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Telecom, Volume 3, Issue 1 (March 2022) – 13 articles

Cover Story (view full-size image): Building information modeling (BIM) is a critical element for the “digitalization” of the construction industry and can be exploited for energy-driven renovation procedures of residences. Advancing beyond BIM with data-capturing capabilities requires sensor data streams related to indoor/outdoor ambient conditions, as well as energy-consumption parameters of the residences. This requires deployment of robust wireless sensor networks (WSNs) able to capture and transmit real-time data to appropriate cloud-based renovation toolkits. This paper sets the lines for similar installations that are required by the construction industry for collecting dynamic data, since it is based on the outcome of real-world WSN installations in pilot sites in three European countries, carried out in the context of a major collaborative BIM research project. View this paper
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23 pages, 3325 KiB  
Article
Analysis and Estimation of Economic Influence of IoT and Telecommunication in Regional Media Based on Evolution and Electronic Markets in Romania
by Andreea Nistor and Eduard Zadobrischi
Telecom 2022, 3(1), 195-217; https://doi.org/10.3390/telecom3010013 - 4 Mar 2022
Cited by 13 | Viewed by 4744
Abstract
The interconnection of devices, intended to collect and transmit data via the Internet, is called the Internet of Things (IoT). This technology has the potential to revolutionize both the economic and industrial sectors, especially in terms of data confidentiality and information security. New [...] Read more.
The interconnection of devices, intended to collect and transmit data via the Internet, is called the Internet of Things (IoT). This technology has the potential to revolutionize both the economic and industrial sectors, especially in terms of data confidentiality and information security. New media, with a merger between those two, have increasingly replaced traditional media, but many researchers characterize them as two distinct but interconnected types of media. From the traditional media, with its technological evolution, the IoT has supported the development of the media through the emergence of applications, websites, and social networks designed to spread information worldwide. This research focuses on how the IoT has the ability to influence economic growth by trying to determine the impact of the IoT through theories and the evolution of economic growth. Thus, the concept of the IoT is interdependent on information and communications technology and, from an economic point of view, is correlated with productivity. In addition, the processes that have an impact on the media are those of an economic nature, all of which are interconnected with progress, innovation, and the promotion of goods and services. At the same time, this paper aims to determine the correlation between IoT and the economy, with a focus on the media, which has the main result of the development of new businesses. Thus, a bibliometric analysis of the scientific papers on the Web of Science platform regarding the IoT field was performed, in order to identify the current state of knowledge in this field. The results of this analysis highlighted that both the IoT and the economy are shaped by innovation, opportunities, and development. Full article
(This article belongs to the Special Issue IoT Applications and Industry 4.0: 2021)
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21 pages, 12687 KiB  
Article
3GPP 5G V2X Scenarios: Performance of QoS Parameters Using Turbo Codes
by Dimitrios Kosmanos, Costas Chaikalis and Ilias K. Savvas
Telecom 2022, 3(1), 174-194; https://doi.org/10.3390/telecom3010012 - 1 Mar 2022
Cited by 6 | Viewed by 4146
Abstract
Cellular vehicle-to-everything (C-V2X) communication has recently gained attention in industry and academia. Different implementation scenarios have been derived by the 3rd Generation Partnership Project (3GPP) 5th Generation (5G) Vehicle-to-Everything (V2X) standard, Release 16. Quality of service (QoS) is important to achieve reliable communication [...] Read more.
