Hasil untuk "Cellular telephone services industry. Wireless telephone industry"

Bander Al-Zahrani, Omar Sami Oubbati, A. Barnawi et al.

Abstract Unmanned Aerial Vehicles (UAVs) are an emerging technology with the potential to be used in industries and various sectors of human life to provide a wide range of applications and services. During the last decade, there has been a growing focus of research in the UAV's assistance paradigm as a fundamental concept resulting in the constant improvement between different kinds of ground networks and the hovering UAVs in the sky. Recently, the wide availability of embedded wireless interfaces in the communicating entities has allowed the deployment of such a paradigm simpler and easiest. Moreover, due to UAVs' controlled mobility and adjustable altitudes, they can be considered as the most appropriate candidate to enhance the performance and overcome the restrictions of ground networks. This comprehensive survey both studies and summarizes the existing UAV-assisted research, such as routing, data gathering, cellular communications, Internet of Things (IoT) networks, and disaster management that supports existing enabling technologies. Descriptions, classifications, and comparative studies related to different UAV-assisted proposals are presented throughout the paper. By pointing out numerous future challenges, it is expected to simulate research in this emerging and hot research area. To the best of our knowledge, there are many survey papers on the topic from a technology perspective. Nevertheless, this survey can be considered as the first attempt at a comprehensive analysis of different types of existing UAV-assisted networks and describes the state-of-the-art in UAV-assisted research.

Leonardo Bonati, Michele Polese, Salvatore D’oro et al.

Abstract Fifth generation (5G) cellular networks will serve a wide variety of heterogeneous use cases, including mobile broadband users, ultra-low latency services and massively dense connectivity scenarios. The resulting diverse communication requirements will demand networking with unprecedented flexibility, not currently provided by the monolithic black-box approach of 4G cellular networks. The research community and an increasing number of standardization bodies and industry coalitions have recognized softwarization, virtualization, and disaggregation of networking functionalities as the key enablers of the needed shift to flexibility. Particularly, software-defined cellular networks are heralded as the prime technology to satisfy the new application-driven traffic requirements and to support the highly time-varying topology and interference dynamics, because of their openness through well-defined interfaces, and programmability, for swift and responsive network optimization. Leading the technological innovation in this direction, several 5G software-based projects and alliances have embraced the open source approach, making new libraries and frameworks available to the wireless community. This race to open source softwarization, however, has led to a deluge of solutions whose interoperability and interactions are often unclear. This article provides the first cohesive and exhaustive compendium of recent open source software and frameworks for 5G cellular networks, with a full stack and end-to-end perspective. We detail their capabilities and functionalities focusing on how their constituting elements fit the 5G ecosystem, and unravel the interactions among the surveyed solutions. Finally, we review hardware and testbeds on which these frameworks can run, and provide a critical perspective on the limitations of the state-of-the-art, as well as feasible directions toward fully open source, programmable 5G networks.

D. Goodman, N. Mandayam

Oluwaseyi Giwa, Tobi Awodunmila, Muhammad Ahmed Mohsin et al.

The dynamic allocation of spectrum in 5G / 6G networks is critical to efficient resource utilization. However, applying traditional deep reinforcement learning (DRL) is often infeasible due to its immense sample complexity and the safety risks associated with unguided exploration, which can cause severe network interference. To address these challenges, we propose a meta-learning framework that enables agents to learn a robust initial policy and rapidly adapt to new wireless scenarios with minimal data. We implement three meta-learning architectures, model-agnostic meta-learning (MAML), recurrent neural network (RNN), and an attention-enhanced RNN, and evaluate them against a non-meta-learning DRL algorithm, proximal policy optimization (PPO) baseline, in a simulated dynamic integrated access/backhaul (IAB) environment. Our results show a clear performance gap. The attention-based meta-learning agent reaches a peak mean network throughput of 48 Mbps, while the PPO baseline decreased drastically to 10 Mbps. Furthermore, our method reduces SINR and latency violations by more than 50% compared to PPO. It also shows quick adaptation, with a fairness index 0.7, showing better resource allocation. This work proves that meta-learning is a very effective and safer option for intelligent control in complex wireless systems.

