Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
2.7
Journals
Entropy
Special Issues
Information Theory and Coding for Wireless Communications II
entropy-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Entropy Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Information Theory and Coding for Wireless Communications II

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4803

Special Issue Editors

Prof. Dr. Predrag Ivanis

E-Mail Website
Guest Editor
School of Electrical Engineering, University of Belgrade, Belgrade 11000, Serbia
Interests: information theory; error control coding; wireless communications theory; beyond-5G mobile networks; Low-Earth-Orbit satellite networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Goran Djordjević

E-Mail Website
Guest Editor
Faculty of Electronic Engineering, University of Niš, Niš 18000, Serbia
Interests: wireless communications theory; cooperative networks; free-space optical systems; satellite communications; physical layer security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue follows the success of the first Special Issue. With this second volume, we continue to present the novel applications of information theory in wireless networks. In the past few decades, it was shown that it is possible to reach very close to the Shannon limit, by using low-density parity-check (LDPC) codes and polar codes. Iterative decoding with reduced complexity enabled the wide application of error-control coding techniques in cellular, satellite, and local wireless networks. The capacity of wireless communication systems can be further increased by applying multiple-input multiple-output (MIMO) techniques, in combination with cognitive radio concepts. On the other hand, various physical layer security procedures are designed with the aim to achieve optimal secrecy capacity.

Recent research shows that machine learning techniques can be efficiently used to optimize iterative decoders and to further improve the physical layer security paradigm. Artificial intelligence methods can be used in traffic balancing in satellite and cellular networks, as well as in the integration of satellite networks with 5G terrestrial networks, providing high data rates, high reliability, low latency, and high security. Therefore, the aim of this Special Issue is to bring together wireless communications, machine learning, and information theory communities.

We intend for this Special Issue to serve as a forum for the presentation of novel and improved techniques based on information theory concepts. In addition to the information theory analysis, based on entropy and mutual information, relevant topics include novel coding and decoding techniques that provide reliable and secure communication in wireless networks, as well as other techniques that can improve the reliability of wireless communication systems. Therefore, our focus is on both fundamental and application-specific analyses. 

We invite authors to submit previously unpublished contributions in any area related to applications of information theory in wireless communications including, but not limited to, the following subtopics:

  • Information theory in wireless systems;
  • Low-density parity-check (LDPC) codes and polar codes;
  • Iterative decoding algorithms;
  • Channel coding techniques for 5G, beyond-5G, and satellite communications;
  • Multiple-input multiple-output (MIMO) techniques;
  • Performance analysis of land mobile satellite systems;
  • Reliability analysis of Low-Earth-Orbit (LEO) satellite networks;
  • Information-theoretic analysis of cognitive radio systems;
  • Wiretap channel and secrecy capacity;
  • Information processing theory;
  • Machine learning for the physical layer communications;
  • Applications of artificial intelligence in cellular and satellite networks.

To view the first volume of this Special Issue, please see:

https://www.mdpi.com/journal/entropy/special_issues/Wirel_Commun

Prof. Dr. Predrag Ivanis
Prof. Dr. Goran T. Djordjević
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

  • 5G and 6G cellular networks
  • wireless communication networks
  • land mobile satellite systems
  • error correction coding
  • physical layer security
  • information processing theory
  • machine learning