Cellular vehicle-to-everything (C-V2X) communication has recently gained attention in industry and academia. Different implementation scenarios have been derived by the 3rd Generation Partnership Project (3GPP) 5th Generation (5G) Vehicle-to-Everything (V2X) standard, Release 16. Quality of service (QoS) is important to achieve reliable communication and parameters which have to be considered are reliability, end-to-end latency, data rate, communication range, throughput and vehicle density for an urban area. However, it would be desirable to design a dynamic selecting system (with emphasis on channel coding parameters selection) so that all QoS parameters are satisfied. Having this idea in mind, in this work we examine nine V2X implementation scenarios using Long Term Evolution (LTE) turbo coding with a geometry−based efficient propagation model for vehicle-to-vehicle communication (GEMV), where we consider the above QoS parameters for SOVA, log-MAP and max-log-MAP decoding algorithms. Our study is suitable for 3GPP cooperative sensing, for the eight scenarios considering medium and large signal-noise-ratio (SNR) values. The proposed model is sustainable despite a doubled data rate, which results in a minimal bit error rate (BER) performance loss up to 1.85 dB. In this case tripling the data rate results in a further 1 dB loss. Moreover, a small loss up to 0.4 dB is seen for a vehicle speed increase from 60 km/h to 100 km/h. Finally, increasing vehicle density has no effect on the implemented 3GPP scenario considering end-to-end latency, irrespectively from the decoding algorithm. Full article
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11 pages, 809 KiB  
Article
Resource Allocation Using Reconfigurable Intelligent Surface (RIS)-Assisted Wireless Networks in Industry 5.0 Scenario
by Sonain Jamil, MuhibUr Rahman, Muhammad Sohail Abbas and Fawad
Telecom 2022, 3(1), 163-173; https://doi.org/10.3390/telecom3010011 - 1 Mar 2022
Cited by 6 | Viewed by 3292
Abstract
Mobile communication networks evolved from first-generation (1G) to sixth-generation (6G) and the requirement for quality of services (QoS) and higher bandwidth increased. The evolvement of 6G can be deployed in industry 5.0 to fulfill the future industry requirement. However, deploying 6G in industry [...] Read more.
Mobile communication networks evolved from first-generation (1G) to sixth-generation (6G) and the requirement for quality of services (QoS) and higher bandwidth increased. The evolvement of 6G can be deployed in industry 5.0 to fulfill the future industry requirement. However, deploying 6G in industry 6.0 is very challenging, and installing a reconfigurable intelligent surface (RIS) is an efficient solution. RIS contains the passive elements which are programmed for the tuning of a wireless channel. We formulate an optimization problem to allocate resources in the RIS-supported network. This article presents a mixed-integer non-linear programable problem (MINLP) considering the industry 5.0 scenario and proposes a novel algorithm to solve the optimization problem. We obtain the ϵ optimal solution using the proposed algorithm. The proposed algorithm is evaluated in energy efficiency (EE), throughput, latency, and channel allocation. We compare the performance of several algorithms, and the proposed algorithm outperforms all the algorithms. Full article
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13 pages, 3450 KiB  
Article
Can the WiMAX IEEE 802.16 Standard Be Used to Resolve Last-Mile Connectivity Issues in Botswana?
by Malebogo Mokeresete and Bukohwo Michael Esiefarienrhe
Telecom 2022, 3(1), 150-162; https://doi.org/10.3390/telecom3010010 - 8 Feb 2022
Cited by 3 | Viewed by 3235
Abstract
Some of the advantages of using Worldwide Interoperability Microwave Access (WiMAX) technology at the last-mile level as an access technology include an extensive range of 50 km Line of Sight (LOS), 5 to 15 km Non-Line of Sight, and fewer infrastructure installations compared [...] Read more.
Some of the advantages of using Worldwide Interoperability Microwave Access (WiMAX) technology at the last-mile level as an access technology include an extensive range of 50 km Line of Sight (LOS), 5 to 15 km Non-Line of Sight, and fewer infrastructure installations compared to other wireless broadband access technologies. Despite positive investments in ICT fiber infrastructure by developing countries, including Botswana, servicing end-users is subjected to high prices and service disparities. The alternative, the Wi-Fi hotspot initiative by the Botswana government, falls short as a solution for last-mile connectivity and access. This study used OPNET simulation Modeler 14.5 to investigate whether Botswana’s national broadband project could adopt WiMAX IEEE 802.16e as an access technology. Therefore, using the experimental method, the simulation evaluated the WiMAX IEEE 802.16e/m over three subscriber locations in Botswana. The results obtained indicate that the deployment of the WiMAX IEEE 802.16e standard can solve most of the deployment issues and access at the last-mile level. Although the findings suggest that WiMAX IEEE 802.16e is more suitable for high-density areas, it could also solve rural areas’ infrastructure development challenges and provide the required high-speed connectivity access. However, unlike the Wi-Fi initiative, which requires more infrastructure deployment and relies less on institutional and regulatory frameworks, the deployment of WiMAX IEEE 802.16e necessitates institutional and regulatory standards. Full article
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14 pages, 1665 KiB  
Article
Channel Modeling for In-Body Optical Wireless Communications
by Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Nestor D. Chatzidiamantis and George K. Karagiannidis
Telecom 2022, 3(1), 136-149; https://doi.org/10.3390/telecom3010009 - 4 Feb 2022
Cited by 3 | Viewed by 2431
Abstract
Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognized in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different types of tissues. In this paper, [...] Read more.
Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognized in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different types of tissues. In this paper, we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, and oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model, we formulate the complete pathloss model. The developed model is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the proposed model in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is expected to enable link budget analysis, performance analysis, and theoretical framework development, which will boost the design of optimized communication protocols for a plethora of biomedical applications. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications 2021)
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1 pages, 146 KiB  
Editorial
Acknowledgment to Reviewers of Telecom in 2021
by Telecom Editorial Office
Telecom 2022, 3(1), 135; https://doi.org/10.3390/telecom3010008 - 4 Feb 2022
Viewed by 1965
Abstract
Rigorous peer-reviews are the basis of high-quality academic publishing [...] Full article
17 pages, 4982 KiB  
Article
Wireless Sensor Networks for Building Information Modeling
by Dimitrios Kontaxis, George Tsoulos, Georgia Athanasiadou and Giorgos Giannakis
Telecom 2022, 3(1), 118-134; https://doi.org/10.3390/telecom3010007 - 2 Feb 2022
Cited by 5 | Viewed by 3678
Abstract
Building Information Modeling (BIM) is a critical element for the “digitalization” of the construction industry and can be exploited for energy-driven renovation procedures of existing residences. Advancing beyond a BIM with data-capturing capabilities that are limited to building static information only requires sensor [...] Read more.
Building Information Modeling (BIM) is a critical element for the “digitalization” of the construction industry and can be exploited for energy-driven renovation procedures of existing residences. Advancing beyond a BIM with data-capturing capabilities that are limited to building static information only requires sensor data streams related to indoor/outdoor ambient conditions, as well as to energy-consumption parameters of the residences. The data streams require the deployment of robust Wireless Sensor Networks (WSNs) that are able to capture and transmit real-time data to appropriate cloud-based renovation toolkits. The technology and topology of such networks are addressed herein. The paper sets the lines for similar installations that are required by the construction industry for collecting dynamic data, since it is based on the outcome of real-world WSN installations in pilot sites in three European countries, carried out in the context of a major collaborative BIM research project. An application example of the WSN data is also provided in the context of training occupant behavior models in order to demonstrate the use of the measured data. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications 2021)
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15 pages, 3112 KiB  
Article
Practical Demonstration of 5G NR Transport Over-Fiber System with Convolutional Neural Network
by Muhammad Usman Hadi
Telecom 2022, 3(1), 103-117; https://doi.org/10.3390/telecom3010006 - 2 Feb 2022
Cited by 6 | Viewed by 3370
Abstract
This study describes an experimental realization using digital predistortion (DPD) for a fifth generation (5G) multiband new radio (NR) optical front haul (OFH) based Radio over Fiber (RoF) link. For the performance enhancement and complexity reduction of RoF links, a novel Convolutional Neural [...] Read more.
