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Wireless Networks: Information Theoretic Perspectives Ⅱ

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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 (8 August 2022) | Viewed by 12515

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Special Issue Editors

Dr. Alex Dytso

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Guest Editor

Department of Electrical Engineering, New Jersey Institute of Technology (NJIT), Newark, NJ 07102, USA
Interests: multiuser information theory and estimation theory and their applications in wireless networks
Special Issues, Collections and Topics in MDPI journals

Dr. Luca Barletta

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Guest Editor

Department of Electronics, Polytechnic University of Milan, 20133 Milan, Italy
Interests: information theory and coding theory with applications to fiber-optic and wireless communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Network information theory is a framework for studying performance limits in communications over networks; as such, it is expected to continue to play an essential role in the future development of wireless networks, including 5G and beyond. This Special Issue aims to bring together the body of recent results in network information theory in order to bolster its value and emphasize the importance it continues to play in the development of wireless communications. Previously unpublished contributions in the intersection network information theory and wireless networks are solicited, including (but not limited to) the following:

Emerging information theoretic models for wireless communications;
Gaussian networks;
Capacity scaling laws;
Massive networks;
Random access;
Interference mitigation schemes;
Relaying techniques;
MIMO channels;
Massive MIMO;
Low latency communications;
Secure and private communications;
Low power communications;
Code design for networks;
Interactive communications and feedback;
Communication under channel uncertainty;
Mismatched network capacity;
Cloud and fog radio access networks.

Dr. Alex Dytso
Dr. Luca Barletta
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.

Related Special Issue

Wireless Networks: Information Theoretic Perspectives III in Entropy (3 articles)

Published Papers (7 papers)

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Research

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31 pages, 1338 KiB

Open AccessArticle

The Strongly Asynchronous Massive Access Channel

by Sara Shahi, Daniela Tuninetti and Natasha Devroye

Entropy 2023, 25(1), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/e25010065 - 29 Dec 2022

Cited by 2 | Viewed by 899

Abstract

This paper considers the Strongly Asynchronous, Slotted, Discrete Memoryless, Massive Access Channel (SAS-DM-MAC) in which the number of users, the number of messages, and the asynchronous window length grow exponentially with the coding blocklength with their respective exponents. A joint probability of error is enforced, ensuring that all the users’ identities and messages are correctly identified and decoded. Achievability bounds are derived for the case that different users have similar channels, the case that users’ channels can be chosen from a set which has polynomially many elements in the blocklength, and the case with no restriction on the users’ channels. A general converse bound on the capacity region and a converse bound on the maximum growth rate of the number of users are derived. It is shown that reliable transmission with an exponential number of users with an exponential asynchronous exponent with joint error probability is possible at strictly positive rates. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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26 pages, 7238 KiB

Open AccessArticle

Speeding up Training of Linear Predictors for Multi-Antenna Frequency-Selective Channels via Meta-Learning

by Sangwoo Park and Osvaldo Simeone

Entropy 2022, 24(10), 1363; https://0-doi-org.brum.beds.ac.uk/10.3390/e24101363 - 26 Sep 2022

Viewed by 1101

Abstract

An efficient data-driven prediction strategy for multi-antenna frequency-selective channels must operate based on a small number of pilot symbols. This paper proposes novel channel-prediction algorithms that address this goal by integrating transfer and meta-learning with a reduced-rank parametrization of the channel. The proposed methods optimize linear predictors by utilizing data from previous frames, which are generally characterized by distinct propagation characteristics, in order to enable fast training on the time slots of the current frame. The proposed predictors rely on a novel long short-term decomposition (LSTD) of the linear prediction model that leverages the disaggregation of the channel into long-term space-time signatures and fading amplitudes. We first develop predictors for single-antenna frequency-flat channels based on transfer/meta-learned quadratic regularization. Then, we introduce transfer and meta-learning algorithms for LSTD-based prediction models that build on equilibrium propagation (EP) and alternating least squares (ALS). Numerical results under the 3GPP 5G standard channel model demonstrate the impact of transfer and meta-learning on reducing the number of pilots for channel prediction, as well as the merits of the proposed LSTD parametrization. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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19 pages, 377 KiB

Open AccessArticle

Repair Rates for Multiple Descriptions on Distributed Storage

by Anders Høst-Madsen, Heecheol Yang, Minchul Kim and Jungwoo Lee

Entropy 2022, 24(5), 612; https://0-doi-org.brum.beds.ac.uk/10.3390/e24050612 - 27 Apr 2022

Viewed by 992

Abstract

In a traditional distributed storage system, a source can be restored perfectly when a certain subset of servers is contacted. The coding is independent of the contents of the source. This paper considers instead a lossy source coding version of this problem where the more servers that are contacted, the higher the quality of the restored source. An example could be video stored on distributed storage. In information theory, this is called the multiple description problem, where the distortion depends on the number of descriptions received. The problem considered in this paper is how to restore the system operation when one of the servers fail and a new server replaces it, that is, repair. The requirement is that the distortions in the restored system should be no more than in the original system. The question is how many extra bits are needed for repair. We find an achievable rate and show that this is optimal in certain cases. One conclusion is that it is necessary to design the multiple description codes with repair in mind; just using an existing multiple description code results in unnecessary high repair rates. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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17 pages, 366 KiB