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 1059 KiB  
Article
Design and Implementation of a Low-Complexity Multi-h CPM Receiver with Linear Phase Approximation Synchronization Algorithm
by Le Wang, Huan Wen, Xucen Wu and Qingping Song
Entropy 2023, 25(11), 1530; https://doi.org/10.3390/e25111530 - 10 Nov 2023
Viewed by 766
Abstract
Multi-h continuous phase modulation (CPM), with extremely high spectral efficiency, involves the plague of high demodulation complexity with a large number of matched filters and a complex trellis. In this paper, an efficient all-digital demodulator for multi-h continuous phase modulation (CPM) [...] Read more.
Multi-h continuous phase modulation (CPM), with extremely high spectral efficiency, involves the plague of high demodulation complexity with a large number of matched filters and a complex trellis. In this paper, an efficient all-digital demodulator for multi-h continuous phase modulation (CPM) is proposed based on a low-complexity decision-directed synchronization algorithm. Based on the maximum-likelihood estimation of the carrier phase and timing errors, we propose a reduced-complexity timing error detector with linear phase approximation (LPA) to the phase of the multi-h CPM. Compared with the traditional synchronization methods, it avoids derivative matched filtering and reduces about 2/3 of matched filters. The estimated accuracy and bit error rate (BER) performance of the LPA-based synchronization algorithm have no loss, as shown by the numerical simulation. Its stability is verified by the derived S-curve. Then, the receivers with the LPA-based synchronization for the three kinds of promising multi-h CPM are implemented on a Xilinx Kintex-7 FPGA platform. The experimental results show that the onboard tested BER of the proposed design has an ignorable loss in the numerical simulation. The implementation overhead on FPGA is significantly reduced by about 27% slices, 64% DSPs, and 70% block RAMs compared with the conventional method. Full article
(This article belongs to the Special Issue Information Theory and Coding for Wireless Communications II)
►▼ Show Figures

Figure 1

15 pages, 631 KiB  
Article
Optimizing Finite-Blocklength Nested Linear Secrecy Codes: Using the Worst Code to Find the Best Code
by Morteza Shoushtari and Willie Harrison
Entropy 2023, 25(10), 1456; https://doi.org/10.3390/e25101456 - 17 Oct 2023
Viewed by 872
Abstract
Nested linear coding is a widely used technique in wireless communication systems for improving both security and reliability. Some parameters, such as the relative generalized Hamming weight and the relative dimension/length profile, can be used to characterize the performance of nested linear codes. [...] Read more.
Nested linear coding is a widely used technique in wireless communication systems for improving both security and reliability. Some parameters, such as the relative generalized Hamming weight and the relative dimension/length profile, can be used to characterize the performance of nested linear codes. In addition, the rank properties of generator and parity-check matrices can also precisely characterize their security performance. Despite this, finding optimal nested linear secrecy codes remains a challenge in the finite-blocklength regime, often requiring brute-force search methods. This paper investigates the properties of nested linear codes, introduces a new representation of the relative generalized Hamming weight, and proposes a novel method for finding the best nested linear secrecy code for the binary erasure wiretap channel by working from the worst nested linear secrecy code in the dual space. We demonstrate that our algorithm significantly outperforms the brute-force technique in terms of speed and efficiency. Full article
(This article belongs to the Special Issue Information Theory and Coding for Wireless Communications II)
►▼ Show Figures

Figure 1

12 pages, 762 KiB  
Article
Pre-Configured Error Pattern Ordered Statistics Decoding for CRC-Polar Codes
by Xuanyu Li, Kai Niu, Yuxin Han, Jincheng Dai, Zhiyuan Tan and Zhiheng Guo
Entropy 2023, 25(10), 1405; https://doi.org/10.3390/e25101405 - 30 Sep 2023
Viewed by 710
Abstract
In this paper, we propose a pre-configured error pattern ordered statistics decoding (PEPOSD) algorithm and discuss its application to short cyclic redundancy check (CRC)-polar codes. Unlike the traditional OSD that changes the most reliable independent symbols, we regard the decoding process as testing [...] Read more.
In this paper, we propose a pre-configured error pattern ordered statistics decoding (PEPOSD) algorithm and discuss its application to short cyclic redundancy check (CRC)-polar codes. Unlike the traditional OSD that changes the most reliable independent symbols, we regard the decoding process as testing the error patterns, like guessing random additive noise decoding (GRAND). Also, the pre-configurator referred from ordered reliability bits (ORB) GRAND can better control the range and testing order of EPs. An offline–online structure can accelerate the decoding process. Additionally, we also introduce two orders to optimize the search order for testing EPs. Compared with CRC-aided OSD and list decoding, PEPOSD can achieve a better trade-off between accuracy and complexity. Full article
(This article belongs to the Special Issue Information Theory and Coding for Wireless Communications II)
►▼ Show Figures