This study describes an experimental realization using digital predistortion (DPD) for a fifth generation (5G) multiband new radio (NR) optical front haul (OFH) based Radio over Fiber (RoF) link. For the performance enhancement and complexity reduction of RoF links, a novel Convolutional Neural Network (CNN) based DPD technique is proposed, followed by comparisons with the generalised memory polynomial (GMP) based DPD method. To support enhanced mobile broad band scenario, the experimental testbed uses the 5G NR waveforms at 10 GHz with 20 MHz bandwidth and a flexible-waveform signal at 3 GHz with 20 MHz bandwidth. For 10 km of typical single mode fiber, a Mach Zehnder Modulator with two distinct radio frequency waveforms modulates a 1310 nm optical carrier utilizing distributed feedback laser. The error vector magnitude and number of estimated coefficients, and multiplications are all used to describe the experimental outcomes. The goal of the research is to see if CNN-based DPD improves performance while lowering complexity levels to meet 3GPP Release 17 criteria. Full article
(This article belongs to the Special Issue Advances in Optical Wireless Communication)
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17 pages, 1219 KiB  
Article
An Unsupervised Machine Learning Approach for UAV-Aided Offloading of 5G Cellular Networks
by Lefteris Tsipi, Michail Karavolos and Demosthenes Vouyioukas
Telecom 2022, 3(1), 86-102; https://doi.org/10.3390/telecom3010005 - 20 Jan 2022
Cited by 8 | Viewed by 3905
Abstract
Today’s terrestrial cellular communications networks face difficulties in serving coexisting users and devices due to the enormous demands of mass connectivity. Further, natural disasters and unexpected events lead to an unpredictable amount of data traffic, thus causing congestion to the network. In such [...] Read more.
Today’s terrestrial cellular communications networks face difficulties in serving coexisting users and devices due to the enormous demands of mass connectivity. Further, natural disasters and unexpected events lead to an unpredictable amount of data traffic, thus causing congestion to the network. In such cases, the addition of on-demand network entities, such as fixed or aerial base stations, has been proposed as a viable solution for managing high data traffic and offloading the existing terrestrial infrastructure. This paper presents an unmanned aerial vehicles (UAVs) aided offloading strategy of the terrestrial network, utilizing an unsupervised machine learning method for the best placement of UAVs in sites with high data traffic. The proposed scheme forms clusters of users located in the affected area using the k-medoid algorithm. Followingly, based on the number of available UAVs, a cluster selection scheme is employed to select the available UAVs that will be deployed to achieve maximum offloading in the system. Comparisons with traditional offloading strategies integrating terrestrial picocells and other UAV-aided schemes show that significant offloading, throughput, spectral efficiency, and sum rate gains can be harvested through the proposed method under a varying number of UAVs. Full article
(This article belongs to the Special Issue Machine Learning and Cognitive Networking)
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16 pages, 12639 KiB  
Article
An IoT-Based Encapsulated Design System for Rapid Model Identification of Plant Development
by Hrvoje Novak, Marko Ratković, Mateo Cahun and Vinko Lešić
Telecom 2022, 3(1), 70-85; https://doi.org/10.3390/telecom3010004 - 6 Jan 2022
Cited by 1 | Viewed by 2698
Abstract
Actual and upcoming climate changes will evidently have the largest impact on agriculture crop cultivation in terms of reduced harvest, increased costs, and necessary deviations from traditional farming. The aggravating factor for the successful applications of precision and predictive agriculture is the lack [...] Read more.
Actual and upcoming climate changes will evidently have the largest impact on agriculture crop cultivation in terms of reduced harvest, increased costs, and necessary deviations from traditional farming. The aggravating factor for the successful applications of precision and predictive agriculture is the lack of granulated historical data due to slow, year-round cycles of crops, as a prerequisite for further analysis and modeling. A methodology of plant growth observation with the rapid performance of experiments is presented in this paper. The proposed system enables the collection of data with respect to various climate conditions, which are artificially created and permuted in the encapsulated design, suitable for further correlation with plant development identifiers. The design is equipped with a large number of sensors and connected to the central database in a computer cloud, which enables the interconnection and coordination of multiple geographically distributed devices and related experiments in a remote, autonomous, and real-time manner. Over 40 sensors and up to 24 yearly harvests per device enable the yearly collection of approximately 750,000 correlated database entries, which it is possible to independently stack with higher numbers of devices. Such accumulated data is exploited to develop mathematical models of wheat in different growth stages by applying the concepts of artificial intelligence and utilizing them for the prediction of crop development and harvest. Full article
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18 pages, 582 KiB  
Article
XGB-RF: A Hybrid Machine Learning Approach for IoT Intrusion Detection
by Jabed Al Faysal, Sk Tahmid Mostafa, Jannatul Sultana Tamanna, Khondoker Mirazul Mumenin, Md. Mashrur Arifin, Md. Abdul Awal, Atanu Shome and Sheikh Shanawaz Mostafa
Telecom 2022, 3(1), 52-69; https://doi.org/10.3390/telecom3010003 - 4 Jan 2022
Cited by 30 | Viewed by 5103
Abstract
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of these devices is exceedingly increasing to make our daily activities easier than ever. However, numerous security flaws persist on IoT devices due to the fact that [...] Read more.
