The increasing complexity of configuring cellular networks suggests that machine learning (ML) can effectively improve 5G technologies. Deep has proven successful in ML tasks such as speech processing and computational vision, with a performance scales the amount available data. lack large datasets inhibits flourish deep applications wireless communications. This paper presents methodology combines vehicle traffic simulator ray-tracing simulator, to generate channel realizations representing...

Establishing and tracking beams in millimeter-wave (mmWave) vehicular communication is a challenging task. Large antenna arrays narrow introduce significant system overhead configuring the using exhaustive beam search. In this paper, we propose to learn optimal pair index by exploiting locations types of receiver vehicle its neighboring vehicles (situational awareness), leveraging machine learning classification past training data. We formulate mmWave selection as multi-class problem based...

The detection of T-wave end points on electrocardiogram (ECG) is a basic procedure for ECG processing and analysis. Several methods have been proposed tested, featuring high accuracy percentages correct detection. Nevertheless, their performance in noisy conditions remains an open problem.A new approach algorithm location based the computation Trapezium's areas validated (in terms repeatability), using signals from Physionet QT Database. has tested compared with one most used approaches...

Modern communication systems may benefit from the availability of sensor data leveraged by sophisticated machine learning algorithms. We recently described how LIDAR (light detection and ranging) on a vehicle can be used for line-of-sight to reduce overhead associated with link configuration in millimeter wave systems. is autonomous driving high resolution mapping positioning. In this paper, we present new LIDAR-based features compare previously proposed distributed architecture two...

Millimeter wave (mmWave) communication systems can leverage information from sensors to reduce the overhead associated with link configuration. Light detection and ranging (LIDAR) is one sensor widely used in autonomous driving for high resolution mapping positioning. This letter shows how LIDAR data be line-of-sight mmWave beam-selection. In proposed distributed architecture, base station broadcasts its position. The connected vehicle leverages suggest a set of beams selected via deep...

The future mobile network has the complex mission of distributing available radio resources among various applications with different requirements. access slicing enables creation logical networks by isolating and using dedicated for each group applications. In this scenario, resource scheduling (RRS) is responsible slices to fulfill their service-level agreement (SLA) requirements, prioritizing critical while minimizing number intent violations. Moreover, ensuring that RRS can deal a high...

Deep learning (DL) provides a framework for designing new communication systems that embrace practical impairments. In this paper, we present an exploration of DL as applied to design the physical layer MIMO with low resolution analog-to-digital converters. The application is nontrivial thanks severe nonlinear distortion caused by quantization and large dimensional channel. We investigate network architectures channel estimation detection. results indicate adopted lead good in...

The fifth-generation (5G) cellular networks incorporate a large variety of technologies in order to address very distinct use cases. Assessing these and investigating future alternatives is complicated when one relies only on simulators. 5G testbeds are an important alternative simulators many have been recently described, emphasizing aspects such as cloud functionalities, management orchestration. This work presents mobile network testbed with virtualized orchestrated structure using...

This work presents a novel method for automatic modulation classification based on discriminative learning. The features are the ordered magnitude and phase of received symbols at output matched filter. results using proposed front end support vector machines compared to other techniques. Frequency offset is also considered show that in this condition new significantly outperforms two cumulant-based classifiers.

G.fast is a new standard from the International Telecommunication Union, which targets 1 Gb/s over short copper loops using frequencies up to 212 MHz. This technology requires accurate parametric cable models for simulation, design, and performance evaluation tests. Some existing were designed very high speed digital subscriber line spectra, i.e., 30 MHz, adopt assumptions that are violated when frequency range extended frequencies. paper introduces simple causal model able accurately...

Configuring beams in millimeter-wave (mmWave) vehicular communication is a challenging task. Large antenna arrays and narrow are deployed at transceivers to exploit beamforming gain, which leads significant system overhead if an exhaustive beam search adopted. In this paper, we propose learn the optimal pair index by exploiting locations sizes of receiver its neighboring vehicles (parts situational awareness for automated driving), leveraging machine learning tools with past training...

We consider the problem of channel estimation in low-resolution multiple-input multiple-output (MIMO) systems operating at millimeter wave (mmWave) and present a deep transfer learning (DTL) approach that exploits previously trained models to speed up site adaptation. The proposed model is composed feature extractor regressor, with only regressor requiring training for new environment. DTL evaluated using two 3D scenarios where ray-tracing performed generate mmWave MIMO channels used...