Francesco Chiti, Simone Morosi, Claudio Bartoli

The Internet of Things has now become an integral part of the most competitive industries, as it enables optimization of production processes, reduction of operating costs and maintenance time, and improvement of the quality of products and services. More specifically the term Industrial Internet of Things (IIoT) identifies the system which consists of advanced Internet-connected equipment and analytics platforms that process the products in industrial activities. IIoT devices range from small environmental sensors to complex industrial robots. Fifth generation (5G) cellular networks represent an enabling technology for the full development of the IIoT, as they realize the infrastructure on which clusters of smart devices rely to interconnect and manage the exchange of data with the various control processes and databases containing the information necessary for their proper operation. This paper presents the design of a high-level network architecture for managing information flows generated by multiple clusters of sensors and actuators: the proposed architecture is based on a Network Slicing approach and applied to an Industry 4.0 context where wireless subnetworks are interconnected via 5G access points and data routing is managed by an SDN Controller. The proposed system is emulated by means of two distinct real time frameworks, one for 5G network and the other for SDN network simulation. The obtained results demonstrate that the proposed approach that is coherent with 5G characteristics, allows to distribute the available resources more efficiently and afford improved performance in terms of connectivity, energy efficiency, end-to-end latency and throughput. In addition its scalability, modularity and flexibility are assessed, making it a general tool to test novel applications and more complex scenarios.

Gaoyang Pang, Wanchun Liu, Dusit Niyato et al.

Wireless Human-Machine Collaboration (WHMC) represents a critical advancement for Industry 5.0, enabling seamless interaction between humans and machines across geographically distributed systems. As the WHMC systems become increasingly important for achieving complex collaborative control tasks, ensuring their stability is essential for practical deployment and long-term operation. Stability analysis certifies how the closed-loop system will behave under model randomness, which is essential for systems operating with wireless communications. However, the fundamental stability analysis of the WHMC systems remains an unexplored challenge due to the intricate interplay between the stochastic nature of wireless communications, dynamic human operations, and the inherent complexities of control system dynamics. This paper establishes a fundamental WHMC model incorporating dual wireless loops for machine and human control. Our framework accounts for practical factors such as short-packet transmissions, fading channels, and advanced HARQ schemes. We model human control lag as a Markov process, which is crucial for capturing the stochastic nature of human interactions. Building on this model, we propose a stochastic cycle-cost-based approach to derive a stability condition for the WHMC system, expressed in terms of wireless channel statistics, human dynamics, and control parameters. Our findings are validated through extensive numerical simulations and a proof-of-concept experiment, where we developed and tested a novel wireless collaborative cart-pole control system. The results confirm the effectiveness of our approach and provide a robust framework for future research on WHMC systems in more complex environments.

W. Lehr, Fabian Queder, Justus Haucap

Abstract The transition to 5G has the potential to significantly disrupt the competitive landscape for wireless services. For Mobile Network Operators (MNOs), 5G represents the next generation of cellular technology. However, the order-of-magnitude performance improvements targeted by 5G, its design philosophy that embraced a wider range of contributors than participated in the development of earlier generations of cellular technology, and by its focus on expanding the range of markets to be addressed by cellular technologies, 5G represents a paradigm shift. It is more of a tool-box of capabilities than a one-size-fits-all technology. This paper compares and contrasts 5G with earlier generations of cellular and related wireless technologies and examines how the economic forces that have shaped the MNO industry heretofore are changed with 5G. This examination highlights the potential for new business models and competition to disrupt the wireless industry in coming years.

