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Entropy
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Integrated Sensing and Communication (ISAC) in 6G
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Integrated Sensing and Communication (ISAC) in 6G

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Signal and Data Analysis".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 3759

Special Issue Editors

Dr. Danaisy Prado-Alvarez

E-Mail Website
Guest Editor
iTEAM Research Institute, Universitat Politècnica de València, Valencia, Spain
Interests: 5G and 6G wireless technologies design; channel modeling; network planning; resource allocation
Dr. Jose F. Monserrat

E-Mail Website
Guest Editor
iTEAM Research Institute, Universitat Politècnica de València, Valencia, Spain
Interests: signal processing; wireless communication systems; channel modeling; vehicular communications; 5G and 6G technologies design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Integrated sensing and communication (ISAC) is an emerging technology that integrates communication and sensing functions into a single system, offering new possibilities for future wireless networks. A key challenge in ISAC systems is optimizing the trade-offs between sensing and communication performance. Both functions often compete for limited resources, such as spectrum, energy, and hardware, making it essential to balance their performance for maximum system efficiency.

Equally important are channel models that account for the correlation between the sensed channel and the communication channel. These models are crucial for accurately characterizing the interactions between communication and sensing, leading to more effective systems that minimize interference and optimize resource usage.

This Special Issue will focus on trade-off analysis and advanced channel modeling in ISAC systems. Contributions will also explore applications in vehicular communications, where ISAC enables enhanced safety and low-latency communication, and in industrial environments, where it facilitates real-time monitoring, predictive maintenance, and efficient resource management. We invite researchers to submit works that address both the theoretical foundations and practical implementations of ISAC, providing insights into the future of integrated systems in these domains.

Dr. Danaisy Prado-Alvarez
Dr. Jose F. Monserrat
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. Entropy is an international peer-reviewed open access monthly 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 2600 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

  • ISAC (integrated sensing and communication)
  • trade-offs
  • channel models
  • sensing and communication
  • vehicular communications
  • industrial applications
  • resource optimization

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Published Papers (3 papers)

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Research

21 pages, 764 KB  
Article
Secrecy Rate Maximization for Movable Antenna-Aided STAR-RIS in Integrated Sensing and Communication Systems
by Guanyi Chen, Gang Wang, Jinlong Wang, Donglai Zhao, Chenxu Wang, Tao Jin and Zhiquan Zhou
Entropy 2025, 27(12), 1180; https://doi.org/10.3390/e27121180 - 21 Nov 2025
Viewed by 656
Abstract
Movable antennas (MAs) and simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently been investigated to enhance integrated sensing and communication (ISAC) systems. However, prior work has not exploited the spatial flexibility of MAs and the extended coverage of STAR-RIS to simultaneously [...] Read more.
Movable antennas (MAs) and simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently been investigated to enhance integrated sensing and communication (ISAC) systems. However, prior work has not exploited the spatial flexibility of MAs and the extended coverage of STAR-RIS to simultaneously address security issues. In this paper, a novel MA- and STAR-RIS-assisted secure ISAC system is proposed that involves multiple legitimate users and potential eavesdroppers. To ensure fairness, we formulate a minimum secrecy rate maximization problem by jointly optimizing the active beamforming covariance matrices at the base station (BS), the passive transmitting and reflecting beamforming coefficients at the STAR-RIS, and the spatial positions of the MAs. To address the highly nonconvex optimization problem, we propose an efficient iterative algorithm based on the alternating optimization (AO) framework. Specifically, we leverage semidefinite relaxation (SDR) and successive convex approximation (SCA) techniques to solve the active and passive beamforming subproblems, and the SCA method is also applied to tackle the highly intractable MA position optimization subproblem. Numerical results demonstrate that the secure performance of the proposed MA and STAR-RIS-assisted scheme significantly outperforms that of other benchmark schemes, validating the benefits of the proposed algorithm. Full article
(This article belongs to the Special Issue Integrated Sensing and Communication (ISAC) in 6G)
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15 pages, 924 KB  
Article
Optimization of ISAC Trade-Off via Covariance Matrix Allocation in Multi-User Systems
by Danaisy Prado-Alvarez, Daniel Calabuig, Saúl Inca and Jose F. Monserrat
Entropy 2025, 27(11), 1144; https://doi.org/10.3390/e27111144 - 9 Nov 2025
Viewed by 646
Abstract
Integrated Sensing and Communication (ISAC) is envisioned as a foundational technology for future wireless networks, enabling simultaneous wireless communication and environmental sensing using shared resources. A key challenge in ISAC systems lies in managing the trade-off between communication data rate and sensing accuracy, [...] Read more.
Integrated Sensing and Communication (ISAC) is envisioned as a foundational technology for future wireless networks, enabling simultaneous wireless communication and environmental sensing using shared resources. A key challenge in ISAC systems lies in managing the trade-off between communication data rate and sensing accuracy, especially in multi-user scenarios. In this work, we investigate the joint design of transmit signal covariance matrices to optimize the sum data rate while ensuring certain sensing performance. Specifically, we formulate a constrained optimization problem where the transmit covariance matrix is allocated to maximize the communication sum-rate under sensing-related constraints. These constraints condition the design of the transmit signal’s covariance matrix, impacting both the sensing channel estimation error and the sum data rate. Our proposed method leverages convex optimization tools to achieve a principled balance between communication and sensing. Numerical results demonstrate that the proposed approach effectively manages the ISAC trade-off, achieving near-optimal communication performance while satisfying sensing requirements. Full article
(This article belongs to the Special Issue Integrated Sensing and Communication (ISAC) in 6G)
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13 pages, 540 KB  
Article
Transmit Power Optimization for Simultaneous Wireless Information and Power Transfer-Assisted IoT Networks with Integrated Sensing and Communication and Nonlinear Energy Harvesting Model
by Chengrui Zhou, Xinru Wang, Yanfei Dou and Xiaomin Chen
Entropy 2025, 27(5), 456; https://doi.org/10.3390/e27050456 - 24 Apr 2025
Viewed by 1333
Abstract
Integrated sensing and communication (ISAC) can improve the energy harvesting (EH) efficiency of simultaneous wireless information and power transfer (SWIPT)-assisted IoT networks by enabling precise energy harvest. However, the transmit power is increased in the hybrid system due to the fact that the [...] Read more.
Integrated sensing and communication (ISAC) can improve the energy harvesting (EH) efficiency of simultaneous wireless information and power transfer (SWIPT)-assisted IoT networks by enabling precise energy harvest. However, the transmit power is increased in the hybrid system due to the fact that the sensing signals are required to be transferred in addition to the communication data. This paper aims to tackle this issue by formulating an optimization problem to minimize the transmit power of the base station (BS) under a nonlinear EH model, considering the coexistence of power-splitting users (PSUs) and time-switching users (TSUs), as well as the beamforming vector associated with PSUs and TSUs. A two-layer algorithm based on semi-definite relaxation is proposed to tackle the complexity issue of the non-convex optimization problem. The global optimality is theoretically analyzed, and the impact of each parameter on system performance is also discussed. Numerical results indicate that TSUs are more prone to saturation compared to PSUs under identical EH requirements. The minimal required transmit power under the nonlinear EH model is much lower than that under the linear EH model. Moreover, it is observed that the number of TSUs is the primary limiting factor for the minimization of transmit power, which can be effectively mitigated by the proposed algorithm. Full article
(This article belongs to the Special Issue Integrated Sensing and Communication (ISAC) in 6G)
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