Network slicing at the radio access network (RAN) domain, called RAN slicing, requires elasticity, efficient resource sharing, and customization. In this scenario, scheduling (RRS) is responsible for dealing with scarce limited frequency spectrum resources available domain while fulfilling slice intents. The wide variety of scenarios supported in 5G beyond networks makes RRS problem scenario a significant challenge. This paper proposes an intent-aware reinforcement learning method to perform...

Abstract An automatic speech recognition system has modules that depend on the language and, while there are many public resources for some languages (e.g., English and Japanese), Brazilian Portuguese (BP) still limited. This work describes development of free tools BP recognition, consisting text audio corpora, phonetic dictionary, grapheme-to-phone converter, acoustic models. All them publicly available together with a proposed application programming interface, have been used several new...

Several new architectures are under investigation for cloud radio access networks, assuming distinct splits of functionality among the network elements. Consequently, research on data compression fronthaul is based assumptions that correspond to a wide variety tradeoffs rate, signal distortion, latency, and computational cost. This letter describes method LTE downlink point-to-point linear prediction Huffman coding, which suitable low cost encoding decoding units with stringent restrictions...

Mining has played an important role in the economies of South American countries. Although industrial mining prevails most countries, expansion garimpo activity increased substantially. Recently, Brazil exhibited two moments dominance over mining: 1989–1997 and 2019–2022. While sites occupied ~ 360 km2 1985 but to 1800 2022, a 5-fold increase, area by 1200%, from 218 2627 2022. More than 91% this is concentrated Amazon. Where almost 40% are five years old or younger, proportion increases 62%...

The use of vectoring for crosstalk cancellation in the new ITU-T G.fast standard next generation DSL systems becomes essential efficient utilization extended bandwidth (up to 200 MHz). In VDSL2 30 MHz), a zero-forcing-based linear precoder is used downstream which approaches single-line performance. However, at high frequencies, may amplify signal power substantially since channel much stronger than lower frequencies. Performance could be significantly degraded by normalization keep PSD...

SCADA (Supervisory Control and Data Acquisition) databases have three main features that identify them as big data systems: volume, variety velocity. SCADAs are extremely important for the safety security operation of modern power system provide essential online information about state to operators. A current research challenge is efficiently process this data, which involves real-time measurements hundreds thousands heterogeneous electrical physical measurements. Among foreseen automation...

This letter presents a fronthaul signal compression scheme based on linear prediction coding adapted to the orthogonal frequency division multiplexing signals. The proposed method is capable of providing fine tuning factor, which an alternative legacy methods that tune factor by changing discrete number bits quantizer, and consequently, are only able do so with coarse resolution.

Spectrum balancing (SB) techniques optimize transmission and can significantly improve digital subscriber lines (DSL) services. In the literature, DSL system optimization is typically formulated as a rate maximization problem. However, there an increasing interest in minimizing considerable amount of power consumed by telecommunication networks. Few works SB literature have explored algorithms for minimization. It known that some existing solutions be converted into minimization algorithms....

Most works in power systems event classification concern classifying an according to the morphology of corresponding waveform. An important and even more difficult problem is underlying cause. However, lack labeled data problematic this second scenario. This paper proposes a framework based on frame-based sequence (FBSC), Alternative Transient Program (ATP), public dataset advance research area. As proof concept, thorough evaluation automatic short circuits transmission lines discussed....

The use of a hybrid copper and fiber architecture is attractive in both fixed access mobile backhauling scenarios. This trend led the industry academia to start developing fourth generation broadband system, which aims at achieving bit-rates 1 Gb/s over short loops. In this context, accurate models twisted-pair cables operating relatively high frequencies are key elements. work describes new parametric cable that incorporate four important characteristics: support up 200 MHz, few parameters,...

Channel estimation for massive MIMO using coarse quantizers is nontrivial due to severe nonlinear distortions caused by quantization and the large dimensional channel. The best solutions this problem nowadays are based on generalized approximate message passing (GAMP) its variations. However, there practical issues such as nonideal that may violate assumptions in which GAMP algorithms rely. This motivates research methods deep learning (DL), provides a framework designing new communication...