Ellie Zontou

The evolution of cellular networks has played a pivotal role in shaping the modern telecommunications landscape. This paper explores the journey of cellular network generations, beginning with the introduction of Japan's first commercial 1G network by Nippon Telegraph and Telephone (NTT) Corporation in 1979. This analog wireless network quickly expanded to become the country's first national 1G network within a remarkably short period. The transition from analog to digital networks marked a significant turning point in the wireless industry, enabled by advancements in MOSFET (Metal-Oxide-Semiconductor Field Effect Transistor) technology. MOSFET, originally developed at Bell Labs in 1959, underwent modifications to suit cellular networks in the early 1990s, facilitating the shift to digital wireless mobile networks. The advent of the 2G generation brought forth the first commercial digital cellular network in 1991, sparking recognition among manufacturers and mobile network operators of the importance of robust networks and efficient architecture. As the wireless industry continued to experience exponential growth, the significance of effective network infrastructure became increasingly evident. In this research, our aim is to provide a comprehensive overview of the entire spectrum of cellular network generations, ranging from 1G to the potential future of 7G. By tracing the evolution of these networks, we aim to shed light on the transformative developments that have shaped the telecommunications landscape and explore the possibilities that lie ahead in the realm of cellular technology.

Daniel Philip Venmani, Fares Zerradi, Fatiha Hamma et al.

Traditionally, the production efficiency of a factory floor is evaluated using non-real time objective functions. These are based on scheduling punctuality criteria such as 'earliness (a measure of finishing operations ahead of schedule)' and 'tardiness (a measure of delay in executing certain operations)'. With process automation becoming more and more inevitable due to the emergence of Industry 4.0 / Industry 5.0, real-time objective functions are also gaining popularity. One such criterion is 'synchronization' or 'timing'. In this article, an IoT enabled real-time synchronization approach is presented in the context of Integrated Industrial Internet of Things (IIoT) from a service provider's perspective. A new business and operational model, termed as "Timing-As-A-Service (TAAS)", is introduced. In this model, the role of a service provider is to "supply" synchronization from the mobile networks to the IIoT domain.

Yan Liu, Fucheng Guo

Time difference of arrival (TDOA) and frequency difference of arrival (FDOA) have been widely used for localizing temporally continuous signals passively. Temporal sparsity of pulse signals makes their TDOA and FDOA estimation processes much different, and computational complexity is a major concern in this area. This paper addresses the problem of fast TDOA and FDOA estimation of pulse signals and focuses mainly on narrowband coherent pulses. By decoupling the effects of TDOA and FDOA in the cost function of localization approximately, we propose a fast coarse TDOA and FDOA estimation method. The estimates are then refined with the cross-ambiguity function (CAF) algorithm within a small TDOA and FDOA neighborhood. In the simulations, the proposed method is demonstrated to have satisfying TDOA and FDOA estimation precisions, and it exceeds existing counterparts largely in computational efficiency.

Marcos Faundez-Zanuy, Jose Juan Lucena-Molina, Martin Hagmueller

In this article, the authors discuss the problem of forensic authentication of digital audio recordings. Although forensic audio has been addressed in several articles, the existing approaches are focused on analog magnetic recordings, which are less prevalent because of the large amount of digital recorders available on the market (optical, solid state, hard disks, etc.). An approach based on digital signal processing that consists of spread spectrum techniques for speech watermarking is presented. This approach presents the advantage that the authentication is based on the signal itself rather than the recording format. Thus, it is valid for usual recording devices in police-controlled telephone intercepts. In addition, our proposal allows for the introduction of relevant information such as the recording date and time and all the relevant data (this is not always possible with classical systems). Our experimental results reveal that the speech watermarking procedure does not interfere in a significant way with the posterior forensic speaker identification.

Boning Li, Gunjan Verma, Santiago Segarra

We develop a novel graph-based trainable framework to maximize the weighted sum energy efficiency (WSEE) for power allocation in wireless communication networks. To address the non-convex nature of the problem, the proposed method consists of modular structures inspired by a classical iterative suboptimal approach and enhanced with learnable components. More precisely, we propose a deep unfolding of the successive concave approximation (SCA) method. In our unfolded SCA (USCA) framework, the originally preset parameters are now learnable via graph convolutional neural networks (GCNs) that directly exploit multi-user channel state information as the underlying graph adjacency matrix. We show the permutation equivariance of the proposed architecture, which is a desirable property for models applied to wireless network data. The USCA framework is trained through a stochastic gradient descent approach using a progressive training strategy. The unsupervised loss is carefully devised to feature the monotonic property of the objective under maximum power constraints. Comprehensive numerical results demonstrate its generalizability across different network topologies of varying size, density, and channel distribution. Thorough comparisons illustrate the improved performance and robustness of USCA over state-of-the-art benchmarks.

