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Integrated Sensing and Communications

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 1808

Special Issue Editors


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Guest Editor
École Normale Supérieure de Lyon, Lyon, France
Interests: network information theory; estimation; multi-armed bandit; probability and statistics; differential privacy

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Guest Editor
Faculty of Electrical Engineering, Technion—Israel Institute of Technology, Haifa 3200003, Israel
Interests: multi-user information theory; modern communication networks (cloud and fog radio networks); information and signal processing (information–estimation); information bottleneck problems in communications and learning; sparse communications models and non-orthogonal (NOMA) systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
LTCI, Telecom Paris, IP Paris, 91120 Paris, France
Interests: network information theory; detection systems; capacity of channels; distributed computing; quantum information theory

Special Issue Information

Dear Colleagues,

With the forthcoming 6G networks on the horizon, we face exciting possibilities, particularly in the realm of environment monitoring through advanced communication networks. At the same time, the extension of 5G and 6G to higher frequencies, closer to the radar spectrum, invites system designers to integrate communication and radar systems into signal platforms that use the same waveform for both the communication and radar tasks with the goal to reduce the utilised spectrum and hardware costs and enable advanced systems that simultaneously acquire information from the environment and communicate it to desired destinations. Such integrated systems can enhance efficiency, reliability, and performance in various domains, such as the Internet of Things (IoT) smart cities and automated manufacturing sites, autonomous vehicles, wifi-sensing, healthcare, and environmental monitoring.

In recent years, researchers have started to model, analyse, and implement the first integrated systems, using tools from information and coding theory, communication theory, optimisation, or machine learning and statistics. Nevertheless, key challenges remain because a full theoretical framework for integrated sensing and communication (ISAC) is still missing. The goal of such a framework is to clearly identify the opportunities and limits of ISAC, and to provide intuition and insights for practical implementations. This Special Issue will collect new results (unpublished original work) contributing to such a theoretical framework and describe promising methods (in comprehensive reviews) related to the analysis, modelling, and implementation of ISAC systems. In particular, the Special Issue includes, but is not restricted to, the following research areas:

  • Information-theoretic limits;
  • New quality-of-service (QoS) measures;
  • Error-correcting codes;
  • Estimation and detection;
  • Modulation and communication schemes;
  • Resource allocation algorithms that improve spectrum utilisation;
  • Design of suitable waveforms;
  • Multi-user communication networks (e.g., NOMA);
  • Collaborative sensing;
  • Emerging communication applications, (e.g., UAVs);
  • Optical systems;
  • Communication techniques based on machine learning;
  • Cybersecurity and security in communication and sensing;
  • Cognitive radio networks;
  • Relays, ambient backscatterers, and intelligent reflective surfaces (IRS);
  • Cross-layer optimisation problems;
  • Green communications;
  • Quantum systems;
  • Controlled sensing and active hypothesis testing;
  • Super high-frequency ISAC theory and practice.

Contributions not related to integrated sensing and communications will not be considered for publication.

Dr. Mehrasa Ahmadipour
Prof. Dr. Shlomo Shamai (Shitz)
Prof. Dr. Michele Wigger
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. 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

  • communication networks
  • capacity
  • wireless communication
  • optical fibres
  • estimation
  • detection
  • active sensing
  • localisation and mapping
  • distributed sensing

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Published Papers (2 papers)

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Research

25 pages, 374 KiB  
Article
Joint Identification and Sensing for Discrete Memoryless Channels
by Wafa Labidi, Yaning Zhao, Christian Deppe and Holger Boche
Entropy 2025, 27(1), 12; https://doi.org/10.3390/e27010012 - 27 Dec 2024
Viewed by 390
Abstract
In the identification (ID) scheme proposed by Ahlswede and Dueck, the receiver’s goal is simply to verify whether a specific message of interest was sent. Unlike Shannon’s transmission codes, which aim for message decoding, ID codes for a discrete memoryless channel (DMC) are [...] Read more.
In the identification (ID) scheme proposed by Ahlswede and Dueck, the receiver’s goal is simply to verify whether a specific message of interest was sent. Unlike Shannon’s transmission codes, which aim for message decoding, ID codes for a discrete memoryless channel (DMC) are far more efficient; their size grows doubly exponentially with the blocklength when randomized encoding is used. This indicates that when the receiver’s objective does not require decoding, the ID paradigm is significantly more efficient than traditional Shannon transmission in terms of both energy consumption and hardware complexity. Further benefits of ID schemes can be realized by leveraging additional resources such as feedback. In this work, we address the problem of joint ID and channel state estimation over a DMC with independent and identically distributed (i.i.d.) state sequences. State estimation functions as the sensing mechanism of the model. Specifically, the sender transmits an ID message over the DMC while simultaneously estimating the channel state through strictly causal observations of the channel output. Importantly, the random channel state is unknown to both the sender and the receiver. For this system model, we present a complete characterization of the ID capacity–distortion function. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications)
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23 pages, 424 KiB  
Article
Joint Communication and Channel Discrimination
by Han Wu and Hamdi Joudeh
Entropy 2024, 26(12), 1089; https://doi.org/10.3390/e26121089 - 13 Dec 2024
Cited by 2 | Viewed by 615
Abstract
We consider a basic joint communication and sensing setup comprising a transmitter, a receiver and a sensor. The transmitter sends a codeword to the receiver through a discrete memoryless channel, and the receiver is interested in decoding the transmitted codeword. At the same [...] Read more.
We consider a basic joint communication and sensing setup comprising a transmitter, a receiver and a sensor. The transmitter sends a codeword to the receiver through a discrete memoryless channel, and the receiver is interested in decoding the transmitted codeword. At the same time, the sensor picks up a noisy version of the transmitted codeword through one of two possible discrete memoryless channels. The sensor knows the codeword and wishes to discriminate between the two possible channels, i.e., to identify the channel that has generated the output given the input. We study the trade-off between communication and sensing in the asymptotic regime, captured in terms of the channel coding rate against the two types of discrimination error exponents. We characterize the optimal trade-off between the rate and the exponents for general discrete memoryless channels with an input cost constraint. Full article
(This article belongs to the Special Issue Integrated Sensing and Communications)
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