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Electronics
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Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects
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Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 6214

Special Issue Editors

Dr. Jiakang Zheng

E-Mail Website
Guest Editor
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
Interests: cell-free massive MIMO; mobile communications; performance analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Yuanbin Chen

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
Interests: holographic MIMO; XL-MIMO; RIS; signal processing
Special Issues, Collections and Topics in MDPI journals
Dr. Weicong Chen

E-Mail Website
Guest Editor
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
Interests: millimeter-wave wireless communications; massive MIMO; reconfigurable intelligent surface
Dr. Yijing Lin

E-Mail Website
Guest Editor
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: federated unlearning; blockchain; data governance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As 6G approaches, MIMO technology is advancing toward the realization of ubiquitous coverage, ultra-high capacity, and intelligent adaptability. This Special Issue focuses on advanced MIMO technologies from three innovative perspectives: network architecture, the antenna scale, and antenna hardware. From a network architecture perspective, cell-free massive MIMO (CF-mMIMO) distributes access points across wide areas to provide ubiquitous service without traditional cell boundaries. At the antenna-scale level, two prominent trends are observed: extremely large-scale MIMO (XL-MIMO), characterized by an increasing number of antenna elements, and holographic MIMO (HMIMO), featuring a denser arrangement of antenna elements. Both paradigms may exhibit pronounced spatial non-stationarity in the near field, in which the electromagnetic information theory can be harnessed to characterize their capabilities in manipulating the radio environment. Meanwhile, innovations in antenna hardware, including fluid/movable antennas and reconfigurable intelligent surfaces (RISs), are enabling wireless systems to actively adapt to and even customize evolving environments, improving flexibility and robustness. Despite significant progress, key challenges remain, including the following: accurate system modeling under real-world conditions, innovative signal processing for advanced MIMO technologies, and intelligent resource allocation by AI-driven methods. This Special Issue invites contributions that address these challenges and advance the practical implementation of next-generation MIMO systems.

Both original research articles and reviews are welcome. Topics include (but are not limited to) the following:

  • CF-mMIMO/XL-MIMO/HMIMO/RIS system design, algorithms, and deployment strategies;
  • Fluid/movable antenna- and RIS-empowered CF-mMIMO/XL-MIMO/HMIMO;
  • Performance analysis of CF-mMIMO/XL-MIMO/HMIMO/RIS under real-world conditions;
  • Advanced signal processing for CF-mMIMO/XL-MIMO/HMIMO/RIS;
  • Intelligent resource allocation for CF-mMIMO/XL-MIMO/HMIMO/RIS by AI-driven methods;
  • Joint optimization of advanced MIMO in terms of network architecture, antenna scale, and hardware.

We look forward to receiving your contributions.

Dr. Jiakang Zheng
Dr. Yuanbin Chen
Dr. Weicong Chen
Dr. Yijing Lin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • MIMO
  • network architecture
  • antenna
  • signal processing
  • resource allocation

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Published Papers (6 papers)

