Search

Design and analysis of a compact multi-band flexible antenna are presented here. The antenna is designed using the flexible substrate material Rogers 5880 and has a compact size of 18mmx18mmx0.254mm. The coplanar waveguide (CPW) fed radiator consists of a rectangular-shaped patch modified using a pair of rectangular slots to achieve the required bandwidth. Another smaller slot was etched in the radiator to achieve a lower resonance. The proposed design offers a multi-band functionality covering ISM, WLAN, Wi-Fi, and upper 5G sub6-GHz bands., QC 20220926Part of proceedings: ISBN 978-9-4639-6805-8

The paper presents the results of a novel 3-D shared aperture 3 x 3 matrix antenna-array for 26 GHz band 5 G wireless networks. Radiation elements constituting the array are hexagonal-shaped patches that are elevated above the common dielectric substrate by 3.35 mm and excited through a metallic rod of 0.4 mm diameter. The rod protrudes through the substrate of 0.8 mm thickness. It is shown that by isolating each radiating element in the array with a wall suppresses unwanted electromagnetic (EM) wave interactions, resulting in improvement in the antenna's impedance matching and radiation characteristics. Moreover, the results show that by embedding hexagonalshaped slots in the patches improve the antenna's gain and radiation efficiency performance. The subwavelength length slots in the patches essentially transform the radiating elements to exhibit metasurface characteristics when the array is illuminated by EM-waves. The proposed array structure has an average gain and radiation efficiency of 20 dBi and 93%, respectively, across 24.0-28.4 GHz. The isolation between its radiation elements is greater than 22 dB. Compared to the unslotted array the improvement in isolation between radiating elements is greater than 11 dB, and the gain and efficiency are better than 10.5 dBi, and 25%, respectively. The compact array has a fractional bandwidth of 16% and a form factor of 20 x 20 x 3.35 mm(3)., QC 20220926

In this survey, we analyze the newest machine learning (ML) techniques for optical orthogonal frequency division multiplexing (O-OFDM)-based optical communications. ML has been proposed to mitigate channel and transceiver imperfections. For instance, ML can improve the signal quality under low modulation extinction ratio or can tackle both determinist and stochastic-induced nonlinearities such as parametric noise amplification in long-haul transmission. The proposed ML algorithms for O-OFDM can in particularly tackle inter-subcarrier nonlinear effects such as four-wave mixing and cross-phase modulation. In essence, these ML techniques could be beneficial for any multi-carrier approach (e.g. filter bank modulation). Supervised and unsupervised ML techniques are analyzed in terms of both O-OFDM transmission performance and computational complexity for potential real-time implementation. We indicate the strict conditions under which a ML algorithm should perform classification, regression or clustering. The survey also discusses open research issues and future directions towards the ML implementation., Comment: 26 pages, 4 figures and 4 tables

A new flexible, secure FSO-CDMA system supporting end-to-end network resource slicing is proposed and investigated. New mathematical formalisms considering distinct turbulence conditions are derived. The system supports different applications, use cases, and traffic requirements.

A new flexible, secure FSO-CDMA system supporting end-to-end network resource slicing is proposed and investigated. New mathematical formalisms considering distinct turbulence conditions are derived. The system supports different applications, use cases, and traffic requirements.