Md Tahmid Rahman Laskar, Cheng Chen, Xue-Yong Fu et al.

Telephone transcription data can be very noisy due to speech recognition errors, disfluencies, etc. Not only that annotating such data is very challenging for the annotators, but also such data may have lots of annotation errors even after the annotation job is completed, resulting in a very poor model performance. In this paper, we present an active learning framework that leverages human in the loop learning to identify data samples from the annotated dataset for re-annotation that are more likely to contain annotation errors. In this way, we largely reduce the need for data re-annotation for the whole dataset. We conduct extensive experiments with our proposed approach for Named Entity Recognition and observe that by re-annotating only about 6% training instances out of the whole dataset, the F1 score for a certain entity type can be significantly improved by about 25%.

Laveena C. Crasta, S. V T

Background/Purpose: Telecommunication is a principal element in the current technology-driven world. The impact of mobile phone services over traditional services is the key to India witnessing the Digital revolution. This paper highlights the mobile phone services that have impacted the traditional services and the digital penetration that has been observed in almost every sector. Design/Methodology/Approach: This study is mainly based on the data collected from secondary sources of information. The secondary data sources are from annual reports of the telecom sector and websites. It is an explorative research case study that shows the emergence of mobile phone services over traditional telephone services and performs PESTLE analysis. Findings/Result: Based on the study, India has moved into a digital population to a great extent through the advancements in technology and internet services through data packs and broadband connections. The mobile phone services along with the Telecom sector in India have played a crucial role in this transformation with connectivity, affordability, and technological change. Originality/Value: This paper analyzes and interprets the data collected from the past 10 years with respect to telecommunications services and mobile services in India. Based on the findings and their interpretation, new knowledge in the form of recommendations/suggestions is presented. Paper Type: Industry Analysis as a Research Case Study.

Meng Xiang, Yu Xiao, Bin Xi et al.

A wideband, low cross-polarization, high-gain, and wide-angle scanning antenna array is presented in this paper. The antenna array contains 8 subarrays in the horizontal dimension, and each subarray contains 4 unit cells. A two-side printed dipole with an amendatory equivalent circuit model is adopted, and the metal vias are introduced in the element design to ameliorate the cross-polarization level. A radome, acting as the wide-angle impedance matching layer, is introduced to achieve wide-angle scanning. A prototype of a 4 × 8 array is fabricated and measured. The results show that the operating bandwidth of aperture efficiency (BWAE) above 60% is about 26.7% from 2.6 GHz to 3.4 GHz. The measured scanning loss in the H-plane is 2.7 dB when scanning up to 60° with active voltage standing wave ratio (VSWR) <3, and the gain can achieve 21 dB at 3 GHz with a cross-polarization level below −30 dB at all angles.

Zijian Wang, Wenbo Yu, Zhongjun Yu et al.

Interrupted-sampling repeater jamming (ISRJ) is a new type of DRFM-based jamming designed for linear frequency modulation (LFM) signals. By intercepting the radar signal slice and retransmitting it many times, ISRJ can obtain radar coherent processing gain so that multiple false target groups can be formed after pulse compression (PC). According to the distribution characteristic of the echo signal and the coherence of ISRJ to radar signal, a new method for ISRJ suppression is proposed in this study. In this method, the position of the real target is determined using a gated recurrent unit neural network (GRU-Net), and the real target can be, therefore, reconstructed by adaptive filtering in the sparse representation of the echo signal based on the target locating result. The reconstruction result contains only the real target, and the false target groups formed by ISRJ are suppressed completely. The target locating accuracy of the proposed GRU-Net can reach 92.75%. Simulations have proved the effectiveness of the proposed method.