Figure 1

17 pages, 3041 KiB  
Article
On the Effect of Imperfect Reference Signal Phase Recovery on Performance of PSK System Influenced by TWDP Fading
by Goran T. Djordjevic, Dejan N. Milic, Bata Vasic, Jarosław Makal and Bane Vasic
Entropy 2023, 25(9), 1341; https://doi.org/10.3390/e25091341 - 15 Sep 2023
Viewed by 827
Abstract
We examine the effects of imperfect phase estimation of a reference signal on the bit error rate and mutual information over a communication channel influenced by fading and thermal noise. The Two-Wave Diffuse-Power (TWDP) model is utilized for statistical characterization of propagation environment [...] Read more.
We examine the effects of imperfect phase estimation of a reference signal on the bit error rate and mutual information over a communication channel influenced by fading and thermal noise. The Two-Wave Diffuse-Power (TWDP) model is utilized for statistical characterization of propagation environment where there are two dominant line-of-sight components together with diffuse ones. We derive novel analytical expression of the Fourier series for probability density function arising from the composite received signal phase. Further, the expression for the bit error rate is presented and numerically evaluated. We develop efficient analytical, numerical and simulation methods for estimating the value of the error floor and identifying the range of acceptable signal-to-noise ratio (SNR) values in cases when the floor is present during the detection of multilevel phase-shift keying (PSK) signals. In addition, we use Monte Carlo simulations in order to evaluate the mutual information for modulation orders two, four and eight, and identify its dependence on receiver hardware imperfections under the given channel conditions. Our results expose direct correspondence between bit error rate and mutual information value on one side, and the parameters of TWDP channel, SNR and phase noise standard deviation on the other side. The results illustrate that the error floor values are strongly influenced by the phase noise when signals propagate over a TWDP channel. In addition, the phase noise considerably affects the mutual information. Full article
(This article belongs to the Special Issue Information Theory and Coding for Wireless Communications II)
►▼ Show Figures

Figure 1

18 pages, 549 KiB  
Article
Blind Source Separation of Intermittent Frequency Hopping Sources over LOS and NLOS Channels
by Anushreya Ghosh, Annan Dong, Alexander Haimovich, Osvaldo Simeone and Jason Dabin
Entropy 2023, 25(9), 1292; https://doi.org/10.3390/e25091292 - 03 Sep 2023
Viewed by 941
Abstract
This paper studies blind source separation (BSS) for frequency hopping (FH) sources. These radio frequency (RF) signals are observed by a uniform linear array (ULA) over (i) line-of-sight (LOS), (ii) single-cluster, and (iii) multiple-cluster Spatial Channel Model (SCM) settings. The sources are stationary, [...] Read more.
This paper studies blind source separation (BSS) for frequency hopping (FH) sources. These radio frequency (RF) signals are observed by a uniform linear array (ULA) over (i) line-of-sight (LOS), (ii) single-cluster, and (iii) multiple-cluster Spatial Channel Model (SCM) settings. The sources are stationary, spatially sparse, and their activity is intermittent and assumed to follow a hidden Markov model (HMM). BSS is achieved by leveraging direction of arrival (DOA) information through an FH estimation stage, a DOA estimation stage, and a pairing stage with the latter associating FH patterns with physical sources via their estimated DOAs. Current methods in the literature do not perform the association of multiple frequency hops to the sources they are transmitted from. We bridge this gap by pairing the FH estimates with DOA estimates and labeling signals to their sources, irrespective of their hopped frequencies. A state filtering technique, referred to as hidden state filtering (HSF), is developed to refine DOA estimates for sources that follow a HMM. Numerical results demonstrate that the proposed approach is capable of separating multiple intermittent FH sources. Full article
(This article belongs to the Special Issue Information Theory and Coding for Wireless Communications II)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop