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ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and...
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ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 29742

Special Issue Editors

Prof. Dr. Chih-Peng Fan

E-Mail Website
Guest Editor
Department of Electrical Engineering, National Chung Hsing University, Taiwan
Interests: digital baseband transceiver design; digital image/video signal processing and system design; fast prototypes with embedded FPGA platform; digital VLSI design
Prof. Dr. Konstantinos E. Psannis

E-Mail Website
Guest Editor
Department of Applied Informatics, University of Macedonia, 54124 Thessaloniki, Greece
Interests: Internet of Things (IoT); artificial intelligence (AI); haptic communications; QoS control; big data analysis; cloud computing; digital twins
Special Issues, Collections and Topics in MDPI journals
Dr. Muh-Tian Shiue

E-Mail Website
Guest Editor
Department of Electrical Engineering, National Central University, Taiwan
Interests: signal processing; VLSI architecture and circuit design for digital communication and biomedical electronics systems
Prof. Dr. Hsi-Pin Ma

E-Mail Website
Guest Editor
Department of Electrical Engineering, National Tsing Hua University, Taiwan
Interests: biomedical electronics systems and wearable applications; biomedical signal processing and health informatics; communications system design and SoC implementation

Special Issue Information

Dear Colleagues,

We invite contributions to a Special Issue that will cover all aspects of the advanced developments and technology applications of wireless/wired communication systems, especially in algorithm/system designs, baseband circuit designs, and baseband signal processing for communications. We want to especially concentrate on the design, implementation, and practical applications for communications and baseband signal processing. This Special Issue will include the advances and methodologies that deal with solving real-world communication issues by using baseband signal processing and circuit design technologies. Papers describing advanced algorithms, systems, hardware architecture, prototypes, and VLSI designs for wireless/wired communications and general survey papers indicating next-generation communication and signal processing trends are also encouraged.

Papers describing original work are invited in any of the five areas listed below:

  1. Algorithm and system designs for wireless/wired communications;
  2. Synchronization, channel estimation, and signal processing;
  3. OFDM, MIMO, beamforming technologies, and signal processing;
  4. Hardware architectures and VLSI implementations for baseband transceiver designs;
  5. Emerging topics for communications and baseband signal processing.

This Special Issue will contain extended versions of selected papers presented at the ICCCI 2020 Conference (http://iccci.org/) held in Nagoya, Japan, 26–29 June 2020, and at the ICCCI 2021 on 25-27 June 2021.

Prof. Chih-Peng Fan
Dr. Kostas E. Psannis
Dr. Muh-Tian Shiue
Prof. Hsi-Pin Ma
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. Information 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 1600 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

  • algorithm and system designs for wireless/wired communications;
  • synchronization, channel estimation, and signal processing;
  • OFDM, MIMO, beamforming technologies, and signal processing;
  • hardware architectures and VLSI implementations for baseband transceiver designs;
  • emerging topics for communications and baseband signal processing