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Research

20 pages, 1247 KB  
Article
Geometrical-Based Modeling for Aerial Intelligent Reflecting Surface-Based MIMO Channels
by Zhangfeng Ma, Shuaiqiang Lu, Yifei Peng, Jianhua Zhou, Jianming Xu, Gaofeng Luo and Meimei Luo
Electronics 2026, 15(4), 875; https://doi.org/10.3390/electronics15040875 - 19 Feb 2026
Viewed by 371
Abstract
Traditional multiple-input multiple-output (MIMO) systems are confronted with significant challenges in realizing ubiquitous connectivity for sixth-generation (6G) networks, particularly in environments characterized by severe signal blockage and dynamic co-mobility. While aerial intelligent reflecting surfaces (AIRS) offer a promising paradigm to address these difficulties, [...] Read more.
Traditional multiple-input multiple-output (MIMO) systems are confronted with significant challenges in realizing ubiquitous connectivity for sixth-generation (6G) networks, particularly in environments characterized by severe signal blockage and dynamic co-mobility. While aerial intelligent reflecting surfaces (AIRS) offer a promising paradigm to address these difficulties, the existing channel models often fail to capture fast channel changes, thereby leading to inefficient phase optimization in time-varying scenarios. To address these limitations, a geometric MIMO channel model is proposed for AIRS-assisted communications. This model comprises an indirect link from the base station (BS) via the AIRS to the receiver (Rx) and a direct BS-Rx link, whose direct propagation environment is rigorously characterized by a one-cylinder model specifically designed to tackle the complexities of dynamic co-mobility and intricate propagation. A joint optimization problem is formulated to maximize the achievable rate by optimizing the transmitted signal’s covariance matrix and the AIRS phase shift. Subsequently, an iterative algorithm employing the projected gradient method (PGM) is proposed for its solution, which is tailored for efficient operation in time-varying environments. Furthermore, expressions for the space–time correlation function and Doppler power spectrum are derived to evaluate the overall channel properties. Significant enhancements in achievable rates are demonstrated by AIRS, with substantial gains being observed even for a small number of reflecting elements. Consequently, crucial guidance for the design of robust AIRS-assisted MIMO systems is provided by these findings, and the broad applicability of the proposed algorithm is thereby confirmed. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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17 pages, 858 KB  
Article
Large AI Model-Enhanced Digital Twin-Driven 6G Healthcare IoE
by Haoyuan Hu, Ziyi Song and Wenzao Shi
Electronics 2026, 15(3), 619; https://doi.org/10.3390/electronics15030619 - 31 Jan 2026
Viewed by 593
Abstract
The convergence of the Internet of Everything (IoE) and healthcare requires ultra-reliable, low-latency, and intelligent communication systems. Sixth-generation (6G) wireless networks, coupled with digital twin (DT) models and large AI models (LAMs), are envisioned to promise substantial and practically meaningful improvements in smart [...] Read more.
The convergence of the Internet of Everything (IoE) and healthcare requires ultra-reliable, low-latency, and intelligent communication systems. Sixth-generation (6G) wireless networks, coupled with digital twin (DT) models and large AI models (LAMs), are envisioned to promise substantial and practically meaningful improvements in smart healthcare by enabling real-time monitoring, diagnosis, and personalized treatment. In this article, we propose an LAM-enhanced DT-driven network slicing framework for healthcare applications. The framework leverages large models to provide predictive insights and adaptive orchestration by creating virtual replicas of patients and medical devices that guide dynamic slice allocation. Reinforcement learning (RL) techniques are employed to optimize slice orchestration under uncertain traffic conditions, with LAMs augmenting decision-making through cognitive-level reasoning. Numerical results show that the proposed LAM–DT–RL framework reduces service-level agreement (SLA) violations by approximately 42–43% compared to a reinforcement-learning-only slicing strategy, while improving spectral efficiency and fairness among heterogeneous healthcare services. Finally, we outline open challenges and future research opportunities in integrating LAMs, DTs, and 6G for resilient healthcare IoE systems. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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21 pages, 5576 KB  
Article
Statistical CSI-Based Transmission Design for Movable Antenna-Aided Cell-Free Massive MIMO
by Yang Zhang, Yuehong Sun, Pin Wen and Foxiang Liu
Electronics 2026, 15(3), 546; https://doi.org/10.3390/electronics15030546 - 27 Jan 2026
Viewed by 406
Abstract
This paper studies a novel movable antenna (MA)-aided Cell-Free Massive MIMO system to leverage the corresponding spatial degrees of freedom (DoFs) for improving the performance of distributed wireless networks. We aim to maximize the ergodic sum capacity by jointly optimizing the MA positions [...] Read more.
