High-speed Communication Research Articles

Nonlinear compensation for few-mode fiber MDM-WDM systems using probabilistic neural network

In this paper, we propose for the first time to apply probabilistic neural network (PNN) to fiber nonlinear compensation (NLC) in a high-speed coherent optical communication system that combines few-mode fiber (FMF) mode division multiplexing (MDM) with wavelength division multiplexing (WDM). By training on a small number of symbols, the PNN equalizer can compute the statistical distribution of the signal nonlinearity, make decisions on test symbols, and thereby compensate for the nonlinear impairments of the signals. To verify the effectiveness of the proposed scheme, we construct a MDM-WDM simulation system with 28 GBaud polarization division multiplexing (PDM) 16-quadrature amplitude modulation(QAM) and 64 GBaud PDM-64QAM, 6 spatial mode signals are transmitted over 11 wavelength channels with link lengths of 1500 km and 400 km, respectively. The results show that the PNN equalizer can make nonlinear judgments on received signals and effectively compensate the signal impairments caused by Kerr nonlinearity and device nonlinearity in a large launch power range after undergoing carrier phase recovery (CPR). Meanwhile, this scheme exhibits strong robustness against residual linear mode coupling (LMC), differential mode group delay (DMGD), and amplified spontaneous emission (ASE) noise. Finally, by the computational complexity comparison, it is proved that the complexity of the probabilistic neural network nonlinear compensation (PNN NLC) scheme is lower than that of digital back propagation (DBP) with comparable performance, which is on the order O(N).

113Gbps rainbow visible light laser communication system based on 10λ laser WDM emitting module in fiber-free space-fiber link.

With the advent of the sixth-generation mobile communication standard (6 G), the visible light communication (VLC) technology based on wavelength division multiplexing (WDM) technology can effectively solve the problem of shortage of spectrum resources and insufficient channel capacity. This paper introduces one of our technical achievements, namely the construction of a near-real-time visible light laser communication (VLLC) system based on WDM, which includes a self-designed 10-λ fully-packaged visible light laser emission module, 1 m multimode fiber - 0.175 m free space - 1 m multimode fiber optical transmission link, and receiver array. In the transmitter system, we adopt adaptive discrete multitone (DMT) modulation technique combined with Quadrature Amplitude Modulation (QAM) modulation scheme to obtain maximum spectral efficiency (SE). In the receiving system, we utilize the sparse-structured reservoir computing post-equalization algorithm to achieve superior equalization performance on the basis of the traditional post-equalization algorithm. The experimental results indicate that this quasi-real-time communication system has achieved a signal transmission rate of 113.175Gbps. To the best of our knowledge, this work has set a record in the field of high-speed visible light laser communication. Therefore, the laser communication system constructed by this work, with its flexibility in deployment and high-speed performance, demonstrates the significant potential application of visible light laser communication in data center interconnection and high-speed indoor access networks.

Mixed reality human teleoperation with device-agnostic remote ultrasound: Communication and user interaction

For many applications, remote guidance and telerobotics provide great advantages. For example, tele-ultrasound can bring much-needed expert healthcare to isolated communities. However, existing tele-guidance methods have serious limitations including either low precision for video conference-based systems, or high complexity and cost for telerobotics. A new concept called human teleoperation leverages mixed reality, haptics, and high-speed communication to provide tele-guidance that gives an expert nearly-direct remote control without requiring a robot. This paper provides an overview of the human teleoperation concept and its application to tele-ultrasound. The concept and its impact are discussed. A new approach to remote streaming and control of point-of-care ultrasound systems independent of their manufacturer is described, as is a high-speed communication system for the HoloLens 2 that is compatible with ResearchMode API sensor stream access. Details of these systems are shown in supplementary video demonstrations. Novel interaction methods enabled by HoloLens 2-based pose tracking are also introduced and tests of the communication and user interaction are presented. The results show continued improvement of the system compared to previous work in instrumentation, HCI, and communication. The system thus has good potential for tele-ultrasound, as well as possible other applications of human teleoperation including remote maintenance, inspection, and training. The remote ultrasound streaming and control application is made available open source.

6G Traffic Prediction with a Novel Parallel Convolutional Neural Networks Architecture and Matrix Format Method Integration

In the evolving world of wireless communication, sixth generation (6G) networks represent a significant leap forward. Beyond its high-speed and reliable communication, 6G integrates Artificial Intelligence (AI), making networks intelligent entities. This elevates the infrastructure of smart cities and other ecosystems. A critical factor in 6G's success is real-time traffic analysis. As 6G aims to interconnect billions of devices, it faces unprecedented traffic patterns. Practical traffic analysis ensures optimal performance, resource distribution, and energy efficiency. It also supports the network in handling vital sectors like healthcare and transportation by anticipating congestion and prioritizing crucial data. However, traditional traffic analysis techniques designed for earlier generations cannot accommodate 6G's demands. With 6G's integration of diverse technologies, understanding traffic becomes more challenging. Recent advancements have incorporated deep learning architectures, notably Convolutional Neural Networks (CNNs), for traffic analysis. While these models show potential, adapting them to 6G's specifics remains challenging. This research presents a unique parallel CNN architecture for 6G traffic prediction. It converts network data into an image using the Matrix Format Method (MFM), making it suitable for CNN processing. This innovation addresses the limitations of traditional methods and meets 6G's requirements. Compared to other models, our parallel CNN architecture highlights enhanced performance, promising increased traffic prediction accuracy. It also paves the way for improved resource allocation, energy management, and quality of service in 6G environments.

Design and application of an information interaction device for household photovoltaic inverters

The rapid growth of household photovoltaics poses a significant challenge to the safe operation of distribution networks. To enable the unified monitoring of household photovoltaic inverters by power grid companies, this paper introduces an information interaction device for household photovoltaic inverters based on high-speed power line carrier communication and high-speed radio frequency communication. The study begins by analyzing the information access architecture of the household photovoltaic inverter, followed by a presentation of the hardware and software design of the information interaction device. Subsequent experiments conducted at various photovoltaic stations demonstrate an impressive 98% success rate for information interaction, highlighting the device’s robust reliability.

High-speed data transmission based on mode-locked optical frequency comb

<sec>With the rapid development of emerging technologies such as multimedia services, live broadcasting, video conferencing, and high-definition television, traditional radio frequency communication is unable to meet people 's growing demand for communication capacity and transmission rate. In recent years, optical communication has received extensive attention from the industrial and scientific communities due to its advantages of large bandwidth, high speed, low power consumption, light weight, and strong anti-interference ability. As an emerging light source, the optical frequency comb (OFC) has a wide spectral range, multi-wavelength, high stability, and good phase coherence, providing a new idea for studying microwave signals with simple system structure, strong tunability and high frequency stability. At the same time, the multi-optical mode characteristics of OFC are compatible with the current communication system based on wavelength division multiplexing technology. Hundreds of laser arrays in a traditional communication system can be replaced by only one laser, which greatly reduces the power consumption of the system.</sec><sec>Combining the above advantages, in this paper, a large-scale parallel high-speed optical communication system based on mode-locked OFC is proposed. The linewidth of the OFC locked to the rubidium atomic clock can reach 1 Hz, which is sufficient to support the transmission of high-order modulation signals. The electro-optic modulators are used to adjust the amplitude and phase of each optical mode of the mode-locked OFC and self-coherently map to the RF domain. The high-speed high-order modulation signal with coded information is obtained by frequency screening through a narrow-band filter. The communication capability of the microwave photonic modulation signal in the 16 quadrature amplitude modulation (QAM) format is verified by simulation. The 16QAM communication with the rate of 2, 6, and 14 Gbit/s is realized by using the photonic microwave signal on the 100 m space optical link, and the bit error rate (BER) is less than 10<sup>–6</sup>. The proposed large-scale parallel optical communication system based on mode-locked OFC can achieve high-speed information transmission with a compact system structure, which is suitable for inter-satellite communication, emergency communication, military communication and other fields.</sec>

Crowdsourcing Geospatial Data for Earth and Human Observations: A Review

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors.

