Telecommunications Research Research Articles

AI Telco Research: Advancements in Telecommunications Scientific Discovery

This article explores the transformative impact of Artificial Intelligence (AI) on telecommunications research and development. It examines how the integration of AI technologies is revolutionizing various aspects of the industry, including network optimization, spectrum management, and scientific discovery. The article highlights the synergy between human expertise and AI capabilities in enhancing research processes, improving data analysis, and driving innovation. Key areas of focus include AI-powered data analysis, network behavior simulation, signal processing enhancements, and the evolving nature of human-AI collaboration in telco research. The article also addresses challenges such as data privacy and algorithmic bias, while emphasizing the potential of AI to unlock new possibilities in telecommunications, from self-optimizing networks to quantum communication systems.

Trends in scientific production in telecommunications (1981–2023): a bibliometric study

Purpose: Telecommunications have evolved in response to technological advancements and regulatory changes established in law. There remains a research gap concerning universal access to communication rights, which can be addressed through a bibliometric analysis of the scientific literature. This study aimed to identify trends in telecommunications research. Accordingly, it analyzed annual scientific output, determined the most representative journals, examined prevalent keywords, highlighted the most productive authors, and identified key articles in the field.Methods: Scientific production was analyzed using the Scopus database. Documents published between 1981 and 2023 in English were included, while those not relevant to the study topic were excluded. A total of 237 documents were analyzed using the Biblioshiny interface and Microsoft Excel.Results: Annual scientific output peaked in 2021, with an annual growth of 2.91%. The most representative journal was <i>Telecommunications Policy</i>. The consolidated keywords were “communication rights,” “public service media,” “media policy,” “regulation,” and “telecommunications.” The most productive authors were Amy Sanders and Pradip Thomas. The most cited article addressed the institutional foundations of telecommunications regulation.Conclusion: There was evidence of growing scientific production in telecommunications, published in high-impact journals with an interdisciplinary approach. The main topics related to telecommunications were communication rights, regulation, and internet governance. Despite the presence of prolific authors, a need for greater collaboration in the formation of international research networks was identified.

Analysis of Managerial Efficiency According to the Support System: Based on Electronics and Telecommunications Research Institute’s Startups

Analysis of Managerial Efficiency According to the Support System: Based on Electronics and Telecommunications Research Institute’s Startups

Design and performance evaluation of a 350 m free space optical communications link for pico-macrocell backhauling

Fibreless optics or free space optical communications (FSOC) has been at the forefront of many academic research in telecommunications due to its numerous benefits of large spectrum, high-speed data transmission, security, low transmit power, unlicensed spectrum and non-interfering links. Among the technical challenges of dense deployment of small cells in heterogeneous networks (HetNet) is a flexible and cost-effective backhaul link. This paper proposes, designs, simulates and evaluates the performance of a 350 m FSOC link under different atmospheric impairments for picocell to macrocell backhauling applications. The performance of the FSOC link is assessed by evaluating bit error rate (BER), eye diagram and quality factor (Q-factor). Results obtained recommend the FSOC link deployment for pico-macrocell backhauling under the weather conditions of clear sky with/without turbulence, heavy rain, heavy haze, heavy fog and wet snow.

Threshold Switching of ALD-NbOx Films for Neuromorphic Applications

Neuromorphic architecture has been suggested as an alternative to the existing von Neumann counterpart. The neuromorphic approach allows massively parallel processing and asynchronous timing schemes with low power consumption. This work presents ALD- NbOx thin films as a potential material for neuromorphic computation. NbO2 shows metal-insulator transition which is the desired property for threshold switching (TS). However, direct forming of NbO2 is rather difficult and deposited NbOx tends predominantly to result in Nb2O5. To obtain NbO2 we used an oxygen scavenger layer of Ti to alter Nb2O5 to NbO2. After a proper electroforming process, the device with a Ti insert showed metal-insulator transition above a specific voltage, i.e., a threshold voltage, and a stable threshold switching characteristics with wide operation range, characteristics not observed in the absence of a Ti insert. The well-defined TS characteristics clearly indicated the Ti role in controlling the oxidation state of NbOx.To verify the oxidation state of NbOx, XPS depth profile analyses were used. The presence of a Ti insertion layer resulted in an increase of 10~30% in Nb4+ states, depending on the total thickness of the NbOx films, while Nb5+ states decreased. Bearing in mind practical applications, we used only CMOS-compatible materials and processes to fabricate TS devices. Our approach suggests a reliable method to fabricate NbO2 neurons.Acknowledgment: This work was supported by Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government under grant " Non-CMOS Neuromorphic Device Basic Technology." (22BB1110).

