Combination of genetic algorithm (GA) and fast fourier transform (FFT) for synthesis of arrays

Abstract

In Figure 5(a)-(b), the bias dependency of both drain current and S parameters are accurately captured by the neural network. In addition, a harmonic balance simulation tests the accuracy of the model for large-signal non-linear simulation. Figure 5(c) shows simulated output power for fundamental, second, and third harmonics both as a function of input power and compared with measurement beyond the 1-dB compression point. As can be seen, accurate reproduction of output power at fundamental frequency has been achieved, with second and third harmonics having a maximum error of only 2-3 dBm over the power sweep range. The power level is pushed beyond the compression point to illustrate the validity of the model under high power conditions. CONCLUSIONWe have reported a neural-network-based non-linear model for CMOS, based on capacitance, extrinsic gate, and substrate resistances parameters together with drain current. The parameters used in the model show strong dependency on bias, which are difficult to formulate accurately using empirical equation. Therefore, we have used three-layered neural network architecture to derive parameter-bias-dependent function. The developed non-linear function has then been adopted in a commercial ADS circuit simulator, using symbolically defined devices (SDD) required for implementation of the CMOS non-linear model. The non-linear mode of operation of the full model has been validated, including harmonic power, and good fits were obtained.

QPSO versus BSA for Failure Correction of Linear Array of Mutually Coupled Parallel Dipole Antennas with Fixed Side Lobe Level and VSWR

“…This relationship is primarily used here for the sole purpose of reducing the overall computing time. Wang et al [5] incorporated the principles of IFFT in obtaining the array factor computation in a short time and verified successfully the proposed idea for both the linear and planar arrays.…”

“…A method [3] based on evolutionary algorithm, namely, genetic algorithm [3][4][5], has been utilized for failure correction by considering the beam weights as an array of complex vector numbers. This algorithm has also been used by Rodriguez et al [4], successfully in such a way that the adjustments of excitations for minimum number of elements were needed to recover the radiation pattern.…”

“…Moreover, literature survey also reveals that inverse fast Fourier transform [5,8,9] can be used to speed up the whole process of failure correction. Here, the relationship of inverse fast Fourier transform (IFFT) with the current excitations of the antenna leading to the array factor is utilized and has been used for synthesis of low side lobe radiation patterns [9].…”

Combination of Inverse Fast Fourier Transform and Modified Particle Swarm Optimization for Synthesis of Thinned Mutually Coupled Linear Array of Parallel Half-Wave Length Dipole Antennas

“…Wang et al [14] designed arrays by the combination of Genetic Algorithm (GA) and Fast Fourier Transform (FFT).…”

“…The element pattern in the horizontal plane is very similar to an isotropic source. Computation time may be significantly reduced by using fast Fourier transform [14].…”