СУЧАСНИЙ СТАН ЦИФРОВІЗАЦІЇ КРАЇН-ЧЛЕНІВ ЄС

This article explores the present status of digitization across European Union member states. While the EU maintains common goals and overarching strategies for digitalization, individual member nations exhibit diverse levels of progress in its implementation. The asynchronous pace of digitalization among EU member states stems from various factors, including economic disparities, variations in technological infrastructure and legal frameworks, cultural and social influences, disparities in education and digital literacy, divergent government initiatives and funding levels, and the extent of collaboration between the public and private sectors. Each member state contributes to distinct dimensions of progress in the implementation of digitalization. The European Commission facilitates the monitoring of digital competitiveness and indicators across EU member states through the utilization of the Digital Economy and Society Index (DESI) report. This report evaluates diverse aspects of the digital economy and society, offering a holistic perspective on digital development within the EU. The current digital landscape in individual EU member states has been analyzed. The study examines the dynamics of changes in specific indicators (connectivity, human capital, integration of digital technologies, and state digital services) within the framework of the DESI from 2015 to 2022 in both the European Union as a collective entity and the individual member states. The research findings indicate that, on the whole, there has been noteworthy advancement in digitalization across all EU member states over the past decade. Nevertheless, the study highlights the contemporary challenges reflected in the objectives outlined in the "Digital Decade" program and the asynchronous fulfillment of these goals among member states. The most significant progress has been observed in accomplishing objectives related to digitalizing public services. All figures of this indicator are approaching the maximum. Notable advances have been made in the connectivity or digital infrastructure domain in implementing 5G and high-speed communications. However, there is a recognized need for further development, particularly in establishing distribution nodes and advancing the field of quantum computing. Examining the indicator of human capital, member states have made significant progress in imparting basic digital skills to their populations. Nevertheless, increasing the number of Information and Communication Technology (ICT) specialists remains required. Turning to the integration of digital technologies, specifically the digital transformation of businesses, discernible progress has been achieved in incorporating digital technologies into Small and Medium Enterprises (SMEs) activities. However, further advancement necessitates the introduction of cloud technologies and artificial intelligence into the operations of enterprises across the European Union.

Reconfigurable Neuromorphic Neural Network Architecture

Neural network (NN), also known as artificial neural network (ANN), provides efficient results in every computation, whether it is pattern recognition, forecasting, customer research, data validation, risk management, data mining, etc. In each computation, NN requires a specific dataset, and according to the datasets, a new NN structure is used to compute the results. Thus, these NN structures mostly depend upon the type of datasets. The current study presents a method that comprises a dedicated architecture known as neuromorphic neural network (NNN), which is made up of optical waveguides that enable high communication and data processing speed at the same time. We have also proposed three algorithms for configuring and building distinct ANN structures from the same architecture. These dedicated structures are not dependent on the datasets and employ the necessary processing element (PE) nodes to function as neurons in the hidden layer. Because specialized resources will be employed to perform operations in the hidden layer, these designs may produce more efficient outcomes than the present logical NN. Furthermore, we assessed our proposed architecture in terms of communication latency, deadlock prevention, energy consumption, and power usage. The simulation results show that deadlocks are avoided to the greatest extent possible, power consumption is reduced by up to 95%, and communicational latency is accomplished in the order of femtoseconds while conversing among PE nodes. The proposed architecture and simulation results promise an alternative for logical NN as well as improved results in terms of speed and efficiency.

Influence of atmospheric turbulence on coherent detection performance of space coherent optical communication

Space coherent optical communication technology is considered to be an important way to overcome the bottleneck in current high-speed space communication. However, atmospheric turbulence seriously limits its realization. Based on the Huygens-Fresnel principle and the low-frequency compensation power spectrum inversion method, this work first investigates the random distribution characteristics of the amplitude and phase of a Gaussian beam after it has been transmitted through atmospheric turbulence. Then, using the coherent mixing efficiency and communication bit error rate model, the influence of atmospheric turbulence on the performance of spatial coherent optical communication systems is obtained. Finally, a laser heterodyne detection experimental system is built to quantitatively study the influence of atmospheric turbulence on the coherent detection performance of spatial coherent optical communication. The conclusions drawn from this study are as follows. 1) The spatial phase distortion caused by the weak turbulence channel is relatively small and will hardly affect the light intensity distribution characteristics of the Gaussian beam. In the case of weak turbulence, the influence of weak turbulence on the performance of coherent optical communication system is almost negligible. The communication bit error rate will decrease rapidly with the increase of the number of single bit data photons. The communication signal-to-noise ratio can be better than 10<sup>–5</sup> when the number of single-bit photons is greater than 10. 2) Moderate turbulence will change the intensity distribution characteristics of the Gaussian beam, but will not cause a serious shift in the center of the spot. Under moderate turbulence conditions, the coherent mixing efficiency decreases rapidly as the turbulence intensity continues to increase, but the communication bit error rate still decreases rapidly with the increase of the number of single bit data photons. At this time, increasing the number of single-bit photons can suppress the negative influence of moderate intensity turbulence on the performance of coherent optical communication systems. 3) Strong turbulence will cause severe spatial phase distortion of the beam, destroy the consistency of the light intensity distribution, and cause a serious shift in the center of the spot. Under strong turbulence conditions, the coherent mixing efficiency of coherent optical communication systems approaches zero, and increasing the number of single bit data photons cannot significantly reduce the bit error rate, seriously affecting the quality of coherent optical communication. Atmospheric turbulence is an important limiting factor for developing space coherent optical communication. This study can provide useful references for evaluating the performance of space coherent optical communication systems.