IoT Technology and Digital Upskilling Framework for Farmers in the Northern Rural Area of Thailand

One-third of Thailand’s workers are in agriculture, but the country’s agricultural GDP is still less than 10% of its total GDP. Most Thai farmers are smallholders with limited land and low incomes. To improve the agricultural GDP and the economic situation of smallholder farmers, the Thai Government has been trying for decades to encourage and support smallholder farmers to adopt modern farming methods and smart farming equipment, including digital technologies. However, the improvement is still sluggish due to a lack of an effective approach to delivering essential digital knowledge and skills, as well as investment support for smart farming equipment. These have hindered smallholder farmers’ digital farming skill progress. To address this issue, the Broadcasting and Telecommunications Research and Development Fund for Public Interest has funded a project to develop the Digital Farmer Development Framework. This framework provides essential digital knowledge, training, coaching, and fundamental resources to upgrade smallholder digital-farming literacy to become digital farmers using problem- or project-based learning approaches and collaborative blended learning theories. Bloom’s taxonomy is used as a guideline for evaluating the framework’s effectiveness. Implementation of the Digital Farmer Development Framework has shown that farmers can significantly improve their digital farming literacy and are capable of using digital technology to improve farm management and productivity. Based on Bloom classification guidelines, 100% of the farms in the project can apply digital skills and utilize fundamental smart farming equipment as well as able to evaluate and analyze data from IoT devices. Moreover, 66% can create their own smart-system solution from fundamental smart farming tools for their farm. The project has also created a digital farmer community that shares knowledge and resources with others.

An Overview of Intelligent Parking Systems

With the development of Internet technology, intelligent parking system has been developed. China's intelligent parking management platform has been connected to the front-end parking points, integrating the parking points of the original information island into a parking network. Gather parking point data into a data center to comb and comprehensive data application provide parking operators scheduling management, financial management, operation analysis, marketing management, advertising management and parking service for owners to provide parking query parking reservation, parking path navigation, electronic payment, monthly, bill inquiry, convenient parking services. The MIT study leverages third-party services to parking recommender systems and provide personalized parking space recommendations for users according to past experience of the user Telecom Research Institute. Users are able to receive parking recommendations while maintaining privacy, because parking measurements weigh practicality against privacy. An intelligent multistory management system in parking depended on RFID technology and user preference review has been studied abroad, which effectively solves the problem of parking lot.

Introducing 6G technology to support metaverse for telecommunication engineering students in Universitas Pendidikan Indonesia

Research on 6G have been started with many applications including on the support of Metaverse, where humans can interact in cyberspace with real experiences. To introduce and provide an understanding of this technology, Program Studi Sistem Telekomunikasi Universitas Pendidikan Indonesia kampus Purwakarta held a Studium Generalle with the theme of "Knowing 6G Connectivity to Support the Metaverse" which was held in a hybrid manner. This Studium Generalle was filled by Assoc. Prof. Dr. Eng. Khoirul Anwar ST., M.Eng. (Director of The University Center of Excellence for Advanced Intelligent Communications or AICOMS and Lecturer of Tel-U). Participants were given a detailed description to contribute in the field of telecommunication research, such as 6G technology mainly on machine learning and quantum information processing. Participants have their understanding measured through Pre-Test and Post-Test. There are 8 multiple choices that are used as indicators of the success of knowledge transfer between the presenters and participants. Based on the answers of 174 participants who have taken the Post-Test, the percentage accuracy of participants's answers is 45%. With the majority of participants managed to answer 5 to 8 questions accurately. Overall, the public lecture is performed well as expected. Evaluation for the next activity is that students must first learn the basic understanding of the material to be delivered so that they can follow easily the lecture. Supporting devices are needed to improve audio quality for online participants and a wider venue for activities to accommodate more offline participants.