This paper studies a novel movable antenna (MA)-aided Cell-Free Massive MIMO system to leverage the corresponding spatial degrees of freedom (DoFs) for improving the performance of distributed wireless networks. We aim to maximize the ergodic sum capacity by jointly optimizing the MA positions and the transmit covariance matrix based on statistical channel state information (CSI). To address the non-convex stochastic optimization problem, we propose a novel Constrained Stochastic Successive Convex Approximation (CSSCA) framework, enhanced with a robust slack-variable mechanism to handle non-convex antenna spacing constraints and ensure iterative feasibility. Numerical results show that the considered MA-enhanced system can significantly improve the ergodic capacity compared to fixed-antenna cell-free systems and that the proposed algorithm exhibits robust convergence behavior. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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18 pages, 964 KB  
Article
Stacked Intelligent Metasurfaces: Key Technologies, Scenario Adaptation, and Future Directions
by Jiayi Liu and Jiacheng Kong
Electronics 2026, 15(2), 274; https://doi.org/10.3390/electronics15020274 - 7 Jan 2026
Viewed by 1379
Abstract
The advent of sixth-generation (6G) imposes stringent demands on wireless networks, while traditional 2D rigid reconfigurable intelligent surfaces (RISs) face bottlenecks in regulatory freedom and scenario adaptability. To address this, stacked intelligent metasurfaces (SIMs) have emerged. This paper presents a systematic review of [...] Read more.
The advent of sixth-generation (6G) imposes stringent demands on wireless networks, while traditional 2D rigid reconfigurable intelligent surfaces (RISs) face bottlenecks in regulatory freedom and scenario adaptability. To address this, stacked intelligent metasurfaces (SIMs) have emerged. This paper presents a systematic review of SIM technology. It first elaborates on the SIM multi-layer stacked architecture and wave-domain signal-processing principles, which overcome the spatial constraints of conventional RISs. Then, it analyzes challenges, including beamforming and channel estimation for SIM, and explores its application prospects in key 6G scenarios such as integrated sensing and communication (ISAC), low earth orbit (LEO) satellite communication, semantic communication, and UAV communication, as well as future trends like integration with machine learning and nonlinear devices. Finally, it summarizes the open challenges in low-complexity design, modeling and optimization, and performance evaluation, aiming to provide insights to promote the large-scale adoption of SIM in next-generation wireless communications. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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23 pages, 1260 KB  
Article
On Deep Learning Hybrid Architectures for MIMO-OFDM Channel Estimation
by Inês Almeida, João Guerreiro and Rui Dinis
Electronics 2025, 14(23), 4692; https://doi.org/10.3390/electronics14234692 - 28 Nov 2025
Cited by 1 | Viewed by 1264
Abstract
Traditional estimation methods face challenges in adverse conditions in systems such as Multiple Input Multiple Output (MIMO) with Orthogonal Frequency Division Multiplexing (OFDM). To overcome those challenges, Deep Learning (DL) approaches have been proposed as an interesting alternative, thanks to their ability to [...] Read more.
Traditional estimation methods face challenges in adverse conditions in systems such as Multiple Input Multiple Output (MIMO) with Orthogonal Frequency Division Multiplexing (OFDM). To overcome those challenges, Deep Learning (DL) approaches have been proposed as an interesting alternative, thanks to their ability to capture channel features without much complexity. This paper presents a hybrid approach that combines DL with traditional estimation methods such as Least Squares (LS) and Minimum Mean Square Error (MMSE), which we designate as DL-Enhanced. Our main innovation is a phase-preserving mechanism that maintains critical phase information frequently degraded in purely data-driven approaches. We evaluate the proposed technique considering MIMO-OFDM systems considering 3GPP Clustered Delay Line Model C (CDL-C) channels. Simulation results demonstrate that our method outperforms conventional techniques at high-SNR levels, thanks to neural network-based feature extraction and adaptive processing. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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12 pages, 3114 KB  
Article
Planar CPW-Fed MIMO Antenna Array Design with Enhanced Isolation Using T-Shaped Neutralization Lines
by Mohamed Morsy
Electronics 2025, 14(18), 3683; https://doi.org/10.3390/electronics14183683 - 17 Sep 2025
Cited by 1 | Viewed by 1364
Abstract
This paper presents the design and performance evaluation of a compact four-element coplanar waveguide (CPW)-fed antenna array operating in the 3.3–3.6 GHz frequency band. The proposed antenna is tailored for sub-6 GHz 5G New Radio (NR) applications, specifically aligning with the n77/n78 bands [...] Read more.
This paper presents the design and performance evaluation of a compact four-element coplanar waveguide (CPW)-fed antenna array operating in the 3.3–3.6 GHz frequency band. The proposed antenna is tailored for sub-6 GHz 5G New Radio (NR) applications, specifically aligning with the n77/n78 bands widely adopted for mid-band 5G deployment. The CPW feeding technique enables low-profile integration and ease of fabrication, while the multi-element configuration supports enhanced gain and spatial diversity. Both simulated and measured results demonstrate good impedance matching (|S11| < −10 dB), stable radiation patterns, and inter-element isolation suitable for MIMO operation. The design offers a promising solution for compact 5G antenna systems and can be extended to future wireless communication platforms requiring high efficiency and compact form factors. Full article
(This article belongs to the Special Issue Advanced MIMO Technologies in Wireless Communications: Innovations and Future Prospects)
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