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 June 2024 | Viewed by 1014

Special Issue Editors


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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

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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

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

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Keywords

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

Published Papers (1 paper)

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Research

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
Viewed by 610
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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