Firefly Optimization Scheme On Non Uniform Antenna Array Using Method Of Moment Using Matlab
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ABSTRACT
The element failure of antenna arrays increases the side lobe power level. In this paper, the problem of antenna array failure has been addressed using Firefly Algorithm (FA) by controlling only the amplitude excitation of array elements. A fitness function has been formulated to obtain the error between pre-failed (original) sidelobe pattern and measured sidelobe pattern and this function has been minimized using FA. Numerical example of large number of element failure correction is presented to show the capability of this flexible approach.
TABLE OF CONTENTS
COVER PAGE
TITLE PAGE
APPROVAL PAGE
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
CHAPTER ONE
1.1 INTRODUCTION
1.2 AIM OF THE STUDY
1.3 OBJECTIVE OF THE STUDY
1.4 EFFECT OF NON-UNIFORM ANTENNA ARRAY
1.5 IMPORTANCE OF ANTENNA ARRAY
CHAPTER TWO
LITERATURE REVIEW
2.1 OVERVIEW OF ANTENNA ARRAY
2.2 REVIEW OF THE STUDY AND APPROACH TO THE PROBLEM
CHAPTER THREE
PROBLEM FORMULATION
3.1 FIREFLY ALGORITHM
CHAPTER FOUR
4.1 SIMULATION RESULTS AND DISCUSSION
CHAPTER FIVE
- CONCLUSION
- REFERENCES
CHAPTER ONE
- INTRODUCTION
For wireless communication system, the antenna array is one of the most important components to improve the system capacity and spectral efficiency. The active antenna array is widely used in many applications like satellite communication, sonar, mobile communication etc. for signal acquisition purpose. Generally the antenna array consists of large number of radiating elements or sub- arrays. Due to large number of elements presented in an array, there is always a possibility of failure of one or more elements in the antenna array system. The failures of elements in the array destroy the symmetry and may cause sharp variation in field intensity across the array, distort the pattern in the form of increased sidelobe level. In some situation like space platform the replacement of the defective element of the array is not possible. It is possible in case of active antennas to restore the radiation pattern with minimal loss of quality without replacing the defective element by controlling the excitations of the normal antenna elements of the array. Many conventional techniques are proposed to solve this problem by improving the array pattern in presence of defective elements like a numerical technique based algorithm [1] to regain the directional pattern of linear antenna array with single element failure conditions, the accumulated averaging scheme combined with the conjugate gradient algorithm [2] for partial compensate the degraded pattern of hexagonal array, shore’s sidelobe sector nulling method [3], an orthogonal method [4], conjugate gradient based method [5].
Generally analytical approaches unable to handle failed element problem, where antenna array considered as nonuniformly spaced array. This problem is also a challenging problem for numerical approaches due to arbitrariness of the geometrical layout of the remaining non defective array elements and of the desired beam shape. Population-based, stochastic methods can provide an effective solution for such problems, as they tend to explore multiple solutions simultaneously, relying only on zero order information. Many stochastic methods have been proposed to solve the problem of antenna array failure using Genetic Algorithm (GA) [6, 7], use of combination of GA and Fast Fourier Transform(FFT) [8], adaptive neuronal system [9], Simulated Annealing (SA) [10, 11].
In this paper, an effective method based on the Firefly Algorithm (FA) is proposed for array failure correction of arbitrary linear antenna arrays. The FA algorithm is a new swarm intelligence based algorithm [12–14] which can deal with continuous variables in multi- dimensional spaces more naturally and efficiently. The FA has been shown to outperform Artificial Bees Colony Algorithm (ABC) in terms of convergence and cost minimization in a statistically meaningful way [15]. The performance of FA has been found more superior than Particle Swarm Optimization (PSO) in terms of finding optimum solutions for the desired beam patterns of ring antenna array [16].
For a uniformly spaced linear array, the array-failure correction is a much more complex problem than simple sidelobe reduction in antenna design. In this paper, FA has been successfully applied first time for linear antenna array failure problem and the antenna pattern has been corrected using amplitude only control. The amplitude only control is preferred as it is simple to implement than amplitude and phase control because it does not need accurate adjustment of phase shifters and only attenuators have to be adjusted in amplitude only control [17]. A large failure rate (31.25%) has been considered to demonstrate the effectiveness of this algorithm.
The problem formulation has been discussed and modeled the fitness function in the second section. Third section of the paper gives a brief introduction of FA algorithm. Simulation results and discussion has been presented in chapter 4 and the work has been concluded in the last section.
1.1 AIM OF THE STUDY
The aim of this work is to investigate the optimization of non-uniform linear antenna arrays (NULAs) for millimeter wave (mmWave) line-of-sight (LoS) multiple-input multiple-output (MIMO) channels.
1.2 OBJECTIVE OF THE STUDY
Our objective focus is on the maximization of the system effective multiplexing gain (EMG), by optimizing the individual antenna positions in the transmit/receive NULAs.
1.3 EFFECT OF NON-UNIFORM ANTENNA ARRAY
More than one antenna element can be arranged in any defined configuration along a co-ordinate system to generate an array antenna, But when this array is not uniform it will lead to low directivity and poor radiation pattern which makes the radiated signal prone to fading and attenuation in long distance communication.
1.4 IMPORTANCE OF ANTENNA ARRAY
An antenna array is a set of 2 or more antennas. The signals from the antennas are combined or processed in order to achieve improved performance over that of a single antenna. The antenna array can be used to:
- increase the overall gain
- provide diversity reception
- cancel out interference from a particular set of directions
- “steer” the array so that it is most sensitive in a particular direction
- determine the direction of arrival of the incoming signals
- to maximize the Signal to Interference Plus Noise Ratio (SINR)
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