Hasil untuk "Telecommunication"

Amal Benhamiche, Pierre Fouilhoux, Lucas Létocart et al.

We initiate the polyhedral study of the Virtual Network Embedding (VNE) problem, which arises in modern telecommunication networks. We propose new valid inequalities for the so-called flow formulation. We then prove, through a dedicated flow decomposition algorithm, that these inequalities characterize the VNE polytope in the case of an embedding of a virtual edge on a substrate path. Preliminary experiments show that the new inequalities propose promising speedups for MIP solvers.

Dibakar Das, Jyotsna Bapat, Angeliki Katsenou et al.

The impact of Artificial Intelligence (AI) is transforming various aspects of urban life, including, governance, policy and planning, healthcare, sustainability, economics, entrepreneurship, etc. Although AI immense potential for positively impacting urban living, its success depends on overcoming significant challenges, particularly in telecommunications infrastructure. Smart city applications, such as, federated learning, Internet of Things (IoT), and online financial services, require reliable Quality of Service (QoS) from telecommunications networks to ensure effective information transfer. However, with over three billion people underserved or lacking access to internet, many of these AI-driven applications are at risk of either remaining underutilized or failing altogether. Furthermore, many IoT and video-based applications in densely populated urban areas require high-quality connectivity. This paper explores these issues, focusing on the challenges that need to be mitigated to make AI succeed in emerging countries, where more than 80% of the world population resides and urban migration grows. In this context, an overview of a case study conducted in Kathmandu, Nepal, highlights citizens' aspirations for affordable, high-quality internet-based services. The findings underscore the pressing need for advanced telecommunication networks to meet diverse user requirements while addressing investment and infrastructure gaps. This discussion provides insights into bridging the digital divide and enabling AI's transformative potential in urban areas.

Dmitry V. Obydennov, Ilya M. Asharchuk, Alexander M. Mumlyakov et al.

The integration of active light-emitting elements into planar photonic circuits on a silicon nitride platform remains challenging due to material incompatibilities and high-temperature processing. Proposed hybrid method embeds monodisperse luminescent particles into lithographically defined wells above a 200 nm-thick silicon nitride taper coupler. A fabrication process involving wells etching, particle deposition, and planarization enables precise integration while maintaining waveguide integrity. When pumped at 950 nm with a diode laser, the device emits broadband radiation in the 1500-1600 nm range, covering the optical telecommunication C-band. Numerical simulations yield an average coupling efficiency of 0.25% into the fundamental waveguide mode, suggesting significant potential for further device optimization. The approach provides a scalable route for integrating broadband telecommunications emitters on a silicon nitride platform.

Nooshin Boroumand Jazi, Farhad Faghani, Mahmoud Daneshvar Farzanegan

Abstract In emergencies where several ground base stations (GBS) are no longer available, mobile base stations based on unmanned aerial vehicles (UAVs) can efficiently resolve coverage issues in remote areas due to their cost‐effectiveness and versatility. Natural disasters, such as a deluge, cause damage to the terrestrial wireless infrastructure. The main challenge in these systems is to determine the optimal 3D placement of UAVs to meet the dynamic demand of users and minimise interference. Various mathematical frameworks and efficient algorithms are suggested for designing, optimising, and deploying UAV‐based communication systems. This paper investigates the challenges of 3D UAV placement through machine learning (ML) and enhanced affinity propagation (EAP). Lastly, the simulation results indicate that the proposed approach improves the system sum rate, interference, and coverage performance compared to DBSCAN, k‐means, and k‐means++ methods. Therefore, this paper identifies UAVs' most effective 3D placement, including minimising the number of UAVs, maximising the number of covered users, and maximising the system sum rate for an arbitrary distribution of users in the disaster area. Additionally, this paper addresses the issue of interference minimisation.

Victor Ruzhentsev

An estimation of the nonlinear degrees for the forward and inverse permutations of the Ascon algorithm is made in this work. This estimation is made by analyzing higher order differentials. The obtained results of nonlinear degree are significantly lower than the known data. Instead of the generally accepted values sr (where s is nonlinear degree of substitution and r is number of rounds), the computational experiments demonstrated the value s(r-1)+1 in all the considered cases. These results allow to clarify the complexity of constructing the best known distinguisher - the zero-sum distinguisher - for a multiround transformations. Thus, instead of the known complexity values of 285 and 2130 for 11 and 12 rounds of transformations, according to our data, the complexity for 11 rounds is 235 and for 12 rounds is 270.

