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Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP)

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 8199

Special Issue Editors

Special Issue Information

Dear Colleagues,

The 43rd (2020) to 45th (2022) International Conference on Telecommunications and Signal Processing (TSP - http://tsp.vutbr.cz/) have been organized virtually by eighteen universities from the Czech Republic, Hungary, Turkey, Croatia, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Romania, Slovenia, Greece, and Poland, for academics, researchers, and developers. This conference serves as a premier annual international forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors worldwide. Authors of selected high-quality research papers will be invited to submit their extended versions for publishing in the Special Issue, "Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP)" in Applied Sciences.

Prof. Dr. Norbert Herencsar
Prof. Dr. Francesco Benedetto
Prof. Dr. Jorge Crichigno
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.

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Keywords

  • telecommunications
  • information systems
  • network services
  • network technologies
  • telecommunication systems
  • simulation and measurement
  • analog signal processing
  • audio signal processing
  • biomedical signal processing
  • digital signal processing
  • image and video signal processing
  • speech and language processing

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Published Papers (4 papers)

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Research

36 pages, 5560 KiB  
Article
Game Theory-Based Load-Balancing Algorithms for Small Cells Wireless Backhaul Connections
by Zsolt Alfred Polgar and Mihaly Varga
Appl. Sci. 2023, 13(3), 1485; https://doi.org/10.3390/app13031485 - 23 Jan 2023
Viewed by 1491
Abstract
5G wireless networks have as one of the main characteristics the large-scale deployment of small cells (microcells, picocells, etc.), which is expected to bring several advantages in what concerns the high speed and low latency connectivity of the users. This large-scale deployment of [...] Read more.
5G wireless networks have as one of the main characteristics the large-scale deployment of small cells (microcells, picocells, etc.), which is expected to bring several advantages in what concerns the high speed and low latency connectivity of the users. This large-scale deployment of small cells also raises several technical challenges, provisioning the backhaul connectivity being one of them. The paper considers the situations when small cells are deployed temporarily or are deployed in a vehicle transporting many passengers, situations when the traditional wired or wireless backhaul solutions could be too costly to be used. The paper proposes, as an alternative solution, the use as backhaul connections of the wireless links set up in the macro cells which cover the location of the small cell. The paper proposes several Game Theory (GT)-based Load-Balancing (LB) algorithms for distributing the traffic of the small cell users over the macro cell links. The proposed LB algorithms are evaluated by computer simulations and are compared with “classical” LB algorithms considered as references. The performed computer simulations show that the auction-based algorithms have the best performance in terms of delay suffered by the transmitted data packets, while the selfish routing type algorithm has weaker performance, even behaving poorly than some of the reference non-GT-based algorithms. The paper also considers the situation when several small cell APs are deployed in a limited area or a vehicle and the user groups that attach to different APs should be identified. The paper proposes two GT-based user clustering algorithms, and the performance of these algorithms are evaluated by computer simulations. These simulations show that even simple clustering algorithms could improve the distribution of the traffic over the neighbor small cell APs and reduce the delay experienced by the data packets in the transmission system. Full article
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21 pages, 976 KiB  
Article
A Declarative Application Framework for Evaluating Advanced V2X-Based ADAS Solutions
by András Wippelhauser, András Edelmayer and László Bokor
Appl. Sci. 2023, 13(3), 1392; https://doi.org/10.3390/app13031392 - 20 Jan 2023
Cited by 5 | Viewed by 2468
Abstract
Application of Vehicular Ad Hoc Networks (VANETs) aims to help in the solution of some problems that have arisen in road transportation systems via short-range, low-latency mobile communication. The application of V2X (Vehicle-to-Everything) communication technologies to the next generation of Advanced Driver Assistance [...] Read more.