Signal Pre-emphasis Technique for 10-60-MHz High-speed Implant Communication System with Bandwidth-limited Small Antennas

Signal Pre-emphasis Technique for 10-60-MHz High-speed Implant Communication System with Bandwidth-limited Small Antennas

Investigation on Effect of Silicon Microring Modulator Coupling States on High-Speed PAM4 Communication System

Investigation on Effect of Silicon Microring Modulator Coupling States on High-Speed PAM4 Communication System

Enhancing High-Speed Data Communications: Optimization of Route Controlling Network on Chip Implementation

Enhancing High-Speed Data Communications: Optimization of Route Controlling Network on Chip Implementation

GaN-Based Series Hybrid LED Array: A Dual-Function Light Source With Illumination and High-Speed Visible Light Communication Capabilities

GaN-Based Series Hybrid LED Array: A Dual-Function Light Source With Illumination and High-Speed Visible Light Communication Capabilities

Uplink Channel Estimation and ICI Elimination for Cell-Free Massive MIMO High-Speed Trains Communications

Uplink Channel Estimation and ICI Elimination for Cell-Free Massive MIMO High-Speed Trains Communications

Research on Key Technologies of Smart Breeding Platform Based on 5G

Abstract In modern animal husbandry, the application of 5G technology opens a new era of farming management, especially in intelligent farming. The high-speed and low-latency communication characteristics make remote monitoring, data transmission, and thoughtful decision-making possible, significantly improving breeding efficiency and management. It has great potential for monitoring animal health, preventing and controlling diseases, and improving production efficiency. This paper explores the application of 5G technology in an intelligent farming management platform and its key technologies. By analyzing the needs of smart farming, we clarify the key application areas of 5G technology. To identify sick pigs, measure their weight accurately using binocular vision technology, and combine with machine learning algorithms, the YOLO v3 algorithm is utilized. The accuracy of sick pig identification based on YOLO v3 reaches 98%, the error of pig weight measurement is controlled within ±2%, and the real-time data transmission and processing realized by 5G technology significantly improves the efficiency of disease prevention and control.5G technology can effectively support the efficient operation of the intelligent farming platform, which is of great significance to enhance the level of farming management and promote the sustainable development of the animal husbandry industry.

Stable and self-healing perovskite for high-speed underwater optical wireless communication

A water-resistant and self-healing perovskite light source employed for underwater wireless optical communication.

Size-Dependent Characteristics of High-Bandwidth Photodetector Based on GaN Micro-LEDs and LEDs for High-Speed Visible Light Communication

Size-Dependent Characteristics of High-Bandwidth Photodetector Based on GaN Micro-LEDs and LEDs for High-Speed Visible Light Communication

FBMC vs. PAM and DMT for High-Speed Wireline Communication

FBMC vs. PAM and DMT for High-Speed Wireline Communication

A compact dual band hexagon rectangular shaped monopole antenna for WIMAX and WLAN applications

This paper presents a compact dual-band hexagon-rectangular shaped monopole antenna for WiMAX and WLAN applications. The miniaturized size of the antenna being 29 × 38 × 0.8 mm3. The proposed antenna operates efficiently within two distinct frequency ranges: 2.7 GHz to 3.2 GHz and 4.0 GHz to 5.1 GHz, addressing the needs of both WiMAX and WLAN systems. The antenna achieves bandwidths of 16.67% and 25.58% for the respective frequency bands, ensuring reliable performance and wide coverage for high-speed wireless communication. The antenna design attains its nature and application as a result of the center hexagonal shaped cavity which creates the required dual bands.