Special Issue "Advanced Coding and Stochastic Signal Processing in Dense Communication Networks"

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Network Science".

Deadline for manuscript submissions: 28 February 2022.

Special Issue Editor

Prof. Dr. Jan Sykora
E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 160 00 Prague, Czech Republic
Interests: coding and information theory; stochastic signal processing; iterative and cooperative algorithms on graphs; estimation theory; physical layer network coding

Special Issue Information

Dear Colleagues,

Advanced coding and stochastic signal processing are key enabling techniques for reliable communications in dense, highly interfering wireless communication networks. The dense networks are defined as multi-node/user wireless network scenarios where mutual signal interaction is a predominant limiting factor. This situation requires that the coding and processing fully exploits the knowledge of the interaction structure and form, together with the network topology, and uses it proactively in the distributed processing algorithms on all network nodes. Frequently, these communication networks are used as a part of some control or sensing network data-processing algorithm or physical device/machinery control loop.

This Special Issue focusses on advances in the following areas:

  • Coding and processing for interference-limited dense wireless networks;
  • Network coding, physical-layer network coding, and relaying technique;
  • Channel and network state estimation and sensing for multi-node dense networks;
  • Distributed and cooperative algorithms on graphs;
  • Machine learning approaches for dense network coding and processing;
  • Network coding aided by active and smart meta-surfaces;
  • Low-latency and ultra-reliable communication;
  • Coding and processing for Non-Orthogonal Multiple Access channel;
  • Coding and processing for weakly defined channel, network and node state information;
  • Joint design of coding/processing and control and/or data-sensing network algorithms over an unreliable dense network.

Prof. Dr. Jan Sykora
Guest Editor

Manuscript Submission Information

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Keywords

  • Network coding
  • Physical layer network coding
  • Channel and network state estimation
  • Sensing for multi-node dense networks
  • Distributed and cooperative algorithms on graphs
  • Machine learning approaches for dense network coding and processing
  • Non-Orthogonal Multiple Access channel
  • Weakly-defined channel, network and node state information
  • Data sensing network algorithms

Published Papers (2 papers)

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Research

Article
Splitting Sequences for Coding and Hybrid Incremental ARQ with Fragment Retransmission
Mathematics 2021, 9(20), 2620; https://doi.org/10.3390/math9202620 - 17 Oct 2021
Viewed by 403
Abstract
This paper proposes a code defined on a finite ring pM, where pM = 2m1 is a Mersenne prime, and m is a binary size of ring elements. The code is based on a splitting sequence [...] Read more.
This paper proposes a code defined on a finite ring pM, where pM = 2m1 is a Mersenne prime, and m is a binary size of ring elements. The code is based on a splitting sequence (splitting set) S, defined for the given multiplier set E=±20, ±21,, ±2m1. The elements of E correspond to the weights of binary error patterns that can be corrected, with the bidirectional single-bit error being the representative that occurs the most. The splitting set splits the code-word into sub-words, which inspired the name splitting code. Each sub-word, provided with auxiliary control symbols that are a byproduct of the coding procedure, corrects a single symbol error. The code can be defined, with some constraints, for general Mersenne numbers as well, while the multiplier set can be adjusted for adjacent binary errors correction. The application proposed for this code is a hybrid three-stage incremental ARQ procedure that transmits the code-word in the first stage, auxiliary control symbols in the second stage, and retransmits the sub-words detected as incorrect in the third stage. At each stage, error correction can be turned on or off, keeping both the retransmission rate and residual error rate at a low level. Full article
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Article
Spectral Properties of Clipping Noise
Mathematics 2021, 9(20), 2592; https://doi.org/10.3390/math9202592 - 15 Oct 2021
Viewed by 193
Abstract
One serious disadvantage of any multicarrier-modulation technique such as orthogonal frequency division multiplexing (OFDM) is its high peak-to-average-power ratio (PAPR) which might lead to signal clipping in several scenarios. To maximize the transmit data rate, it is important to take this non-linear distortion [...] Read more.
One serious disadvantage of any multicarrier-modulation technique such as orthogonal frequency division multiplexing (OFDM) is its high peak-to-average-power ratio (PAPR) which might lead to signal clipping in several scenarios. To maximize the transmit data rate, it is important to take this non-linear distortion into account. The most common approach is based on the Bussgang theorem, which splits the distortion in a correlated part, represented by a linear damping factor, and uncorrelated additive noise. However, there are two aspects that are not correctly considered by the Bussgang theorem. Firstly, clipping noise shows a frequency-dependent power spectrum which depends on the clipping probability. Secondly, some of the clipping noise power is located outside of the transmission bandwidth, so that it does not influence the transmission quality. In this work, the Bussgang theorem is reviewed in detail and the exact power spectral density of the uncorrelated clipping noise is approximated to determine the signal-to-noise power ratio on every subcarrier separately. Although it is shown that the frequency dependence within the transmission bandwidth is relatively small, at least 36% of the uncorrelated noise power, depending on the clipping level, lays outside of the transmission band. Monte Carlo simulations validate that a simple expression for the power spectral density allows to calculate the symbol error probability of an OFDM transmission system that suffers from clipping. Furthermore, the newly found result can be used to optimize bit allocation tables in bit loading algorithms or to calculate the channel capacity. Full article
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