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

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

Study of two-memcapacitor circuit model with semi-explicit ODE solver

This article discusses software tools for studying non-linear dynamical systems. For a detailed analysis of the behavior of chaotic systems stepsize-parameter diagrams are introduced. A new self-adjoint semi-explicit algorithm for the numerical integration of differential equations is described. Two modifications of the proposed method are represented. A two-memcapacitor circuit is selected as a test dynamical system. Symmetry, accuracy and performance analysis of semi-explicit extrapolation ODE solver are considered in a series of computational experiments. Phase space of the two-memcapacitor circuit model, stepsize-parameter diagrams and dynamical maps are given as experimental findings

Persistent Cohomology and Circular Coordinates

Nonlinear dimensionality reduction (NLDR) algorithms such as Isomap, LLE and Laplacian Eigenmaps address the problem of representing high-dimensional nonlinear data in terms of low-dimensional coordinates which represent the intrinsic structure of the data. This paradigm incorporates the assumption that real-valued coordinates provide a rich enough class of functions to represent the data faithfully and efficiently. On the other hand, there are simple structures which challenge this assumption: the circle, for example, is one-dimensional but its faithful representation requires two real coordinates. In this work, we present a strategy for constructing circle-valued functions on a statistical data set. We develop a machinery of persistent cohomology to identify candidates for significant circle-structures in the data, and we use harmonic smoothing and integration to obtain the circle-valued coordinate functions themselves. We suggest that this enriched class of coordinate functions permits a precise NLDR analysis of a broader range of realistic data sets