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Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing

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

Deadline for manuscript submissions: 15 August 2026 | Viewed by 17004

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Editors

Dr. Wensheng Lin

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Guest Editor

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China
Interests: semantic communications; wireless communications; AI; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Junli Liang

E-Mail Website
Guest Editor

School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Interests: radar signal processing; machine learning; 6G, and their applications
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Haitao Xu

E-Mail Website
Guest Editor

Department of Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: wireless resource allocation and management; wireless communications and networking; dynamic game and mean field game theory; big data analysis; security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radio frequency (RF) is a common resource used in wireless communication and radar. In the past, wireless communication and radar were considered to be conflicting due to the interference between them; however, with the development of RF technologies, people have found that wireless communication and radar can co-exist harmoniously. For example, positioning the receiver can help the transmitter direct the communication signal more accurately toward the mobile receiver via beamforming. Conversely, distributed radar systems have a higher resolution by communicating the sensing data. In addition, dual-function radar-communication systems have also emerged. Therefore, wireless communication and radar can benefit from each other, which becomes a significant trend for future wireless communication and radar systems.

This Special Issue aims to present state-of-the-art research in wireless communication and/or radar-related technologies. Topics of interest include (but are not limited to) the following:

6G;
Radar signal processing;
Integrated sensing and communication;
Semantic communication;
Reconfigurable intelligent surface;
Machine learning;
Resource allocation and management;
Information theory;
Joint source-channel coding;
Security.

Dr. Wensheng Lin
Prof. Dr. Junli Liang
Dr. Haitao Xu
Guest Editors

Manuscript Submission Information

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Keywords

6G
integrated sensing and communication
radar signal processing
semantic communication
reconfigurable intelligent surface
machine learning
resource allocation and management
information theory
joint source-channel coding
security

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Published Papers (6 papers)

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Research

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25 pages, 5757 KB

Open AccessArticle

A Device-Free Human Detection System Using 2.4 GHz Wireless Networks and an RSSI Distribution-Based Method with Autonomous Threshold

by Charernkiat Pochaiya, Apidet Booranawong, Dujdow Buranapanichkit, Kriangkrai Tassanavipas and Hiroshi Saito

Electronics 2026, 15(2), 491; https://doi.org/10.3390/electronics15020491 - 22 Jan 2026

Viewed by 907

Abstract

A device-free human detection system based on a received signal strength indicator (RSSI) monitors and analyzes the change of RSSI signals to detect human movements in a wireless network. This study proposes and implements a real-time, device-free human detection system based on an RSSI distribution-based detection method with an autonomous threshold. The novelty and contribution of our solution is that the RSSI distribution concept is considered and used to calculate the optimal threshold setting for human detection, while thresholds can be automatically determined from RSSI data streams gathered from test environments. The proposed system can efficiently work without requiring an offline phase, as introduced in many existing works in the research literature. Experiments using 2.4 GHz IEEE 802.15.4 technology have been carried out in indoor environments in two laboratory rooms with different numbers of wireless links, human movement patterns, and movement speeds. Experimental results show that, in all test scenarios, the proposed method can monitor and detect human movement in a wireless network in real time. It outperforms a comparative method and achieves high accuracy (i.e., 100% detection accuracy) with a low computational complexity requirement. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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21 pages, 2894 KB

Open AccessArticle

Tracking Control of Quadrotor UAVs with Prescribed Performance and Prescribed-Time Convergence Under Arbitrary Initial Conditions

by Tiantian Xiao, Jinlong Guo, Jintao Chen, Dawei Sun, Daochun Li and Jinwu Xiang

Electronics 2026, 15(2), 408; https://doi.org/10.3390/electronics15020408 - 16 Jan 2026

Viewed by 699

Abstract

Quadrotor unmanned aerial vehicles demonstrate broad application prospects, yet existing research still lacks a comprehensive solution that simultaneously addresses efficiency, disturbance rejection, environmental adaptability, and precision in their control performance. To achieve prescribed-time convergence and prescribed tracking performance, this work proposes a composite control scheme that integrates prescribed-performance control, disturbance estimation, and terminal sliding-mode control. First, a prescribed-time adaptive composite disturbance observer is developed to estimate and compensate for system composite disturbances, and a stability analysis shows that the disturbance estimation error converges to a small neighborhood of the origin within a prescribed time. Second, the system is decomposed into position and attitude subsystems, enabling tailored hierarchical control-law design and analysis based on their distinct dynamics. For position control, a prescribed-performance control method is employed, incorporating a prescribed-time performance function that accommodates large initial deviations, thereby guaranteeing convergence of the position-tracking errors to a small neighborhood within a specified time. For attitude control, a prescribed-time terminal sliding-mode surface and corresponding control law are designed to eliminate singularities and ensure convergence of the attitude errors to a small neighborhood within a predetermined time. The stability of both subsystems is rigorously substantiated through theoretical analysis. Finally, comparative simulation results confirm the effectiveness and superiority of the proposed control strategy. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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11 pages, 639 KB

Open AccessArticle

Velocity Ambiguity and Inter-Carrier Interference Suppression Algorithm in Stepped-Carrier OFDM Radar for ISAC

by Xuanxuan Tian

Electronics 2025, 14(23), 4763; https://doi.org/10.3390/electronics14234763 - 3 Dec 2025

