Optimizing Wireless Systems with

Electromagnetic Simulation

Electromagnetic simulation has dramatically improved the design of a wide

range of wireless systems by making it possible for engineers to simulate

their operation and predict their performance without the need for building

and testing of prototypes. But while a design concept can generally be

simulated in far less time than it can be built or tested, simulation by itself

still frequently requires modeling of a large number of alternatives without

any assurance of achieving an optimized design. Researchers at the

Computational Electromagnetics Research Laboratory at McMaster

University, Hamilton, Ontario, have addressed this challenge by developing

an efficient method for optimizing the design of wireless systems based on

sensitivity analysis of the scattering parameters (S-parameters). The basic

idea is that the number of simulations required to identify an optimized

design can be reduced by determining the design sensitivity with respect to

its shape and material parameters. This makes it possible to iterate to an

optimized design in much less time than was required in the past.

Electromagnetic simulation takes only a small fraction of the time and

expense involved in building and testing wireless systems. Simulation also

provides more information than physical experiments by yielding results at

every point in the solution domain, far exceeding the results that can be

achieved with physical measurements. The simulation itself provides an

analysis of the system such that the results of each simulation provide

insight into only a single point in the design space. To obtain a more

complete picture of the design space, a series of simulations must normally

be carried out. Optimization streamlines the process of exploring the design

space.

New method reduces optimization time

Researchers Natalia Nikolova, Ying Li, Yan Li, and Mohammed Bakr of the

Computational Electromagnetics Laboratory at McMaster University have

made a significant advancement in this area by developing a sensitivity

analysis method that specifically targets wireless systems. "The new

approach greatly reduces the number of simulations required to optimize the

design by calculating the sensitivity or derivatives of the S-parameters with

respect to changes in design variables," Nikolova said. "It uses a fast