Crosstalk reduction using novel cross-shaped resonators with via fence in high-frequency transmission lines

Purpose The purpose of this paper is to design a suitable guard trace to reduce the electromagentic interference between two closely spaced high frequency transmission lines. A novel cross-shaped resonator combined via fence is passed down to alleviate far-end and near-end crosstalk (NEXT) in tightly coupled high-speed transmission lines. The distance between the adjacent transmission lines is increased stepwise as a function of trace width. Design/methodology/approach A rectangular-shaped resonator via fence is connected by a guard trace has been proposed to overcome the coupling between the traces that is separated by 2 W. Similarly, by creating a cross-shaped resonator via fence connected by guard trace that reduces the spacing further by 1.5 W. Findings A tightly coupled transmission line structure that needs separation by a designed unit cell structure. Further research needs to be conducted to improve the NEXT, far-end crosstalk (FEXT) and spacing between the transmission lines. Originality/value This study portrays a novel method that combines the resonators via fence with a minimum spacing between the tightly coupled transmission lines which reduce the NEXT and FEXT; thereby reducing the size of the routing area. The resultant test structures are characterized at high frequencies using time domain and frequency domain analysis. The following scattering parameters such as insertion loss, NEXT and FEXT of the proposed method are measured as 1.504 dB, >30 dB and >20 dB, respectively.

Modeling Radio-Frequency Devices Based on Deep Learning Technique

An advanced method of modeling radio-frequency (RF) devices based on a deep learning technique is proposed for accurate prediction of S parameters. The S parameters of RF devices calculated by full-wave electromagnetic solvers along with the metallic geometry of the structure, permittivity and thickness of the dielectric layers of the RF devices are used partly as the training and partly as testing data for the deep learning structure. To implement the training procedure efficiently, a novel selection method of training data considering critical points is introduced. In order to rapidly and accurately map the geometrical parameters of the RF devices to the S parameters, deep neural networks are used to establish the multiple non-linear transforms. The hidden-layers of the neural networks are adaptively chosen based on the frequency response of the RF devices to guarantee the accuracy of generated model. The Adam optimization algorithm is utilized for the acceleration of training. With the established deep learning model of a parameterized device, the S parameters can efficiently be obtained when the device geometrical parameters change. Comparing with the traditional modeling method that uses shallow neural networks, the proposed method can achieve better accuracy, especially when the training data are non-uniform. Three RF devices, including a rectangular inductor, an interdigital capacitor, and two coupled transmission lines, are used for building and verifying the deep neural network. It is shown that the deep neural network has good robustness and excellent generalization ability. Even for very wide frequency band (0–100 GHz), the maximum relative error of the coupled transmission lines using the proposed method is below 3%.

Features of the implementation of fixed phase shifters on coupled microstrip transmission lines with a stub

Fixed phase shifters with a phase-shifting channel based on coupled transmission lines of class II with a stub have a number of advantages in comparison with previously known structures for similar purposes. However, their practical implementation causes difficulties associated with the topological features of the structure, which, in turn, leads to a deterioration in frequency characteristics. In this regard, a numerical analysis of inhomogeneities in a class II structure with a stub and an assessment of their influence on the frequency characteristics of fixed phase shifters is required. In this work, circuitry and electrodynamic modeling of class II structure elements has been carried out, which showed that the greatest parasitic effect on the frequency characteristics of the phase shifter has a nonzero coupling coefficient of single transmission lines and an inhomogeneity localized at the junction of the short-circuited stub and the output arms of the associated transmission lines. A fixed phase shifter with a phase-shifting channel based on a smoothly stepped structure with a stub has been developed. The presented results of the study of fixed phase shifters based on microstrip coupled transmission lines of class II with a stub can be useful to scientific and technical workers engaged in the development of functional devices for the phase shift of microwave signals.

Perfect absorption in complex scattering systems with or without hidden symmetries

Wavefront shaping (WFS) schemes for efficient energy deposition in weakly lossy targets is an ongoing challenge for many classical wave technologies relevant to next-generation telecommunications, long-range wireless power transfer, and electromagnetic warfare. In many circumstances these targets are embedded inside complicated enclosures which lack any type of (geometric or hidden) symmetry, such as complex networks, buildings, or vessels, where the hypersensitive nature of multiple interference paths challenges the viability of WFS protocols. We demonstrate the success of a general WFS scheme, based on coherent perfect absorption (CPA) electromagnetic protocols, by utilizing a network of coupled transmission lines with complex connectivity that enforces the absence of geometric symmetries. Our platform allows for control of the local losses inside the network and of the violation of time-reversal symmetry via a magnetic field; thus establishing CPA beyond its initial concept as the time-reversal of a laser cavity, while offering an opportunity for better insight into CPA formation via the implementation of semiclassical tools.