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of these devices is exceedingly increasing to make our daily activities easier than ever. However, numerous security flaws persist on IoT devices due to the fact that the majority of them lack the memory and computing resources necessary for adequate security operations. As a result, IoT devices are affected by a variety of attacks. A single attack on network systems or devices can lead to significant damages in data security and privacy. However, machine-learning techniques can be applied to detect IoT attacks. In this paper, a hybrid machine learning scheme called XGB-RF is proposed for detecting intrusion attacks. The proposed hybrid method was applied to the N-BaIoT dataset containing hazardous botnet attacks. Random forest (RF) was used for the feature selection and eXtreme Gradient Boosting (XGB) classifier was used to detect different types of attacks on IoT environments. The performance of the proposed XGB-RF scheme is evaluated based on several evaluation metrics and demonstrates that the model successfully detects 99.94% of the attacks. After comparing it with state-of-the-art algorithms, our proposed model has achieved better performance for every metric. As the proposed scheme is capable of detecting botnet attacks effectively, it can significantly contribute to reducing the security concerns associated with IoT systems. Full article
(This article belongs to the Special Issue Machine Learning and Cognitive Networking)
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35 pages, 1648 KiB  
Article
A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks
by Natalie Temene, Charalampos Sergiou, Christiana Ioannou, Chryssis Georgiou and Vasos Vassiliou
Telecom 2022, 3(1), 17-51; https://doi.org/10.3390/telecom3010002 - 1 Jan 2022
Cited by 6 | Viewed by 3476
Abstract
The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those [...] Read more.
The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems. Full article
(This article belongs to the Special Issue IoT Applications and Industry 4.0: 2021)
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16 pages, 15390 KiB  
Article
A Novel Dual-Band Implantable Antenna for Pancreas Telemetry Sensor Applications
by Maria Matthaiou, Stavros Koulouridis and Stavros Kotsopoulos
Telecom 2022, 3(1), 1-16; https://doi.org/10.3390/telecom3010001 - 1 Jan 2022
Cited by 5 | Viewed by 2812
Abstract
In this study, a novel implantable dual-band planar inverted F-antenna (PIFA) is proposed and designed for wireless biotelemetry. The developed antenna is intended to operate on the surface of the pancreas within the Medical Device Radiocommunications Service (MedRadio 401–406 MHz) and the industrial [...] Read more.
In this study, a novel implantable dual-band planar inverted F-antenna (PIFA) is proposed and designed for wireless biotelemetry. The developed antenna is intended to operate on the surface of the pancreas within the Medical Device Radiocommunications Service (MedRadio 401–406 MHz) and the industrial scientific and medical band (ISM, 2.4–2.5 GHz). The design analysis was carried out in two steps, initially inside a canonical model representing the pancreas, based on a finite element method (FEM) numerical solver. The proposed antenna was further simulated inside the human body taking into account the corresponding dimensions of the tissues and the electrical properties at the frequencies of interest using a finite-difference time-domain (FDTD) numerical solver. Resonance, radiation performance, electrical field attenuation, total radiated power, and specific absorption rate (SAR), which determines the safety of the patient and the maximum permissible input power and other electromagnetic parameters, are presented and evaluated. Full article
(This article belongs to the Special Issue Modern Circuits and Systems Technologies on Communications 2021)
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