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Performance Analysis of Wireless Communication Systems
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Performance Analysis of Wireless Communication Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 30 December 2024 | Viewed by 420

Special Issue Editor

Dr. Luca Rugini

E-Mail Website
Guest Editor
Department of Engineering, University of Perugia, 06125 Perugia, Italy
Interests: signal processing for wireless communications; performance analysis of wireless communications

Special Issue Information

Dear Colleagues,

Wireless communication systems are often designed with specific targets, in terms of error performance, data rate, and complexity. These three fundamental aspects, combined with the available resources (such as signal energy and bandwidth), hold crucial importance in the comparison of different communication systems. Specifically, performance analyses allow us to understand the quality of transmission and reception systems under determined channel conditions. This Special Issue focuses on the error performance of the physical layer of wireless communication systems. Two performance indicators commonly employed in the literature are the (bit/symbol/frame) error probability and the (root) mean-squared error (MSE). These indicators are often calculated using theoretical approaches only or semi-analytical methods based on a mix of theory and simulations. For this Special Issue, we welcome research that undertakes the performance analysis of new as well as existing wireless communication systems. The scope of this issue includes (but is not limited to):

  • Performance of Modulation and Coding Schemes;
  • Performance of Signal Detection and Interference Cancellation;
  • Performance of Channel Estimation and Equalization;
  • Performance of Diversity Schemes and Fading Countermeasures;
  • Performance of CDMA and Spread Spectrum Systems;
  • Performance of OFDM and Multicarrier Systems;
  • Performance of Orthogonal and NOMA Techniques;
  • Performance of MIMO and Massive MIMO Systems;
  • Performance of Space-Time Coding and Space-Time Processing;
  • Performance of Ultra-Wideband and Millimeter-wave Communications;
  • Performance of Spectrum Sensing and Spectrum Sharing;
  • Performance of Relay-aided and Cooperative Communications;
  • Performance of Internet of Things (IoT) Communications;
  • Performance of Machine-to-Machine and Devices-to-Devices communications;
  • Performance of Digital Broadcasting for audio and video (DAB, DVB);
  • Performance of Satellite Communications;
  • Performance of Underwater Communications.

Dr. Luca Rugini
Guest Editor

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. Sensors is an international peer-reviewed open access semimonthly 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

  • performance of modulation and coding schemes
  • performance of signal detection and interference cancellation
  • performance of channel estimation and equalization
  • performance of diversity schemes and fading countermeasures
  • performance of CDMA and spread spectrum systems
  • performance of OFDM and multicarrier systems
  • performance of orthogonal and NOMA techniques
  • performance of MIMO and massive MIMO systems
  • performance of space-time coding and space-time processing
  • performance of ultra-wideband and millimeter-wave communications
  • performance of spectrum sensing and spectrum sharing
  • performance of relay-aided and cooperative communications
  • performance of Internet of Things (IoT) communications
  • performance of machine-to-machine and devices-to-devices communications
  • performance of digital broadcasting for audio and video (DAB, DVB)
  • performance of satellite communications
  • performance of underwater communications

Published Papers (1 paper)

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17 pages, 1119 KiB  
Study Protocol
Network Topology Reconfiguration-Based Blind Equalization over Sensor Network
by Chi Sulin and Shimamura Tetsuya
Sensors 2024, 24(14), 4524; https://doi.org/10.3390/s24144524 - 12 Jul 2024
Viewed by 255
Abstract
Distributed in-network processing has garnered much attention due to its capability to estimate the unknown parameter of interest from noisy measurements based on a set of cooperating sensor nodes. In previous studies, distributed in-network processing mainly focused on short-distance communication systems, wherein sensor [...] Read more.
Distributed in-network processing has garnered much attention due to its capability to estimate the unknown parameter of interest from noisy measurements based on a set of cooperating sensor nodes. In previous studies, distributed in-network processing mainly focused on short-distance communication systems, wherein sensor nodes collect certain parameters of interest within their maximum communication distance. In addition, the estimation of certain parameter vectors of interest from noisy measurements, relying heavily on training signals, is achieved with a non-blind distributed estimation algorithm. However, in some applications, acquiring knowledge of training signals beforehand is difficult. Therefore, it is necessary to perform distributed estimation algorithms for receivers without training signals, a concept known as blind distributed estimation. In this paper, the generalized Sato algorithm is used to design the blind equalizer for the signal estimation. In addition, we consider extending the short-distance communication system to a long-distance communication system for an unmanned aerial vehicle (UAV) cooperating with sensor nodes in the wireless sensor network (WSN). In this scenario, the data signal is transmitted from a UAV to the WSN and is received by sensor nodes. However, the performance of the blind equalizer is susceptible to the transmission channel in long-distance communication systems. Here, we present a network topology reconfiguration approach to address the issue of distributed blind equalization. The objective of the proposed method is to discard the influence of ill-channels on the other sensor nodes by detecting ill-channels and redesigning the sensor node weights. Through computer simulation experiments, we evaluated the performance of the blind equalizer using the average mean square error (MSE) and average symbol error rate (SER). In the results of the computer simulation experiments, the blind equalizer using the proposed method outperformed the conventional methods in terms of prediction accuracy and convergence speed. Full article
(This article belongs to the Special Issue Performance Analysis of Wireless Communication Systems)
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