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

29 pages, 3251 KiB  
Article
A Proposal of the Fingerprint Optimization Method for the Fingerprint-Based Indoor Localization System with IEEE 802.15.4 Devices
by Yuanzhi Huo, Pradini Puspitaningayu, Nobuo Funabiki, Kazushi Hamazaki, Minoru Kuribayashi and Kazuyuki Kojima
Information 2022, 13(5), 211; https://doi.org/10.3390/info13050211 - 20 Apr 2022
Cited by 9 | Viewed by 2329
Abstract
Nowadays, human indoor localization services inside buildings or on underground streets are in strong demand for various location-based services. Since conventional GPS cannot be used, indoor localization systems using wireless technologies have been extensively studied. Previously, we studied a fingerprint-based indoor localization system [...] Read more.
Nowadays, human indoor localization services inside buildings or on underground streets are in strong demand for various location-based services. Since conventional GPS cannot be used, indoor localization systems using wireless technologies have been extensively studied. Previously, we studied a fingerprint-based indoor localization system using IEEE802.15.4 devices, called FILS15.4, to allow use of inexpensive, tiny, and long-life transmitters. However, due to the narrow channel band and the low transmission power, the link quality indicator (LQI) used for fingerprints easily fluctuates by human movements and other uncontrollable factors. To improve the localization accuracy, FILS15.4 restricts the detection granularity to one room in the field, and adopts multiple fingerprints for one room, considering fluctuated signals, where their values must be properly adjusted. In this paper, we present a fingerprint optimization method for finding the proper fingerprint parameters in FILS15.4 by extending the existing one. As the training phase using the measurement LQI, it iteratively changes fingerprint values to maximize the newly defined score function for the room detecting accuracy. Moreover, it automatically increases the number of fingerprints for a room if the accuracy is not sufficient. For evaluations, we applied the proposed method to the measured LQI data using the FILS15.4 testbed system in the no. 2 Engineering Building at Okayama University. The validation results show that it improves the average detection accuracy (at higher than 97%) by automatically increasing the number of fingerprints and optimizing the values. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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25 pages, 41720 KiB  
Article
Constructing a Real-Time Value-Chain Integration Architecture for Mass Individualized Juice Production
by Jen Hin Hang, Donovan Sheldon Charles, Zheng Hung Gan, Sze Kai Gan, Yee Mei Lim, Wah Pheng Lee, Thein Lai Wong and Ching Pang Goh
Information 2022, 13(2), 56; https://doi.org/10.3390/info13020056 - 23 Jan 2022
Cited by 1 | Viewed by 3568
Abstract
Mass individualized production refers to the mass production of individualized products. It becomes important for delivering a personalized customer experience in the Industrial Revolution 4.0 era. Developing seamless value chain integration between enterprises to achieve mass individualized production is challenging. Based on Reference [...] Read more.
Mass individualized production refers to the mass production of individualized products. It becomes important for delivering a personalized customer experience in the Industrial Revolution 4.0 era. Developing seamless value chain integration between enterprises to achieve mass individualized production is challenging. Based on Reference Architecture Model Industrie 4.0 (RAMI 4.0), this paper aims to address two major challenges, which are asset modeling and integration, and data communication and brokering in a value chain data exchange ecosystem. This paper proposes a communication architecture that enables both vertical and horizontal value-chain integration. A proof-of-concept is built, which involves two stakeholders. The first is the individualized juice online ordering system, named PEC, and the second is a highly automated individualized mixed juice production manufacturing line, named OMIS. Three different tests are conducted in the experiments. The first is to test the creation of assets wrapped in the asset administration shell. The second is to test the connectivity between the Asset Brokering Manager (ABM) Connector and the ABM Portal. Last is to test the connectivity performance between two Asset Administration Systems. As a result, the experiments successfully created the asset instance data accurately, and the data were published in the ABM Portal for subscription by PEC and OMIS. The connectivity tests from OMIS to PEC, and vice versa, were successful, with the time taken of 114 and 121 ms, respectively. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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15 pages, 6592 KiB  
Article
Three-Dimensional LiDAR Decoder Design for Autonomous Vehicles in Smart Cities
by Yu-Cheng Fan and Sheng-Bi Wang
Information 2022, 13(1), 18; https://doi.org/10.3390/info13010018 - 4 Jan 2022
Cited by 4 | Viewed by 3081
Abstract
With the advancement of artificial intelligence, deep learning technology is applied in many fields. The autonomous car system is one of the most important application areas of artificial intelligence. LiDAR (Light Detection and Ranging) is one of the most critical components of self-driving [...] Read more.
With the advancement of artificial intelligence, deep learning technology is applied in many fields. The autonomous car system is one of the most important application areas of artificial intelligence. LiDAR (Light Detection and Ranging) is one of the most critical components of self-driving cars. LiDAR can quickly scan the environment to obtain a large amount of high-precision three-dimensional depth information. Self-driving cars use LiDAR to reconstruct the three-dimensional environment. The autonomous car system can identify various situations in the vicinity through the information provided by LiDAR and choose a safer route. This paper is based on Velodyne HDL-64 LiDAR to decode data packets of LiDAR. The decoder we designed converts the information of the original data packet into X, Y, and Z point cloud data so that the autonomous vehicle can use the decoded information to reconstruct the three-dimensional environment and perform object detection and object classification. In order to prove the performance of the proposed LiDAR decoder, we use the standard original packets used for the comparison of experimental data, which are all taken from the Map GMU (George Mason University). The average decoding time of a frame is 7.678 milliseconds. Compared to other methods, the proposed LiDAR decoder has higher decoding speed and efficiency. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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15 pages, 932 KiB  
Article
The Use of Information and Communication Technology (ICT) in the Implementation of Instructional Supervision and Its Effect on Teachers’ Instructional Process Quality
by Bambang Budi Wiyono, Agus Wedi, Saida Ulfa and Arda Purnama Putra
Information 2021, 12(11), 475; https://doi.org/10.3390/info12110475 - 16 Nov 2021
Cited by 7 | Viewed by 6186
