Fast Antenna Characterization Using the Sources Reconstruction Method on Graphics Processors

Abstract

Abstract-The Sources Reconstruction Method (SRM) is a noninvasive technique for, among other applications, antenna characterization. The SRM is based on obtaining a distribution of equivalent currents that radiate the same field as the antenna under test. The computation of these currents requires solving a linear system, usually ill-posed, that may be very computationally demanding for commercial antennas. Graphics Processing Units (GPUs) are an interesting hardware choice for solving compute-bound problems that are prone to parallelism. In this paper, we present an implementation on GPUs of the SRM applied to antenna characterization that is based on a compute-bound algorithm with a high degree of parallelism. The GPU implementation introduced in this work provides a dramatic reduction on the time cost compared to our CPU implementation and, in addition, keeps the low-memory footprint of the latter. For the sake of illustration, the equivalent currents are obtained on a base station antenna array and a helix antenna working at practical frequencies. Quasi real-time results are obtained on a desktop workstation.

A Multi-Gpu Sources Reconstruction Method for Imaging Applications

“…It is worth noting the high occupancy (defined as the ratio of the number of active threads to the maximum possible number of active threads) is achieved due to the moderate usage of both registers and shared memory. The occupancy has gone from 33% in [25] to 42-58% in the case of the Fermi GPUs and 56-75% in the case of the Kepler GPUs. In order to compare the current occupancy to that of our previous work [25], the occupancy calculator that is part of the CUDA toolkit [39] has been used.…”

“…The occupancy has gone from 33% in [25] to 42-58% in the case of the Fermi GPUs and 56-75% in the case of the Kepler GPUs. In order to compare the current occupancy to that of our previous work [25], the occupancy calculator that is part of the CUDA toolkit [39] has been used.…”

“…Those kernels that deal with the reconstruction of the equivalent currents were first used by the authors in [25]. Since then, we found several ways for improving the performance of the above mentioned kernels.…”

“…Therefore, and taking into account our previous experience [25], the Sources Reconstruction Method (SRM) seems to be an algorithm able to fully exploit the massively parallel architecture of the GPUs.…”

A Semi-Analytical Method to Calculate the Entries of the Method of Moments Matrix for the Mixed Potential Integral Equation of a Source Reconstruction Problem

“…[20] is related with using the source reconstruction method for the accurate modeling of the noise sources in an electronic circuit and the estimation of the noise to be radiated by the circuit. [21] is about employing the graphical processing unit(GPU) with the memory saving technique to calculate the elements of the impedance matrix of the integral equation to find the equivalent currents. [22] describes the use of the source reconstruction method for the modeling of a frequency scanning antenna array of an imaging system.…”