Stance construction viathat-clauses in telecommunications research articles: a comparison of L1 and L2 expert writers

AbstractGiven the unsettled debate about the role of nativeness and/or expertise in academic writing, we compared the first language (L1)-English expert writers and the Second language (L2)-English (Chinese L1) expert writers with a similar expertise level in the use of stance complementthat-clauses. For our analysis, we selected equal numbers of published research articles written by the L1 and the L2 experts in the field of Telecommunications. We found considerable differences between the two groups of writers in terms of frequency, range, and semantic classes of words controllingthat-clauses. First, although both the L1 experts and the L2 experts overwhelmingly used verb +that-clauses, they demonstrated relatively different syntactic preferences for stance construction. The L2 experts used more verb +that-clauses than the L1 experts, while the L1 experts utilized more noun +that-clauses. Second, the L2 experts were more likely to express greater certainty towards the claims inthat-clauses than the L1 experts. Third, the L2 experts employed a narrower range of words controllingthat-clauses than the L1 experts in all the semantic classes. These findings suggest that the nativeness status of academic writers still influences their use of evaluativethat-clauses even at an advanced level.

Effects of Technology Commercialization Proactiveness on Commercialization Success: The Case of ETRI in Korea

Public technology transfer and technology commercialization are attracting worldwide attention, but the research on the commercialization of technology transferred from government-funded research institutes (GRIs) to small- and medium-sized enterprises (SMEs) is scarce. This study aims to identify and prioritize the factors contributing to the commercialization success of technologies transferred from GRIs to SMEs and to quantitatively present their importance. We proposed novel concepts of SMEs’ and GRIs’ technology commercialization proactiveness (SME TCP and GRI TCP) as two main success factors. We conducted hierarchical logistic regression analysis and decision tree analysis for 301 SME cases that adopted technology between 2013 and 2016 from Electronics and Telecommunications Research Institute (ETRI), a representative GRI in Korea. As a result, SME TCP was measured based on technology transfer expenditure (TTE), and frequency (TTF) was confirmed to be the most important factor. In particular, the success rate was higher when TTE exceeded 151 M KRW, or TTF was three or more. In addition, the success rate varied greatly depending on GRI TCP, namely the degree and the type of GRI researchers’ support. These findings can be used as primary data when establishing policies to promote cooperation between SMEs and other GRIs and provide practical implications for both technology providers and adopters.

Emotional Intelligence Impacts on Work Performance: The Case in Telecommunication Malaysia Research Company

The study of the correlation between Emotional Intelligence (EI) and work performance is crucial for the organisation. Some of the organisations do not consider EI skills as the work performed. This study investigates the correlation between EI and the work performance of a telecommunication research company in Malaysia. There are 66 participants involved in this study: senior researchers and researchers. A set of questionnaires was distributed to assess their employees’ background, EI, and work performance. As a predictor of research employees’ work performance and EI, the results show that EI had a significant positive relationship with work performance. The findings also show that employees with high EI experience a greater level of task performance. Moreover, the authors also present the relationship of EI with work performance over employees’ background such as gender, marital status, age and work experience. It was found that married employees have a higher correlation than single employees. The study recommends that organisations introduce EI development programs for existing staff to improve their performance at work.

Gavan Edmund Rosman (1934–2022)

Gavan Rosman was valued at the Telecom (later Telstra) Research Laboratories, Australia, for his expertise as a research engineer in radio and coaxial cable technologies and, in particular, for his pioneering work on optical fibre technologies. He was also valued for his wide-ranging intellect and gentle, satirical sense of humour. His fluency in speaking Japanese was appreciated by visiting Japanese researchers. In retirement from TRL, he worked at Optiscan Imaging in Melbourne on developing an optical endoscope.