Abstract
This study aimed to explore communication techniques based on the information and communication technology (ICT) used in the implementation of instructional supervision to determine their effect on the teacher’s learning process and find effective techniques to improve the quality of the teacher’s learning [...] Read more.
This study aimed to explore communication techniques based on the information and communication technology (ICT) used in the implementation of instructional supervision to determine their effect on the teacher’s learning process and find effective techniques to improve the quality of the teacher’s learning process. This research was conducted in Blitar City with a sample of 60 teachers through a random sampling technique. The data collection technique used a rating scale, checklist, and open-form questionnaire. Descriptive statistics were used to describe the data, while the Pearson product-moment correlation techniques and multiple regression were used to test the research hypotheses. The results show that the most widely used ICT-based communication techniques are WhatsApp, Google Meet, Zoom, Skype, and Google Forms. These are followed by email, video-recording, and audio-recording techniques. The use of ICT is still rare. There is a significant relationship between the use of ICT in instructional supervision and the quality of the teacher’s teaching-learning process, except when using telephones and televisions. ICT techniques are most commonly used for synchronous communication, followed by use for sharing information, and recording activities. The use of ICT in instructional supervision simultaneously affects the teacher’s instructional process. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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16 pages, 549 KiB  
Article
Classification of Relaxation and Concentration Mental States with EEG
by Shingchern D. You
Information 2021, 12(5), 187; https://doi.org/10.3390/info12050187 - 26 Apr 2021
Cited by 12 | Viewed by 6566
Abstract
In this paper, we study the use of EEG (Electroencephalography) to classify between concentrated and relaxed mental states. In the literature, most EEG recording systems are expensive, medical-graded devices. The expensive devices limit the availability in a consumer market. The EEG signals are [...] Read more.
In this paper, we study the use of EEG (Electroencephalography) to classify between concentrated and relaxed mental states. In the literature, most EEG recording systems are expensive, medical-graded devices. The expensive devices limit the availability in a consumer market. The EEG signals are obtained from a toy-grade EEG device with one channel of output data. The experiments are conducted in two runs, with 7 and 10 subjects, respectively. Each subject is asked to silently recite a five-digit number backwards given by the tester. The recorded EEG signals are converted to time-frequency representations by the software accompanying the device. A simple average is used to aggregate multiple spectral components into EEG bands, such as α, β, and γ bands. The chosen classifiers are SVM (support vector machine) and multi-layer feedforward network trained individually for each subject. Experimental results show that features, with α+β+γ bands and bandwidth 4 Hz, the average accuracy over all subjects in both runs can reach more than 80% and some subjects up to 90+% with the SVM classifier. The results suggest that a brain machine interface could be implemented based on the mental states of the user even with the use of a cheap EEG device. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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14 pages, 416 KiB  
Article
A Modular Design Concept for Shaping Future Wireless TSN Solutions
by Christoph Fischer, Dennis Krummacker, Michael Karrenbauer and Hans Dieter Schotten
Information 2021, 12(1), 12; https://doi.org/10.3390/info12010012 - 30 Dec 2020
Cited by 8 | Viewed by 3205
Abstract
The use of wireless communication systems in industrial environments is gaining international importance. The requirements, which are placed thereby on the communication systems, are manifold depending on the specific use. In the field of industrial manufacturing, however, many applications are characterized by high [...] Read more.
The use of wireless communication systems in industrial environments is gaining international importance. The requirements, which are placed thereby on the communication systems, are manifold depending on the specific use. In the field of industrial manufacturing, however, many applications are characterized by high reliability requirements and hard real-time demands. The latter requires a time-deterministic handling of processed transmissions and therefore requires the use of Time-Sensitive Networking (TSN) solutions. In this paper, we briefly describe which functionalities characterize a wireless TSN system and which approaches have already been pursued in the literature and standardization. Subsequently, we present a concept for a toolbox that allows one to combine the required functionalities into a working solution, which can be used as a guideline for software-based implementation. Additionally, since reliability of transmissions is one of the key challenges, especially in wireless communication, to achieve a performance comparable to wired systems, we provide some further design considerations to improve. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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12 pages, 742 KiB  
Article
Comparative Study of Dimensionality Reduction Techniques for Spectral–Temporal Data
by Shingchern D. You and Ming-Jen Hung
Information 2021, 12(1), 1; https://doi.org/10.3390/info12010001 - 22 Dec 2020
Cited by 6 | Viewed by 2872
Abstract
This paper studies the use of three different approaches to reduce the dimensionality of a type of spectral–temporal features, called motion picture expert group (MPEG)-7 audio signature descriptors (ASD). The studied approaches include principal component analysis (PCA), independent component analysis (ICA), and factor [...] Read more.
This paper studies the use of three different approaches to reduce the dimensionality of a type of spectral–temporal features, called motion picture expert group (MPEG)-7 audio signature descriptors (ASD). The studied approaches include principal component analysis (PCA), independent component analysis (ICA), and factor analysis (FA). These approaches are applied to ASD features obtained from audio items with or without distortion. These low-dimensional features are used as queries to a dataset containing low-dimensional features extracted from undistorted items. Doing so, we may investigate the distortion-resistant capability of each approach. The experimental results show that features obtained by the ICA or FA reduction approaches have higher identification accuracy than the PCA approach for moderately distorted items. Therefore, to extract features from distorted items, ICA or FA approaches should also be considered in addition to the PCA approach. Full article
(This article belongs to the Special Issue ICCCI 2020&2021: Advances in Baseband Signal Processing, Circuit Designs, and Communications)
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