Patch antenna design optimization using opposition based grey wolf optimizer and map-reduce framework

Abstract

Purpose

Microstrip patch antenna is generally used for several communication purposes particularly in the military and civilian applications. Even though several techniques have been made numerous achievements in several fields, some systems require additional improvements to meet few challenges. Yet, they require application-specific improvement for optimally designing microstrip patch antenna. The paper aims to discuss these issues.

Design/methodology/approach

This paper intends to adopt an advanced meta-heuristic search algorithm called as grey wolf optimization (GWO), which is said to be inspired by the hunting behaviour of grey wolves, for the design of patch antenna parameters. The searching for the optimal design of the antenna is paced up using the opposition-based solution search. Moreover, the proposed model derives a nonlinear objective model to aid the design of the solution space of antenna parameters. After executing the simulation model, this paper compares the performance of the proposed GWO-based microstrip patch antenna with several conventional models.

Findings

The gain of the proposed model is 27.05 per cent better than WOAD, 2.07 per cent better than AAD, 15.80 per cent better than GAD, 17.49 per cent better than PSAD and 3.77 per cent better than GWAD model. Thus, it has proved that the proposed antenna model has attained high gain, leads to cause superior performance.

Originality/value

This paper presents a technique for designing the microstrip patch antenna, using the proposed GWO algorithm. This is the first work utilizes GWO-based optimization for microstrip patch antenna.

Citation

Guttula, R. and Nandanavanam, V.R. (2020), "Patch antenna design optimization using opposition based grey wolf optimizer and map-reduce framework", Data Technologies and Applications, Vol. 54 No. 1, pp. 103-120. https://doi.org/10.1108/DTA-06-2019-0084