Fully cognitive transceiver for High Frequency (HF) applications

Ionospheric conditions are variable in nature and can cause destructive interference to transmissions made in the High Frequency (HF) band, which ranges from 3-30 MHz. This poses a problem as the HF band is a critical frequency range for various applications (i.e. emergency, military). To manage these dynamic conditions, intelligent techniques should be implemented at the transmitter and receiver to properly maintain reliable communications. In this paper, we present work deriving components of a cognitive HF transceiver with agents called cognitive engines (CEs) operating at the transmitter and receiver. At the transmitter, cognition is employed to determine the combination of modulation and coding techniques that maximize throughput. At the receiver, cognition is implemented to derive the best parameters for equalization (i.e. tap length, step size, filter type, etc.) Results are presented showing that the individual components are able to satisfy their objectives. A discussion is also provided surveying recent research efforts pertaining to the development of cognitive methods for the Automatic Link Establishment (ALE) protocol, a common networking methodology for HF stations.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Toward Scale-Adaptive Subgrid-Scale Model in LES for Turbulent Flow Past a Sphere

This study explores the dynamics of turbulent flow around a sphere at a Reynolds number of Re=103 using large-eddy simulation, focusing on the intricate connection between vortices and strain within the recirculation bubble of the wake. Employing a relatively new subgrid-scale modeling approach based on scale adaptivity, this research implements a functional relation to compute ksgs that encompasses both vortex-stretching and strain rate mechanisms essential for the energy cascade process. The effectiveness of this approach is analyzed in the wake of the sphere, particularly in the recirculation bubble, at the specified Reynolds number. It is also evaluated in comparison with two different subgrid-scale models through detailed analysis of the coherent structures within the recirculation bubble. These models—scale-adaptive, k-Equation, and dynamic k-Equation—are assessed for their ability to capture the complex flow dynamics near the wake. The findings indicate that while all models proficiently simulate key turbulent wake features such as vortex formation and kinetic energy distribution, they exhibit unique strengths and limitations in depicting specific flow characteristics. The scale-adaptive model shows a good ability to dynamically adjust to local flow conditions, thereby enhancing the representation of turbulent structures and eddy viscosity. Similarly, the dKE model exhibits advantages in energy dissipation and vortex dynamics due to its capability to adjust coefficients dynamically based on local conditions. The comparative analysis and statistical evaluation of vortex stretching and strain across models deepen the understanding of turbulence asymmetries and intensities, providing crucial insights for advancing aerodynamic design and analysis in various engineering fields and laying the groundwork for further sophisticated turbulence modeling explorations