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Applied Sciences
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Integrated Sensing and Communications: Latest Advances and Prospects
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Integrated Sensing and Communications: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 July 2025 | Viewed by 8547

Special Issue Editors

Prof. Dr. Višnja Križanović

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: communication technologies assisted by sensors; advanced networking technologies assisted by sensors; performance evaluation of networking solutions with sensors
Prof. Dr. Krešimir Grgić

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: wireless communications; smart sensing; security aspects of communication systems
Prof. Dr. Drago Žagar

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: advanced networking technologies assisted by sensors; smart sensing; wireless communications

Special Issue Information

Dear Colleagues,

Signal processing procedures played an important role in the early development of combined sensing and communication systems, due to the need to use a limited spectrum more efficiently and reduce hardware expenditures. At first, dual-function radar communication systems prevailed over the field of joint sensing and communication. However, this area has since evolved into a more complex archetype called integrated sensing and communication (ISAC), which takes into account various types of sensing and communication interactions and considers other sensors besides radar. Wireless sensing was for a long time a separate technology developed as a complement to mobile communication systems. General sensing should be integrated into 6G mobile communication systems to open up new services for 6G.

The capabilities of ISAC will enable many services that mobile communication system operators offer. These include localization and tracking, high-accuracy positioning, imaging for biomedical and security applications, natural disaster monitoring, activity and gesture recognition, defect and material detection, and numerous other services. Designing future ISAC systems requires many challenges to be overcome, such as selecting transmitter signals, processing received signals, estimating channels, and tracking and allocating resources. In recent years, several signal processing techniques have been introduced to address these challenges, resulting in a growing interest in advanced signal processing methods for designing ISAC and implementing it in future wireless networks. Despite drawing significant attention from both academia and industry, many open problems still require investigation. This Special Issue aims to provide a collection of technical papers from academia and industry, focusing on major trends related to ISAC. Contributions may be focused on topics including but not limited to the following:

  • Communication technologies assisted by sensors;
  • Advanced networking technologies assisted by sensors;
  • Experimental demonstrations and prototypes of ISAC for sensors;
  • Performance evaluation for ISAC with sensors;
  • Security and privacy issues of ISAC;
  • Application of advanced ISAC technologies;
  • Progress in the standardization of ISAC;
  • Integrated sensing, communication, and computing for ISAC;
  • Centralized or distributed machine learning for ISAC.

Prof. Dr. Višnja Križanović
Prof. Dr. Krešimir Grgić
Prof. Dr. Drago Žagar
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Applied Sciences 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

  • integrated sensing and communication
  • combined sensing and communication systems
  • trends related to integrated sensing and communication

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Published Papers (4 papers)