Mohammad Asif Hasan, Fariha Haque, Saifur Rahman Sabuj et al.

To effectively treat lung and colon cancer and save lives, early and accurate identification is essential. Conventional diagnosis takes a long time and requires the manual expertise of radiologists. The rising number of new cancer cases makes it challenging to process massive volumes of data quickly. Different machine learning approaches to the classification and detection of lung and colon cancer have been proposed by multiple research studies. However, when it comes to self-learning classification and detection tasks, deep learning (DL) excels. This paper suggests a novel DL convolutional neural network (CNN) model for detecting lung and colon cancer. The proposed model is lightweight and multi-scale since it uses only 1.1 million parameters, making it appropriate for real-time applications as it provides an end-to-end solution. By incorporating features extracted at multiple scales, the model can effectively capture both local and global patterns within the input data. The explainability tools such as gradient-weighted class activation mapping and Shapley additive explanation can identify potential problems by highlighting the specific input data areas that have an impact on the model’s choice. The experimental findings demonstrate that for lung and colon cancer detection, the proposed model was outperformed by the competition and accuracy rates of 99.20% have been achieved for multi-class (containing five classes) predictions.

Sangyeop Yeo, Yu-Seung Ma, Sang Cheol Kim et al.

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and introduce a new metric, pass-ratio@n, which captures the granularity of accuracy according to the pass rate of test cases. The framework is intended to be fully automatic to handle the repetitive work involved in generating prompts, conducting inferences, and executing the generated codes. A preliminary evaluation focusing on the prompt detail, problem publication date, and difficulty level demonstrates the successful integration of our framework with the LeetCode coding platform and highlights the applicability of the pass-ratio@n metric.

Vishal Sharma

In the current research work, an analysis of differential phase shift quantum key distribution using InGaAs/InP and Silicon-APD (avalanche photodiode) as single photon detectors is performed. Various performance parameters of interest such as shifted key rate, secure key rate, and secure communication distance obtained are investigated. In this optical fiber-based differential phase shift quantum key distribution, it is observed that Si-APD under frequency conversion method at telecommunication window outperforms the InGaAs/InP APD.

Sumiko Miyata, Keisuke Ode

Abstract Many network devices, such as a smartphones and tablets, and streaming services, such as YouTube and Netflix, have become widespread. This causes network‐bandwidth congestion, so users require stable and consistent communication quality. Call admission control (CAC) has been proposed to solve these bandwidth resource problems. Some CACs have been proposed in order to maintain QoS. However, these CAC does not assume user behaviour. If CAC assumes some user behaviour, optimal control parameter derived conventional CAC may change because traffic load change by considering user behaviour. This article assumes that arriving types of flows are of three types: narrowband flows, broadband flow without seek‐bar operation, and broadband flows with seek‐bar operation. Under this assumpution, two CAC methods with single threshold or two thresholds are proposed. With these methods, it is assumed that all arriving flows result in the same user satisfaction when accommodated in a network. Under this assumption, the maximum of each user satisfaction is the same as the maximum number of accommodated flows. Using the call loss probability characteristics of Method 1, the objective function in Method 2 is modified. By using the modified objective function, CAC can be realised while properly accommodating broadband users who have been excessively rejected.

Mahmood Khosrowjerdi

Information transparency is a major building block of responsible governments. We explored factors influencing the information transparency of 117 world nations. After controlling for the effects of confounding variables of wealth (GDP per capita), corruption rate, population density, human capital, and telecommunication infrastructure, we found that the good governance indices (democracy, economy, and management) were strong and stable predictors of information transparency of world nations.

Hamza Kheddar

The second-generation (2G) mobile systems were developed in response to the growing demand for a system that met mobile communication demands while also providing greater interoperability with other systems. International organizations were crucial in the development of a system that would offer better services, be more transparent, and be more interoperable with other networks. The aim of having a single set of standards for networks worldwide was sadly not realized by the 2G network standards. The third generation (3G) was born. It was called the universal terrestrial mobile system (UMTS), which is European telecommunications standards institute (ETSI) driven. IMT-2000 is the international telecommunication union-telecommunication standardization sector (ITU-T) name for the 3G network. Wide-band code division multiple access (WCDMA) is the air interface technology for the UMTS. This platform offers many services that are based on the Internet, along with video calling, imaging, etc. Further advancements to mobile network technology led to long term evolution (LTE), a technology referred to as 4G. The primary goal of LTE was to improve the speed and capacity of mobile networks while lowering latency. As we move to an ALL-IP system, mobile networks' design becomes much simpler. LTE uses orthogonal frequency division multiplexing (OFDM) in its air interface. This paper details all mentioned mobile generations, as well as all the differences between them in terms of hardware and software architectures.

