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Novel Signal Processing Techniques for Wireless Communications
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Novel Signal Processing Techniques for Wireless Communications

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

Deadline for manuscript submissions: 31 October 2025 | Viewed by 3200

Special Issue Editor

Prof. Dr. Zhongxia He

E-Mail Website
Guest Editor
School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China
Interests: THz communication and sensing; THz chipsets; THz antenna and packaging

Special Issue Information

Dear Colleagues,

The THz band offers unparalleled high bandwidth, making it a promising frontier for future communication and sensing systems. However, the challenge lies in processing these high-frequency signals efficiently. Traditional analog-to-digital converters (ADCs) struggle with the high bandwidth of THz signals, especially within constrained cost and power budgets. Novel signal processing techniques are emerging as viable solutions to this dilemma.

Analog circuits, with their inherent ability to handle wide bandwidths, provide a pathway to process THz signals without the significant power overhead associated with digital conversion. Optoelectronic approaches, leveraging the principles of photonics, enable high-speed signal processing with reduced power consumption. These methods utilize the interaction of light with electronic signals to perform high-bandwidth operations at a fraction of the power cost. Additionally, exploring other physical principles, such as plasmonics and metamaterials, can further enhance signal processing capabilities, offering low-loss, high-speed alternatives.

These innovative signal processing solutions are not just technological advancements; they are critical enablers for the next generation of communication and sensing systems. By efficiently managing the high bandwidth and power requirements of THz signals, these technologies pave the way for ultra-fast wireless communication, high-resolution imaging, and advanced sensing applications, driving progress in fields ranging from telecommunications to healthcare and beyond.

Prof. Dr. Zhongxia He
Guest Editor

Manuscript Submission Information

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Keywords

  • signal processing
  • wireless communication
  • THz signals

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Published Papers (3 papers)

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Research

15 pages, 1164 KiB  
Article
On the Error Metrics Used for Direction of Arrival Estimation
by Mohammad Abdul Hannan, Ottavio Crisafulli, Giuseppe Giammello and Gino Sorbello
Sensors 2025, 25(8), 2358; https://doi.org/10.3390/s25082358 - 8 Apr 2025
Viewed by 231
Abstract
In this article, the error metrics used for evaluating the performance of direction of arrival (DoA) estimation are thoroughly investigated to recommend the most suitable one. This investigation highlights the lack of consensus in the literature regarding the selection and definition of these [...] Read more.
In this article, the error metrics used for evaluating the performance of direction of arrival (DoA) estimation are thoroughly investigated to recommend the most suitable one. This investigation highlights the lack of consensus in the literature regarding the selection and definition of these metrics. We show that this disparity is particularly serious in 2D DoA estimation, an aspect often overlooked by many authors. Notably, certain widely accepted error metrics can yield inaccurate and misleading results. Therefore, this article advocates for the adoption of a specific error metric that ensures accurate and meaningful assessments of 2D DoA estimation. A set of numerical and experimental results is presented to demonstrate the potential of the proposed error metric compared to other well-known metrics. Unlike other metrics, our proposed error definition is frame-independent. Finally, practical use cases are briefly discussed to highlight the pervasive impact of this fundamental definition. Full article
(This article belongs to the Special Issue Novel Signal Processing Techniques for Wireless Communications)
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15 pages, 874 KiB  
Article
Deep Reinforcement Learning-Driven Jamming-Enhanced Secure Unmanned Aerial Vehicle Communications
by Zhifang Xing, Yunhui Qin, Changhao Du, Wenzhang Wang and Zhongshan Zhang
Sensors 2024, 24(22), 7328; https://doi.org/10.3390/s24227328 - 16 Nov 2024
Cited by 1 | Viewed by 937
Abstract
Despite its flexibility, unmanned aerial vehicle (UAV) communications are susceptible to eavesdropping due to the open nature of wireless channels and the broadcasting nature of wireless signals. This paper studies secure UAV communications and proposes a method to optimize the minimum secrecy rate [...] Read more.
Despite its flexibility, unmanned aerial vehicle (UAV) communications are susceptible to eavesdropping due to the open nature of wireless channels and the broadcasting nature of wireless signals. This paper studies secure UAV communications and proposes a method to optimize the minimum secrecy rate of the system by using interference technology to enhance it. To this end, the system not only deploys multiple UAV base stations (BSs) to provide services to legitimate users but also assigns dedicated UAV jammers to send interference signals to active or potential eavesdroppers to disrupt their eavesdropping effectiveness. Based on this configuration, we formulate the optimization process of parameters such as the user association variables, UAV trajectory, and output power as a sequential decision-making problem and use the single-agent soft actor-critic (SAC) algorithm and twin delayed deep deterministic policy gradient (TD3) algorithm to achieve joint optimization of the core parameters. In addition, for specific scenarios, we also use the multi-agent soft actor-critic (MASAC) algorithm to solve the joint optimization problem mentioned above. The numerical results show that the normalized average secrecy rate of the MASAC algorithm increased by more than 6.6% and 14.2% compared with that of the SAC and TD3 algorithms, respectively. Full article
(This article belongs to the Special Issue Novel Signal Processing Techniques for Wireless Communications)
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17 pages, 7120 KiB  
Article
Two-Step Iterative Medical Microwave Tomography
by Zekun Zhang, Heng Liu, Xiang Gao, Zeyu Zhang, Zhongxia Simon He, Luoyuan Liu, Rui Zong and Zhizhen Qin
Sensors 2024, 24(21), 6897; https://doi.org/10.3390/s24216897 - 27 Oct 2024
Cited by 1 | Viewed by 1576
Abstract
In the field of medical imaging, microwave tomography (MWT) is based on the scattering and absorption characteristics of different tissues to microwaves and can reconstruct the electromagnetic property distribution of biological tissues non-invasively and without ionizing radiation. However, due to the inherently nonlinear [...] Read more.
In the field of medical imaging, microwave tomography (MWT) is based on the scattering and absorption characteristics of different tissues to microwaves and can reconstruct the electromagnetic property distribution of biological tissues non-invasively and without ionizing radiation. However, due to the inherently nonlinear and ill-posed characteristics of MWT calculations, actual imaging is prone to overfitting or artifacts. To address this, this paper proposes a two-step iterative imaging approach for rapid medical microwave tomography. This method establishes corresponding objective functions for microwave imaging across multiple frequencies and conducts iterative calculations on images at varying resolutions. This effectively enhances image clarity and accuracy while alleviating the issue of prolonged computational time associated with imaging complex structures at high resolution due to insufficient prior information during iterative processes. In the electromagnetic simulation section, we simulated a three-layer brain model and conducted imaging experiments. The results demonstrate that the algorithm significantly enhances imaging resolution, accurately pinpointing cerebral hemorrhages at different locations using an eight-antenna array and successfully reconstructs tomography images with a hemorrhage area radius of 1 cm. Lastly, experiments were conducted using a medical microwave tomography platform and four simplified human brain models, achieving millimeter-level accuracy in MWT. Full article
(This article belongs to the Special Issue Novel Signal Processing Techniques for Wireless Communications)
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