Bacteria Foraging Optimization in Antenna Engineering: An Application to Array Fault Finding

Finding fault elements in linear antenna arrays using bacteria foraging optimization (BFO) is presented. One of the better options of array diagnosis is to perform it by measuring the radiated field, because in this case, removal of the array from its working site is not required and thereby not interrupting its normal operation. This task of fault finding from far-field data is designed as an optimization problem where the difference between the far-field power pattern obtained for a given configuration of failed element(s) and the measured one is minimized w. r. t. the excitations of the array elements. This set of excitations on comparison with the excitations of the original array gives the idea of the fault position and their type, such as either complete fault or partial fault. BFO being relatively new to microwave community when compared with other soft-computing techniques, its performance was observed w. r. t. time of computation and convergence of the iterative process. Possibility of finding the faults from random sample points and use of minimum number of sample points for array fault finding are the novelties of the present work

Neural networks in antenna engineering - Beyond black-box modeling

Abstract- Recently neural networks have been applied in antenna modeling where the role of the network is not just for black-box modeling. This paper highlights that aspect of neural networks from the antenna engineering application point of view

Null Steering in Failed Antenna Arrays

Antenna array pattern nulling is desirable in order to suppress the interfering signals. But in large antenna arrays, there is always a possibility of failure of some elements, which may degrade the radiation pattern with an increase in side lobe level (SLL) and removal of the nulls from desired position. In this paper a correction procedure is introduced based on Particle Swarm Optimization (PSO) which maintains the nulling performance of the failed antenna array. Considering the faulty elements as nonradiating elements, PSO reoptimizes the weights of the remaining radiating elements to reshape the pattern. Simulation results for a Chebyshev array with imposed single, multiple, and broad nulls with failed antenna array are presented

Crosstalk in Modern On-Chip Interconnects

The book provides accurate FDTD models for on-chip interconnects, covering most recent advancements in materials and design. Furthermore, depending on the geometry and physical configurations, different electrical equivalent models for CNT and GNR based interconnects are presented. Based on the electrical equivalent models the performance comparison among the Cu, CNT and GNR-based interconnects are also discussed in the book. The proposed models are validated with the HSPICE simulations. The book introduces the current research scenario in the modeling of on-chip interconnects. It presents the structure, properties, and characteristics of graphene based on-chip interconnects and the FDTD modeling of Cu based on-chip interconnects. The model considers the non-linear effects of CMOS driver as well as the transmission line effects of interconnect line that includes coupling capacitance and mutual inductance effects. In a more realistic manner, the proposed model includes the effect of width-dependent MFP of the MLGNR while taking into account the edge roughness