Bin Han, Hans D. Schotten

Enabled and driven by modern advances in wireless telecommunication and artificial intelligence, the convergence of communication, computing, and control is becoming inevitable in future industrial applications. Analytical and optimizing frameworks, however, are not yet readily developed for this new technical trend. In this work we discuss the necessity and typical scenarios of this convergence, and propose a new approach to model the system-level reliability across all involved domainss

Gabin Maxime Nguegnang, Marcellin Atemkeng, Theophilus Ansah-Narh et al.

The instability of power generation from national grids has led industries (e.g., telecommunication) to rely on plant generators to run their businesses. However, these secondary generators create additional challenges such as fuel leakages in and out of the system and perturbations in the fuel level gauges. Consequently, telecommunication operators have been involved in a constant need for fuel to supply diesel generators. With the increase in fuel prices due to socio-economic factors, excessive fuel consumption and fuel pilferage become a problem, and this affects the smooth run of the network companies. In this work, we compared four machine learning algorithms (i.e. Gradient Boosting, Random Forest, Neural Network, and Lasso) to predict the amount of fuel consumed by a power generation plant. After evaluating the predictive accuracy of these models, the Gradient Boosting model out-perform the other three regressor models with the highest Nash efficiency value of 99.1%.

Koesmarijanto Koesmarijanto, Ainun Azizah, Hendro Darmono

Antennas are an important component in wireless communication systems that continue to grow in the use of the 2.4 GHz frequency for 4G/LTE applications. Technology in the field of telecommunications has developed very rapidly using wireless communication, which is easily accessible by various devices, for example, Wi-Fi or Wireless Fidelity. Microstrip antenna is one type of antenna that has a narrow bandwidth, small gain. This research aims to widen the bandwidth by designing and manufacturing a truncated corner microstrip patch antenna with a 2x4 array at a frequency of 2.4 GHz with a U-slot. The truncated corner method is used to obtain circular polarization. The truncated corner microstrip antenna is designed by cutting corners. The array method is used to obtain the maximum gain value, while the addition of U-slot aims to reduce the return loss and Voltage Standing Wave Ratio (VSWR) values.

Nian TAO, Sheng ZHANG, Tai FU

With the continuous development and maturity of new-generation information technologies such as 5G, artificial intelligence, and the Internet of things, the construction of smart communities has entered the second half, with greater space and higher requirements.Firstly, the development status of community and business needs was analyzed.Secondly, the design ideas based on “pan-sensing, data collection, and intelligent application” was proposed for the pain points of users, such as government, property management and residents.Thirdly, an overall plan for 5G+AIoT smart community was built, focusing on wisdom community 5G application scenarios, the industrial and social benefits of smart community construction were discussed.Finally, the future development trend of smart communities was looked forward.

Sonali, Abhishek Dixit, Virander Kumar Jain

Free-space optical (FSO) communication is crucial for the next-generation 5G+ wireless networks. The FSO links suffer from atmospheric-turbulence-induced bit errors. For the increasing link's performance, low-density parity-check (LDPC) codes, complemented by the belief-propagation (BP) algorithm, are an excellent option. The bit error rate (BER) of the LDPC code is characterized by a parameter called the threshold. The threshold is the signal-to-noise ratio (SNR), after which the BER falls arbitrarily and becomes close to zero. We derive the threshold for the LDPC codes under the BP algorithm for an uncorrelated flat FSO channel. The determination of the FSO channel threshold is a tedious task as the density of the log-likelihood ratio from the FSO channel cannot be assumed as Gaussian and is available only in a numerical form. It, thus, requires testing different values of SNR as a possible threshold systematically. Therefore, we propose the divide and conquer algorithm. The threshold depends on the degree distributions, channel state information (CSI), and the turbulence level. When CSI is known, we obtain the threshold at an SNR of 8.10 dB in high turbulence for a regular (3, 6) LDPC code. This threshold steps up to 12.48 dB when the CSI is unknown at the receiver. We evaluate the threshold values for various degree distributions (regular and irregular LDPC codes) under high, moderate, and low turbulence levels for both channel models (CSI known and unknown at the receiver). We also confirm the derived threshold values with MATLAB simulations.

