Amalendu Patnaik

ANN techniques in microwave engineering

In the last two decades, artificial neural network (ANN) technology has leaped forward and is now being applied in different areas such as speech recognition, control, telecommunication, remote sensing, pattern recognition, etc. ANN application to the field of microwaves is very recent. This article reviews the development of neural network techniques, introduces some basic concepts involved in it, and gives a comprehensive survey of neural network application to different branches of microwave engineering.

Defected Ground Structure in the perspective of Microstrip Antennas: A Review

Defected ground structures (DGS) have been developed to improve characteristics of many microwave devices. Although the DGS has advantages in the area of themicrowave filter design, microwave oscillators, microwave couplers to increase the coupling, microwave amplifiers, etc., it is also used in the microstrip antenna design for different applications such as antenna size reduction, cross polarization reduction,mutual coupling reduction in antenna arrays, harmonic suppression etc., TheDGS ismotivated by a study of Photonic/Electromagnetic Band gap structures. The etching of one or more PBG element creates defect in the ground plane and used for the same purpose. The DGS is easy to be an equivalent L-C resonator circuit. The value of the inductance and capacitance depends on the area and size of the defect. By varying the various dimensions of the defect, the desired resonance frequency can be achieved. In this paper the effect of DGS, to the different antenna parameter enhancement is studied. Index Terms – Defected Ground Structure, Microstrip Antennas.

Applications of neural networks in wireless communications

In recent years, the art of using neural networks (NNs) for wireless-communication engineering has been gaining momentum. Although it has been used for a variety of purposes and in different ways, the basic purpose of applying neural networks is to change from the lengthy analysis and design cycles required to develop high-performance systems to very short product-development times. This article overviews the current state of research in this area. Different applications of neural-network techniques for wireless communication front ends are briefly reviewed, stressing the purpose and the way neural networks have been implemented, followed by a description of future avenues of research in this field.

Designing rectangular patch antenna using the neurospectral method

This paper presents a new method for developing computer-aided design (CAD) models, using spectral domain (SD) formulation. Using the artificial neural network (ANN) technique, a combination of continuous function and delta functions constitutes the spectral domain Greens functions. We obtain closed-form formulas for integration involving these equations. Another neural network relates different antenna parameters. Utilizing the reverse modeling for patch dimension determination, it becomes useful as a CAD model for patch antenna design. Designs, of simple rectangular patch antennas, serve as illustration of this method.

An artificial neural network model for effective dielectric constant of microstrip line

A backpropagation network structure is presented for the calculation of the effective dielectric constant (/spl epsiv//sub eff/) of microstrip lines. Results of the network are compared with those of the spectral-domain (SD) technique.

An ANN Application for Fault Finding in Antenna Arrays

A very flexible approach of locating fault elements in antenna arrays is proposed using artificial neural networks (ANN). The network takes samples of radiation pattern of the array with fault elements and maps it to the location of the faulty element in that array. The developed methodology is tested for a linear array and the same can easily be extended for planar arrays also. The developed network can be used at the base stations to find out the number and location of the fault elements in the array in space platforms

Neurocomputational analysis of a multiband reconfigurable planar antenna

Procedures using neural networks are developed for characterizing multiband reconfigurable antennas. A multilayer perceptron (MLP) is used to locate the operational frequency bands of the antenna at different reconfigured conditions. Another self-organizing map (SOM) neural network accomplishes the task of locating the switches to be turned ON for a desired frequency response. The developed formulation is tested on a laboratory prototype antenna.

An Accurate FDTD Model for Crosstalk Analysis of CMOS-Gate-Driven Coupled RLC Interconnects

This paper accurately models the crosstalk effects in a CMOS-gate-driven coupled RLC interconnects using the nth power law model and finite-difference time-domain (FDTD) technique. The propagation delay, peak crosstalk voltage, and peak voltage timing on victim line of coupled-multiple lines are observed and compared to HSPICE simulation results for the global interconnect length at 32 nm technology node. The numerical results illustrate that the proposed model accurately estimates the performance parameters of driver interconnect load system. An average error of less than 2% is observed in estimation of peak crosstalk voltage and its timing. The proposed model can be extended for coupled n lines and useful for the evaluation of signal integrity, issues of EMI, and EMC of on-chip interconnects.

MICROSTRIP PATCH ANTENNA WITH SKEW-F SHAPED DGS FOR DUAL BAND OPERATION

The goal of this paper is to use defected ground structure (DGS) in microstrip antennas for dual band operation at microwave frequencies. The soft nature of the DGS facilitates improvement in the performance of microstrip antennas. A design study on microstrip patch antenna with speciflc DGS slot has been presented in the proposed work. In this paper, a stacked microstrip patch antenna (SMPA) has been designed for broadband behavior, and then skew- F shaped DGS has been integrated with a detailed study of possible DGS slots in a small area for dual band operation. The design and optimization of both the SMPA and DGS structures along with the parametric study were carried out using CST Microwave Studio V.9. Further, the dual band antenna, i.e., the SMPA with skew-F shaped DGS, has been fabricated, and the experimental results have shown a good agreement with the simulation ones.

Neurospectral computation for complex resonant frequency of microstrip resonators

Spectral domain formulation is followed by the neural network technique to determine the resonant frequency of open microstrip resonators. This neurospectral approach considerably reduces the problem complexity. The results of the neurospectral technique compare well with those of traditional spectral domain technique.