Open AccessArticle

Secure Physical Layer Network Coding versus Secure Network Coding

by Masahito Hayashi

Entropy 2022, 24(1), 47; https://0-doi-org.brum.beds.ac.uk/10.3390/e24010047 - 27 Dec 2021

Cited by 1 | Viewed by 2087

Abstract

When a network has relay nodes, there is a risk that a part of the information is leaked to an untrusted relay. Secure network coding (secure NC) is known as a method to resolve this problem, which enables the secrecy of the message when the message is transmitted over a noiseless network and a part of the edges or a part of the intermediate (untrusted) nodes are eavesdropped. If the channels on the network are noisy, the error correction is applied to noisy channels before the application of secure NC on an upper layer. In contrast, secure physical layer network coding (secure PLNC) is a method to securely transmit a message by a combination of coding operation on nodes when the network is composed of set of noisy channels. Since secure NC is a protocol on an upper layer, secure PLNC can be considered as a cross-layer protocol. In this paper, we compare secure PLNC with a simple combination of secure NC and error correction over several typical network models studied in secure NC. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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18 pages, 442 KiB

Open AccessArticle

The Listsize Capacity of the Gaussian Channel with Decoder Assistance

by Amos Lapidoth and Yiming Yan

Entropy 2022, 24(1), 29; https://0-doi-org.brum.beds.ac.uk/10.3390/e24010029 - 24 Dec 2021

Cited by 3 | Viewed by 1836

Abstract

The listsize capacity is computed for the Gaussian channel with a helper that—cognizant of the channel-noise sequence but not of the transmitted message—provides the decoder with a rate-limited description of said sequence. This capacity is shown to equal the sum of the cutoff rate of the Gaussian channel without help and the rate of help. In particular, zero-rate help raises the listsize capacity from zero to the cutoff rate. This is achieved by having the helper provide the decoder with a sufficiently fine quantization of the normalized squared Euclidean norm of the noise sequence. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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20 pages, 387 KiB

Open AccessFeature PaperArticle

Encoding Individual Source Sequences for the Wiretap Channel

by Neri Merhav

Entropy 2021, 23(12), 1694; https://0-doi-org.brum.beds.ac.uk/10.3390/e23121694 - 17 Dec 2021

Cited by 4 | Viewed by 1898

Abstract

We consider the problem of encoding a deterministic source sequence (i.e., individual sequence) for the degraded wiretap channel by means of an encoder and decoder that can both be implemented as finite-state machines. Our first main result is a necessary condition for both reliable and secure transmission in terms of the given source sequence, the bandwidth expansion factor, the secrecy capacity, the number of states of the encoder and the number of states of the decoder. Equivalently, this necessary condition can be presented as a converse bound (i.e., a lower bound) on the smallest achievable bandwidth expansion factor. The bound is asymptotically achievable by Lempel–Ziv compression followed by good channel coding for the wiretap channel. Given that the lower bound is saturated, we also derive a lower bound on the minimum necessary rate of purely random bits needed for local randomness at the encoder in order to meet the security constraint. This bound too is achieved by the same achievability scheme. Finally, we extend the main results to the case where the legitimate decoder has access to a side information sequence, which is another individual sequence that may be related to the source sequence, and a noisy version of the side information sequence leaks to the wiretapper. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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Other

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32 pages, 1958 KiB

Open AccessTutorial

An Information-Theoretic View of Mixed-Delay Traffic in 5G and 6G

by Homa Nikbakht, Michèle Wigger, Malcolm Egan, Shlomo Shamai (Shitz), Jean-Marie Gorce and H. Vincent Poor

Entropy 2022, 24(5), 637; https://0-doi-org.brum.beds.ac.uk/10.3390/e24050637 - 30 Apr 2022

Cited by 9 | Viewed by 2303

Abstract

Fifth generation mobile communication systems (5G) have to accommodate both Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) services. While eMBB applications support high data rates, URLLC services aim at guaranteeing low-latencies and high-reliabilities. eMBB and URLLC services are scheduled on the same frequency band, where the different latency requirements of the communications render their coexistence challenging. In this survey, we review, from an information theoretic perspective, coding schemes that simultaneously accommodate URLLC and eMBB transmissions and show that they outperform traditional scheduling approaches. Various communication scenarios are considered, including point-to-point channels, broadcast channels, interference networks, cellular models, and cloud radio access networks (C-RANs). The main focus is on the set of rate pairs that can simultaneously be achieved for URLLC and eMBB messages, which captures well the tension between the two types of communications. We also discuss finite-blocklength results where the measure of interest is the set of error probability pairs that can simultaneously be achieved in the two communication regimes. Full article

(This article belongs to the Special Issue Wireless Networks: Information Theoretic Perspectives Ⅱ)

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