Pernilla Bergmark, Vlad C. Coroamă, Mattias Höjer et al.

Information and communication technologies (ICT) can make existing products and activities more efficient or substitute them altogether and could thus become crucial for the mitigation of climate change. In this context, individual ICT companies, industry organizations and international initiatives have started to estimate the environmental effects of ICT services. Often such assessments rely on crude assumptions and methods, yielding inaccurate or even misleading results. The few existing methodological attempts are too general to provide guidance to practitioners. The starting points of this paper are i) a high level standard from the European Telecommunication Standardisation Institute (ETSI) and the International Telecommunication Union (ITU), and ii) its suggested enhancements for single service assessment outlined in "A Methodology for Assessing the Environmental Effects Induced by ICT Services Part I: Single services" (Part I in short). Building on the assessment of single services, the current article identifies and addresses shortcomings of existing methodologies and industry practices with regard to multiple services assessment. For a collection of services, it addresses the goal and scope definition, the so far ignored aggregation of effects among several services, and the allocation between several companies contributing to one or more services. The article finally brings these considerations together with those of Part I into a workflow for performing such assessments in practice.

Seokjin Lee, Jun-seok Lim

Abstract In active sonar systems, the detection of echo from targets can deteriorate due to reverberation. Detection becomes more difficult if targets have low-Doppler frequency and are located near the reverberation band, especially in an environment with low signal-to-reverberation ratio. In this paper, we propose an algorithm for the reverberation suppression of continuous wave signals using non-negative matrix factorization. To extract the target echo signal mixed with reverberations, the bases for the target echo and the reverberation are independently defined, and different constraints are applied for their corresponding estimation. We also derive constraints on temporal continuity and temporal length to estimate bases for the target echo. Experiments using simulated reverberations are performed to evaluate the proposed algorithm, and the results show an enhancement in the signal-to-noise ratio by 6–15 dB, as well as in the detection probability at several signal-to-reverberation ratios. Moreover, an experiment is conducted using reverberation measured from an ocean, and the results show that the proposed algorithm can effectively suppress reverberation and enhance detection performance in practical settings.

Yaliang Gui, Mario Miscuglio, Zhizhen Ma et al.

The class of transparent conductive oxides includes the material indium tin oxide (ITO) and has become a widely used material of modern every-day life such as in touch screens of smart phones and watches, but also used as an optically transparent low electrically-resistive contract in the photovoltaics industry. More recently ITO has shown epsilon-near-zero (ENZ) behavior in the telecommunication frequency band enabling both strong index modulation and other optically-exotic applications such as metatronics. However the ability to precisely obtain targeted electrical and optical material properties in ITO is still challenging due to complex intrinsic effects in ITO and as such no integrated metatronic platform has been demonstrated to-date. Here we deliver an extensive and accurate description process parameters of RF-sputtering, showing a holistic control of the quality of ITO thin films in the visible and particularly near-infrared spectral region. We further are able to custom-engineer the ENZ point across the telecommunication band by explicitly controlling the sputtering process conditions. Exploiting this control we design a functional sub-wavelength-scale filter based on lumped circuit-elements, towards the realization of integrated metatronic devices and circuits.

Shengtao Lin, Zinan Wang, Ji Xiong et al.

Highly coherent wave is favorable for applications in which phase retrieval is necessary, yet a high coherent wave is prone to encounter Rayleigh fading phenomenon as it passes through a medium of random scatters. As an exemplary case, phase-sensitive optical time-domain reflectometry (Φ-OTDR) utilizes coherent interference of backscattering light along a fiber to achieve ultra-sensitive acoustic sensing, but sensing locations with fading won't be functional. Apart from the sensing domain, fading is also ubiquitous in optical imaging and wireless telecommunication, therefore it is of great interest. In this paper, we theoretically describe and experimentally verify how the fading phenomena in one-dimension optical scatters will be suppressed with arbitrary number of independent probing channels. We initially theoretically explained why fading would cause severe noise in the demodulated phase of Φ-OTDR; then M-degree summation of incoherent scattered light-waves is studied for the purpose of eliminating fading. Finally, the gain of the retrieved phase signal-to-noise-ratio and its fluctuations were analytically derived and experimentally verified. This work provides a guideline for fading elimination in one-dimension optical scatters, and it also provides insight for optical imaging and wireless telecommunication.