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Research

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20 pages, 739 KiB  
Article
Compact Bistatic Iterative Passive Radar Based on Terrestrial Digital Video Broadcasting Signals
by Víctor P. Gil Jiménez and Atilio Gameiro
Appl. Sci. 2025, 15(7), 3460; https://doi.org/10.3390/app15073460 - 21 Mar 2025
Viewed by 232
Abstract
Passive radar has become very popular in recent years because it is usually undetectable, and countermeasures used to prevent its functioning are complex and, in general, easily identified. Terrestrial digital video broadcasting (DVB-T) is commonly used as an opportunistic illumination signal because of [...] Read more.
Passive radar has become very popular in recent years because it is usually undetectable, and countermeasures used to prevent its functioning are complex and, in general, easily identified. Terrestrial digital video broadcasting (DVB-T) is commonly used as an opportunistic illumination signal because of its large range and widespread deployment, both of which make it applicable to almost all scenarios. This paper presents the design of a compact and robust receiver for passive radar that uses a low number of antenna while achieving high accuracy. In order to do this, we use an iterative algorithm to refine the initial estimations based on time-domain channel information to converge to the true estimations. This is especially effective when the signal-to-noise-ratio (SNR) at the receiver is moderate and/or there are several reflections in the environment that may introduce some error into schemes that perform the angle of arrival or time of arrival for the estimation. The algorithm proposed herein is able to accurately estimate the position of a target with a low SNR. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications: Latest Advances and Prospects)
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21 pages, 7993 KiB  
Article
Real-Time Failure Prediction of ROADMs by GAN-Enhanced Machine Learning
by Takeshi Naito, Shota Nishijima, Yuichiro Nishikawa and Akira Hirano
Appl. Sci. 2025, 15(4), 2107; https://doi.org/10.3390/app15042107 - 17 Feb 2025
Cited by 1 | Viewed by 670
Abstract
We proposed a novel technique for detecting optical filter shift in ROADMs in optical transmission lines by applying machine learning on DP-16QAM constellation data captured just after Analogue-to-Digital Converters (ADCs) in a digital coherent receiver. For this purpose, we implemented Docker container applications [...] Read more.
We proposed a novel technique for detecting optical filter shift in ROADMs in optical transmission lines by applying machine learning on DP-16QAM constellation data captured just after Analogue-to-Digital Converters (ADCs) in a digital coherent receiver. For this purpose, we implemented Docker container applications in WhiteBox Cassini to acquire the real-time raw digital data. By using the captured data, we generated CNN models for the detections in off-line processing and used them for real-time detections. As preliminary results, we confirmed the successful detection of optical filter shift in real-time with an accuracy of 51 GHz. To enhance the detection accuracy, we challenged ourselves to reproduce digital coherent constellation data by using a Generative Adversarial Network (GAN) for real-time optical filter shift detection for the first time. By utilizing a GAN, we successfully generated clone data based on actual constellation data. By adding the cloned data onto the actually captured data, we successfully enhanced detection sensitivity to as high as 26 GHz. As a result, we reduced the amount of required data for the high detection accuracy by 68% with the help of GAN-supported data augmentation. Furthermore, we confirmed our augmentation method enables the prediction of faults before they occur by enabling high enough detection sensitivity to detect an optical filter shift before degradation of Bit Error Rates (BERs) appears. This demonstrates the potential of GAN-based data augmentation in optimizing the efficiency and precision of optical network impairment sensing by using captured digital coherent optical signal. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications: Latest Advances and Prospects)
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15 pages, 865 KiB  
Article
An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian
by Qiang Fu, Ling Wang, Qiyue Xie and Yucai Zhou
Appl. Sci. 2024, 14(4), 1393; https://doi.org/10.3390/app14041393 - 8 Feb 2024
Cited by 2 | Viewed by 1579
Abstract
The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this [...] Read more.
The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for the state prediction covariance matrix. The system state and noise parameter posterior distributions are then iteratively updated for adaptive estimation. Furthermore, we make adaptive adjustments to the IEKF filter parameters to enhance sensitivity and filtering accuracy, thus ensuring robust prediction estimation. A two-dimensional target tracking and nonlinear numerical UNGM simulation validated our algorithm. Compared to existing algorithms RKF-ML and GA-VB, our method showed significant improvements in RMSEpos and RMSEvel, with increases of 21.81% and 22.11% respectively, and a 49.04% faster convergence speed. These results highlight the method’s reliability and adaptability. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications: Latest Advances and Prospects)
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Review

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45 pages, 2825 KiB  
Review
UWB-Based Real-Time Indoor Positioning Systems: A Comprehensive Review
by Mohammed Faeik Ruzaij Al-Okby, Steffen Junginger, Thomas Roddelkopf and Kerstin Thurow
Appl. Sci. 2024, 14(23), 11005; https://doi.org/10.3390/app142311005 - 26 Nov 2024
Cited by 6 | Viewed by 4971
Abstract
Currently, the process of tracking moving objects and determining their indoor location is considered to be one of the most attractive applications that have begun to see widespread use, especially after the adoption of this technology in some smartphone applications. The great developments [...] Read more.
Currently, the process of tracking moving objects and determining their indoor location is considered to be one of the most attractive applications that have begun to see widespread use, especially after the adoption of this technology in some smartphone applications. The great developments in electronics and communications systems have provided the basis for tracking and location systems inside buildings, so-called indoor positioning systems (IPSs). The ultra-wideband (UWB) technology is one of the important emerging solutions for IPSs. This radio communications technology provides important characteristics that distinguish it from other solutions, such as secure and robust communications, wide bandwidth, high data rate, and low transmission power. In this paper, we review the implementation of the most important real-time indoor positioning and tracking systems that use ultra-wideband technology for tracking and localizing moving objects. This paper reviews the newest in-market UWB modules and solutions, discussing several types of algorithms that are used by the real-time UWB-based systems to determine the location with high accuracy, along with a detailed comparison that saves the reader a lot of time and effort in choosing the appropriate UWB-module/method/algorithm for real-time implementation. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications: Latest Advances and Prospects)
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