D. Kiarie

Syed Mushhad Mustuzhar Gilani, Muhammad Tamur Sultan, Zeng Shuai et al.

This study aimed to explore a metallic striped grid array planar antenna, analyze it numerically in terms of its parameters, and optimize it for best performance. It may be an appropriate candidate for long-range point-to-point connectivity in wireless sensor networks. Antenna gain and frequency impedance bandwidth are two important performance parameters. For an efficient antenna, its gain should be high while maintaining operating bandwidth wide enough to accommodate the entire frequency range for which it has been designed. Concurrently, antenna size should also be small. In this study, antenna dimensions were kept as small as possible without compromising its performance. Its dimensions were 300 mm × 210 mm × 9.9 mm, which made it compact and miniature. It had a maximum gain of 16.72 dB at 2.45 GHz and maximum frequency impedance bandwidth of 7.68% relative to 50 Ω. It operated across a frequency band ranging from 2.38 GHz to 2.57 GHz, encapsulating the entire ISM 2.4 GHz band. Its radiation efficiency remained above 93% in this band with a maximum of 98.5% at 2.45 GHz. Moreover, it also had narrow HPBWs in horizontal and vertical planes having values of 18.52° and 31.25°, respectively.

Assoule Dechaïcha, Djamel Alkama

L’étalement urbain constitue un des problèmes majeurs que connaissant les oasis du Bas-Sahara algérien. Le suivi et la compréhension de son évolution spatiale demeurent une étape essentielle dans toute démarche de développement soutenable de la ville oasienne. Les autorités locales ne disposent pas d’outils appropriés, susceptibles d’être mis à jour régulièrement, pour leur permettre d’agir efficacement en matière de planification et d’aménagement spatial. La télédétection spatiale et les Systèmes d’Information Géographique (SIG) offrent des opportunités permettant de surmonter ces difficultés. La présente étude consiste en l’application d’une technique de détection du changement pour cartographier et quantifier l’étalement spatiotemporel de la ville de Biskra (Algérie) durant la période 1985 - 2000, en utilisant des images Landsat des années 1985, 2000 et 2015. La comparaison post-classification des cartes d’occupation du sol a révélé une croissance des surfaces bâties, allant jusqu’au-delà des limites communales en conurbation avec l’agglomération de Chetma, au détriment d’un recul progressif de la palmeraie. Cette dernière a subi un processus de morcellement et de mitage par le bâti, conduisant à la perte de l’identité oasienne de la ville. L’objectif de la présente étude est de mettre en évidence le processus de l’étalement urbain et les modifications d’occupation du sol qu’il engendre. Elle montre l’importance des méthodes de détection du changement pour la compréhension des formes d’urbanisation et l’évaluation de leurs impacts sur les écosystèmes oasiens. Mots clés : Étalement urbain, ville oasienne, télédétection spatiale, SIG, détection du changement.

Vahid Garousi, Seyfettin Arkan, Gökhan Urul et al.

Context: While many companies conduct their software testing activities in-house, many other companies outsource their software testing needs to other firms who act as software testing service providers. As a result, Testing as a Service (TaaS) has emerged as a strong service industry in the last several decades. In the context of software testing services, there could be various challenges (e.g., during the planning and service delivery phases) and, as a result, the quality of testing services is not always as expected. Objective: It is important, for both providers and also customers of testing services, to assess the quality and maturity of test services and subsequently improve them. Method: Motivated by a real industrial need in the context of several testing service providers, to assess the maturity of their software testing services, we chose the existing CMMI for Services maturity model (CMMI-SVC), and conducted a case study using it in the context of two Turkish testing service providers. Results: The case-study results show that maturity appraisal of testing services using CMMI-SVC was helpful for both companies and their test management teams by enabling them objectively assess the maturity of their testing services and also by pinpointing potential improvement areas. Conclusion: We empirically observed that, after some minor customization, CMMI-SVC is indeed a suitable model for maturity appraisal of testing services.