near-Field Communications
by Yunxing Xiang, Yi Yan, Yunchao Song, Jing Gao, Xiaohui You, Jun Wang, Huibin Liang and Yixin Jiang
Sensors 2026, 26(1), 60; https://doi.org/10.3390/s26010060 - 21 Dec 2025
Viewed by 592
Abstract
For XL-MIMO multi-user frequency division duplex systems, this paper proposes a near-field beam training scheme using a two-phase combinatorial multi-armed bandit (MAB) framework. This scheme leverages the MAB framework, integrating energy-aware user scheduling and hierarchical beam training to balance communication quality and device [...] Read more.
For XL-MIMO multi-user frequency division duplex systems, this paper proposes a near-field beam training scheme using a two-phase combinatorial multi-armed bandit (MAB) framework. This scheme leverages the MAB framework, integrating energy-aware user scheduling and hierarchical beam training to balance communication quality and device battery level, thereby effectively enhancing system energy efficiency and extending the device’s lifespan. Specifically, in the first phase, we account for user battery levels by designing an energy-aware upper confidence bound (UCB) algorithm for user scheduling. This algorithm effectively balances exploration and exploitation, prioritizing users with higher achievable rates and sufficient battery level. In the second phase, based on the scheduled users, two UCB algorithms are employed for beam training. In the first layer, discrete Fourier transform codebook-based beam scanning is utilized, and a UCB algorithm is applied to initially acquire angle information for scheduled users. In the second layer, based on the obtained angle information, a candidate set of polar-domain codewords is constructed. Another UCB algorithm is then employed to select the optimal polar-domain codewords. The effectiveness of our scheme is confirmed by simulations, demonstrating notable achievable rate gains for multi-user communications. Full article
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