Application of Vehicular Ad Hoc Networks (VANETs) aims to help in the solution of some problems that have arisen in road transportation systems via short-range, low-latency mobile communication. The application of V2X (Vehicle-to-Everything) communication technologies to the next generation of Advanced Driver Assistance Systems (ADAS) is essential to the extension of the operational design domain (ODD) of the systems to provide safe, secure, and efficient automated driving solutions. Due to the safety-critical nature of the problem, the large-scale testing of V2X enabled ADAS solutions to evaluate and measure the anticipated quality and functionality of the experimental system is of great significance. This article proposes a novel ADAS application prototyping framework, using declarative programming, built on top of the popular Artery/OMNeT++ simulator. The framework is capable of simulating V2X-enabled ADAS applications using accurate network simulation and realistic simulated traffic on real-world maps. The solution features XML descriptions for application specification. The sensor model of Artery is used to provide information to applications. By using the simulator, one can conclude the performance of the applications and discover locations, circumstances and design patterns, where design limits should apply. Full article
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18 pages, 1650 KiB  
Article
Flexible Convolver for Convolutional Neural Networks Deployment onto Hardware-Oriented Applications
by Moisés Arredondo-Velázquez, Paulo Aaron Aguirre-Álvarez, Alfredo Padilla-Medina, Alejandro Espinosa-Calderon, Juan Prado-Olivarez and Javier Diaz-Carmona
Appl. Sci. 2023, 13(1), 93; https://doi.org/10.3390/app13010093 - 21 Dec 2022
Viewed by 1805
Abstract
This paper introduces a flexible convolver capable of adapting to the different convolution layer configurations of state-of-the-art Convolution Neural Networks (CNNs). The use of two proposed programmable components achieves this adaptability. A Programmable Line Buffer (PLB) based on Programmable Shift Registers (PSRs) allows [...] Read more.
This paper introduces a flexible convolver capable of adapting to the different convolution layer configurations of state-of-the-art Convolution Neural Networks (CNNs). The use of two proposed programmable components achieves this adaptability. A Programmable Line Buffer (PLB) based on Programmable Shift Registers (PSRs) allows the generation of the required convolution masks required for each processed CNN layer. The convolution layer computing is performed through a proposed programmable systolic array configured according to the target device resources. In order to maximize the device resource usage and to achieve a shortened processing time, the filter, data, and loop parallelisms are leveraged. These characteristics allow the described architecture to be scalable and implemented on any FPGA device targeting different applications. The convolver description was written in VHDL using the Intel Cyclone V 5CSXFC6D6F31C6N device as a reference. The experimental results show that the proposed computing method allows the processing of any CNN without requiring special adaptation for a specific application since the standard convolution algorithm is used. The proposed flexible convolver achieves competitive performance compared with those reported in related works. Full article
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14 pages, 826 KiB  
Article
Evaluation of the User Adaptation in a BCI Game Environment
by Kosmas Glavas, Georgios Prapas, Katerina D. Tzimourta, Nikolaos Giannakeas and Markos G. Tsipouras
Appl. Sci. 2022, 12(24), 12722; https://doi.org/10.3390/app122412722 - 12 Dec 2022
Cited by 6 | Viewed by 1885
Abstract
Brain-computer interface (BCI) technology is a developing field of study with numerous applications. The purpose of this paper is to discuss the use of brain signals as a direct communication pathway to an external device. In this work, Zombie Jumper is developed, which [...] Read more.
Brain-computer interface (BCI) technology is a developing field of study with numerous applications. The purpose of this paper is to discuss the use of brain signals as a direct communication pathway to an external device. In this work, Zombie Jumper is developed, which consists of 2 brain commands, imagining moving forward and blinking. The goal of the game is to jump over static or moving “zombie” characters in order to complete the level. To record the raw EEG data, a Muse 2 headband is used, and the OpenViBE platform is employed to process and classify the brain signals. The Unity engine is used to build the game, and the lab streaming layer (LSL) protocol is the connective link between Muse 2, OpenViBE and the Unity engine for this BCI-controlled game. A total of 37 subjects tested the game and played it at least 20 times. The average classification accuracy was 98.74%, ranging from 97.06% to 99.72%. Finally, playing the game for longer periods of time resulted in greater control. Full article
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