Toward Integrating Intelligence and Programmability in Open Radio Access Networks: A Comprehensive Survey

Open RAN is an emerging vision and an advancement of the Radio Access Network (RAN). Its purpose is to implement a vendor and network-generation agnostic RAN, provide networking solutions across all service requests, and implement artificial intelligence solutions in different stages of an end-to-end communication path. The 5th Generation (5G) and beyond the 5th Generation (B5G) of networking introduce and support new use cases, such as tactile internet and autonomous driving. The complexity and innovative nature of these use cases require continuous innovation at a high pace in the RAN. The traditional approach of building end-to-end RAN solutions by only one vendor hampers the speed of innovation—furthermore, the lack of a standard approach to implementing artificial intelligence complicates the compatibility of products with the RAN ecosystem. O-RAN Alliance, a community of industry and academic experts in RAN, works on writing Open RAN specifications on top of the 3rd Generation Partnership Project (3GPP) standards. Founded on these specifications, the aim of this paper is to introduce open research topics in Open RAN that overlap the interests of both AI and telecommunication researchers. The paper provides an overview of the architecture and components of Open RAN, then explores AI use cases in Open RAN. Also, this survey includes some plausible AI deployment scenarios that the specifications have not covered. Open RAN in future cities creates opportunities for various use cases across different sectors, including engineering, operations, and research that this paper addresses.

3D Filmmaking for User-Selective UHD Stereoscopic Media System: A Case Study on the Film The Old, the New and the Other

Despite skepticism about commercial potential, the stereoscopic 3D cinema is still a form that any filmmaker can choose to employ for its aesthetics and its immersive potential. Based on a haptic illusion, the stereoscopic media content requires a new perspective different from the principle of 2D media content in terms of creation and acceptance. This paper examines the technical and aesthetic issues of stereoscopic 3D film production from the perspective of today’s emerging realistic and immersive media through a case study. One of the key factors for successful content creation and research and development in stereoscopic 3D cinema is the combination of artistic principles together with technical mastering of the new image technology. The purpose of this paper is to outline the principal challenges and research topics in stereoscopic 3D cinema through a case study of stereoscopic 3D pilot film production for the ‘User-Selective UHD Stereoscopic Media Service Platform’ of the ETRI (Electronics and Telecommunications Research Institute). This paper intends to examine stereoscopic 3D filmmaking workflow and production methodologies, as well as technical elements and aesthetic issues.

Antony Hewish

Antony Hewish (1924–2021) Pioneer radio astronomer and leader of the team of researchers who identified the first pulsar, remembered by Malcolm Longair. Antony (Tony) Hewish went up to Cambridge University in 1942 to read natural sciences. After his second year, however, he was sent for war service at the Telecommunications Research Establishment, Malvern, where Martin Ryle was head of the radar counter-measures group. Tony worked on devices to jam the radar systems of hostile night-fighters. Returning to Cambridge in 1946, he completed his physics degree and then joined the newly founded radio astronomy group led by Ryle at the Cavendish Laboratory. Tony specialized in the phenomenon of radio scintillation, the twinkling of radio sources caused by plasma irregularities along the line of sight to the source. In 1951–52, he worked out in detail the theory of radio source scintillation (Hewish 1952) and in 1964 the phenomenon was observed in compact radio sources (Hewish et al. 1964). These sources included the recently discovered quasars, among the most extreme examples of active galactic nuclei.

Body and Hand-Object ROI-Based Behavior Recognition Using Deep Learning.

