Design of Reconfigurable Multiple-Beam Array Feed Network Based on Millimeter-Wave Photonics Beamformers

In this chapter, elaborating the direction of designing photonics-based beamforming networks (BFN) for millimeter-wave (mmWave) antenna arrays, we review the worldwide progress referred to designing multiple-beam photonics BFN and highlight our last simulation results on design and optimization of millimeter-photonics-based matrix beamformers. In particular, we review the specialties of mmWave photonics technique in 5G mobile networks of Radio-over-Fiber (RoF) technology based on fiber-wireless architecture. In addition, the theoretical background of array antenna multiple-beam steering using ideal models of matrix-based phase shifters and time delay lines is presented including a general analysis of radiation pattern sensitivity to compare updated photonics beamforming networks produced on phase shifter or true-time delay approach. The principles and ways to optimized photonics BFN design are discussed based on the study of photonics BFN scheme including integrated 8×8 optical Butler matrix (OBM). All schemes are modeled using VPIphotonics Design Suite and MATLAB software tools. In the result of simulation experiments, the outcome is obtained that both the integrated optical Butler matrix itself and the BFN based on it possess an acceptable quality of beams formation in a particular 5G pico-cell

Design and Optimization of Photonics-Based Beamforming Networks for Ultra-Wide mmWave-Band Antenna Arrays

In this chapter, we review the worldwide progress referred to designing optical beamforming networks intended to the next-generation ultra-wideband millimeter-wave phased array antennas for incoming fifth-generation wireless systems, which in recent years is under the close attention of worldwide communication community. Following the tendency, we study in detail the design concepts below true-time-delay photonics beamforming networks based on switchable or continuously tunable control. Guided by them, we highlight our NI AWRDE CAD-based simulation experiments in the frequency range of 57–76 GHz on design of two 16-channel photonics beamforming networks using true-time-delay approach. In the first scheme of the known configuration, each channel includes laser, optical modulator, and 5-bit binary switchable chain of optical delay lines. The second scheme has an optimized configuration based on only 3-bit binary switchable chain of optical delay lines in each channel, all of which are driven by four lasers with wavelength division multiplexing and a common optical modulator. In the result, the novel structural and cost-efficient configuration of microwave-photonics beamforming network combining wavelength division multiplexing and true-time-delay techniques is proposed and investigated

Studying a LW-VCSEL-Based Resonant Cavity Enhanced Photodetector and Its Application in Microwave Photonics Circuits

A detailed comparative experimental study was carried out to pursue advanced performances corresponding to the key parameters of two photodetectors based on vertical cavity surface emitting laser (VCSEL) operating in free-running or optically injection locked mode, as well as an inherent pin-photodetector. During the preliminary study, the key static and dynamic parameters were quantitatively determined and the optimal operating modes were derived for the both versions of VCSEL-based photodetectors as separate microwave-photonics circuit elements. Based on them, a final experiment was conducted to evaluate the processing quality, when one of the versions of VCSEL-based photodetectors or a inherent pin-photodetector is implemented as an optical-to-electrical converter for a typical microwave-photonics circuit that processes 120-Mbps 16-position quadrature amplitude modulated signal on the radio frequency carrier of 1–6 GHz. As a result, it was confirmed that better processing quality, i.e. Error Vector Magnitude value of less than 4%, could be obtained by using the free-running VCSEL-based photodetector version

Solving Data Quality Problems with Desbordante: a Demo

Data profiling is an essential process in modern data-driven industries. One of its critical components is the discovery and validation of complex statistics, including functional dependencies, data constraints, association rules, and others. However, most existing data profiling systems that focus on complex statistics do not provide proper integration with the tools used by contemporary data scientists. This creates a significant barrier to the adoption of these tools in the industry. Moreover, existing systems were not created with industrial-grade workloads in mind. Finally, they do not aim to provide descriptive explanations, i.e. why a given pattern is not found. It is a significant issue as it is essential to understand the underlying reasons for a specific pattern's absence to make informed decisions based on the data. Because of that, these patterns are effectively rest in thin air: their application scope is rather limited, they are rarely used by the broader public. At the same time, as we are going to demonstrate in this presentation, complex statistics can be efficiently used to solve many classic data quality problems. Desbordante is an open-source data profiler that aims to close this gap. It is built with emphasis on industrial application: it is efficient, scalable, resilient to crashes, and provides explanations. Furthermore, it provides seamless Python integration by offloading various costly operations to the C++ core, not only mining. In this demonstration, we show several scenarios that allow end users to solve different data quality problems. Namely, we showcase typo detection, data deduplication, and data anomaly detection scenarios