Improvement of Adaptive Smart Concentric Circular Antenna Array Based Hybrid PSOGSA Optimizer

Ahmed Magdy,Osama M,Hesham F

doi:10.14569/ijacsa.2016.070637

Ahmed Magdy, Osama M + Show 1 more

Open Access

https://doi.org/10.14569/ijacsa.2016.070637

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Abstract

Unlike all recent research which used Concentric Circular Antenna Array (CCAA) based on one beam-former for each single main beam, this research presents a technique to adapt smart CCAA by using only single beam-former for multi main beams based on hybrid PSOGSA. Hybrid PSOGSA is a combining technique between Particle Swarm Optimization and Gravitational Search Algorithm which is applied in the feeding of the smart CCAA to enhance its performance. Phase excitation of the array with a large number of elements is suggested for different scenarios based on hybrid PSOGSA and other algorithms such as PSO and GSA in High Altitude Platform (HAP) application. Simulation results proved that hybrid PSOGSA achieves better performance than other optimizers for excitation of the smart CCAA in all scenarios for different parameters like normalized array factor, fitness values, convergence rate, and directivity

Highlights

Smart antenna was one of the main parts in various communication systems [1,2,3]
In [22], an algorithm based on collective animal behaviour (CAB) is used for finding the best optimal excitation weights for linear antenna arrays, but in [4,5], hybrid PSOGSA utilizing UCA achieved better results than ULA in terms of studying the directed power in terms of normalized array factor toward the intended direction in addition to direct null to signal Not of interest (SNOI) for different scenarios
When PSOGSA is compared with other previous algorithms like Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) according to many factors such as normalized array factor using(1), directivity using (3) as shown in [7] and computational speed with convergence rate for normalized fitness values using (2)

Summary

INTRODUCTION

Smart antenna was one of the main parts in various communication systems [1,2,3]. Circular Antenna Array (CAA) [4,5] was considered recently in the latest research because of its ability to steer the radiation pattern more than linear antenna arrays and overcoming the broadside problem. The suggested Gravitational Search Algorithm (GSA) in [15] was used for Direction of Arrival estimation in smart antenna systems and achieved better results than MUSIC and PSO in [16]. Hybrid Particle Swarm Optimization with Gravitational Search Algorithm (Hybrid PSOGSA) technique was considered as a new optimization technique that showed better performance than standard PSO and GSA in terms of computational speed and fitness values [20,21]. In [22], an algorithm based on collective animal behaviour (CAB) is used for finding the best optimal excitation weights for linear antenna arrays, but in [4,5], hybrid PSOGSA utilizing UCA achieved better results than ULA in terms of studying the directed power in terms of normalized array factor toward the intended direction in addition to direct null to signal Not of interest (SNOI) for different scenarios.

OPTIMIZATION PROBLEM MODEL

HYBRID PSOGSA OPTIMIZER

SIMULATION AND DISCUSSION RESULTS

CONCLUSION