Behavior recognition has applications in automatic crime monitoring, automatic sports video analysis, and context awareness of so-called silver robots. In this study, we employ deep learning to recognize behavior based on body and hand–object interaction regions of interest (ROIs). We propose an ROI-based four-stream ensemble convolutional neural network (CNN). Behavior recognition data are mainly composed of images and skeletons. The first stream uses a pre-trained 2D-CNN by converting the 3D skeleton sequence into pose evolution images (PEIs). The second stream inputs the RGB video into the 3D-CNN to extract temporal and spatial features. The most important information in behavior recognition is identification of the person performing the action. Therefore, if the neural network is trained by removing ambient noise and placing the ROI on the person, feature analysis can be performed by focusing on the behavior itself rather than learning the entire region. Therefore, the third stream inputs the RGB video limited to the body-ROI into the 3D-CNN. The fourth stream inputs the RGB video limited to ROIs of hand–object interactions into the 3D-CNN. Finally, because better performance is expected by combining the information of the models trained with attention to these ROIs, better recognition will be possible through late fusion of the four stream scores. The Electronics and Telecommunications Research Institute (ETRI)-Activity3D dataset was used for the experiments. This dataset contains color images, images of skeletons, and depth images of 55 daily behaviors of 50 elderly and 50 young individuals. The experimental results showed that the proposed model improved recognition by at least 4.27% and up to 20.97% compared to other behavior recognition methods.

The Display Week 2021 Symposium Preview

The Display Week 2021 Symposium Preview

Rain Effect to A 60 GHz Broadband Wireless System’s Performance: Study Case In Purwakarta

Nowadays, world wide telecommunication researchers are developing 5G technology. One of most important key technology in 5G is Milimeter-Wave (mmWave). This study measure 60 GHz broadband wireless system performance because of it’s promising potentials. However, the use of these frequencies is quite sensitive to rain that resulting an atenuation in the channel. Therefore, this study proposes two schemes to address the problem. The first scheme is the use of QAM modulation (Quadrature Amplitude Modulation) and the second scheme is an addition of LDPC (Low Density Parity Check) code techniques. From the results of this study, by using 4-QAM modulation and LDPC coderate 1/2, the broadband wireless system’s performance on the second scheme is better compared to the first scheme with 8.33 dB Signal to Noise Ratio (SNR) value to provides BER (Bit Error Rate) 10-4

Development of a Real-Time Dynamic Weighting Method in Routing for Congestion Control: Application and Analysis

Congestion control issues have received consistent attention from several telecommunication researchers and practitioners for many years because network congestion often causes significant packet loss and delay problems. Although many suggested methods for these issues and problems can be available in telecommunication literature, there is room for improvement. This paper's primary objective is to propose a dynamic weighting method in routing to reduce congestion during peak hours by predicting incoming traffics and optimizing weights in the adjacency matrix of the routing table online. While changing weight values in the routing table, this method implicitly changes the routing path of many nodes through the congested node. As a result, the packet losses and delays can be decreased in used nodes. The main steps of this proposed framework are fourfold. First, the candidate weighing list is calculated based on the routing table of the congested node. Second, a proposed auto-adaptive framework (AAF) is used to predict congestion levels and apply the weighing list in the network node. Third, the evaluation of network congestion is then performed by the probability of packet losses due to overflowing buffers. Finally, the case study results demonstrate that the proposed AAF framework can significantly reduce network congestion.

A Novel Autonomous Profiling Method for the Next-Generation NFV Orchestrators

Currently, telecommunication research communities are striving towards the adoption of Zero-touch network and Service Management (ZSM) in Network Function Virtualisation (NFV) orchestration. Contemporary efforts on adopting Machine Learning (ML) and Artificial Intelligence (AI) have caused an upsurge of ZSM application in the VNF space. While ML and AI complement the ZSM goals for building the intelligent NFV orchestration, a deep knowledge about the resource consumption by Network Services (NSs) and its constituent Virtual Network Functions (VNFs) is required, which would enable AI and ML models to manage the available resources better and enhance user experience. In this article, we propose a Novel Autonomous Profiling ( NAP ) method that not only predicts the optimum network load a VNF can support but also estimates the required resources in terms of CPU, Memory, and Network, to meet the performance targets and workload by utilising ML techniques. Our performance evaluation results on real datasets show that the output of NAP can be used in the next generation of NFV orchestration.