Viewed by 829

Abstract

Stepped-carrier orthogonal frequency division multiplexing (SC-OFDM) radar is an emerging low-cost alternative to standard OFDM radar for automotive applications due to providing high-range resolution at a low sampling rate. However, it is limited by inter-carrier interference (ICI) and velocity ambiguity in high-speed target detection. To address these issues, this paper proposes a two-step method for SC-OFDM radar. The method first applies multi-hypothesis Doppler compensation and leverages peak sidelobe ratio (PSLR) in the range profile as a distinguishing feature to estimate the target’s unambiguous velocity. Then, target signals are reconstructed into components free from ICI. Simulation results confirm the effectiveness of the proposed method. Compared to existing methods, this approach eliminates ICI without repeating OFDM symbols, thereby preserving communication data rate and enhancing suitability for integrated sensing and communication (ISAC) applications. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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18 pages, 4415 KB

Open AccessArticle

Ultra-Dense Uplink UAV Lossy Communications: Trajectory Optimization Based on Mean Field Game

by Yibo Ma and Shen Qian

Electronics 2025, 14(11), 2219; https://doi.org/10.3390/electronics14112219 - 29 May 2025

Cited by 1 | Viewed by 1258

Abstract

This paper investigates a multiple unmanned aerial vehicle (UAV) enabled network for supporting emergency communication services, where each drone acts as a base station (also called the drone small cell (DSC)). The novelty of this paper is that a mean field game (MFG)-based strategy is conceived for jointly controlling the three-dimensional (3D) locations of these drones to guarantee the distortion requirement of lossy communications, while considering the inter-cell interference and the flight energy consumption of drones. More explicitly, we derive the Hamilton–Jacobi–Bellman (HJB) and Fokker–Planck–Kolmogorov (FPK) equations, and propose an algorithm where both the Lax–Friedrichs scheme and the Lagrange relaxation are invoked for solving the HJB and FPK equations with 3D control vectors and state vectors. The numerical results show that the proposed algorithm can achieve a higher access rate with a similar flight energy consumption. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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Review

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34 pages, 1509 KB

Open AccessReview

AI for Wireless Waveform Recognition: A Survey from a Component Perspective

by Decan Zhao, Junteng Yang, Dongwei Zhao, Lechi Zhang, Zhenyu Xu, Anjie Cao, Wensheng Lin, Wenchi Cheng, Qinghe Du and Lixin Li

Electronics 2026, 15(10), 2112; https://doi.org/10.3390/electronics15102112 - 14 May 2026

Cited by 1 | Viewed by 341

Abstract

Electromagnetic signal waveform recognition (ESWR) constitutes a fundamental enabling technology for modern spectrum management, cognitive radio, and electronic warfare applications. Among various ESWR subtasks, automatic modulation recognition (AMR) has attracted the most intensive research efforts and serves as the primary focus of this survey. Over the past decade, deep learning (DL) has fundamentally transformed ESWR by replacing hand-crafted feature engineering with data-driven end-to-end learning paradigms. However, the rapid proliferation of DL-based approaches has resulted in a fragmented research landscape. This paper addresses this gap by proposing a unified system-component framework that decomposes any DL-ESWR system into four foundational modules: (i) dataset construction and data augmentation, (ii) signal representation and preprocessing, (iii) core network architecture, and (iv) training and optimization strategy. Through this systematic lens, we provide a comprehensive review that catalogs the state of the art across recent publications and precisely attributes each innovation to specific modules within our framework. Furthermore, we identify eight core challenges confronting the practical deployment of DL-ESWR systems and systematically analyze how targeted modular innovations address each challenge. A critical analysis of prevalent benchmark datasets reveals significant limitations in channel diversity, modulation coverage, and ecological validity. Finally, we outline seven promising future research directions, including foundation models for wireless signals, physics-informed neural networks, and waveform recognition for emerging communication paradigms, such as semantic communications and integrated sensing and communication (ISAC). This survey aims to provide researchers and practitioners with a structured roadmap for understanding, evaluating, and advancing the field of AI-enabled electromagnetic signal waveform recognition. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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28 pages, 3675 KB

Open AccessReview

Advancements in Millimeter-Wave Radar Technologies for Automotive Systems: A Signal Processing Perspective

by Boxun Yan and Ian P. Roberts

Electronics 2025, 14(7), 1436; https://doi.org/10.3390/electronics14071436 - 2 Apr 2025

Cited by 20 | Viewed by 11585

Abstract

This review paper provides a comprehensive examination of millimeter-wave radar technologies in automotive systems, reviewing their advancements through signal processing innovations. The evolution of radar systems, from conventional platforms to mmWave technologies, has significantly enhanced capabilities such as high-resolution imaging, real-time tracking, and multi-object detection. Signal processing advancements, including constant false alarm rate detection, multiple-input–multiple-output systems, and machine learning-based techniques, are explored for their roles in improving radar performance under dynamic and challenging environments. The integration of mmWave radar with complementary sensing technologies such as LiDAR and cameras facilitates robust environmental perception essential for advanced driver-assistance systems and autonomous vehicles. This review also calls attention to key challenges, including environmental interference, material penetration, and sensor fusion, while addressing innovative solutions such as adaptive signal processing and sensor integration. Emerging applications of joint communication–radar systems further presents the potential of mmWave radar in autonomous driving and vehicle-to-everything communications. By synthesizing recent developments and identifying future directions, this review stresses the critical role of mmWave radar in advancing vehicular safety, efficiency, and autonomy. Full article

(This article belongs to the Special Issue Innovations in Radio Frequency Technologies, Wireless Communication, and Signal Processing)

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