A Comparison Between Circular and Hexagonal Array Geometries for Smart Antenna Systems Using Particle Swarm Optimization Algorithm

Abstract

Abstract-In this paper, circular and hexagonal array geometries for smart antenna applications are compared. Uniform circular (UCA) and hexagonal arrays (UHA) with 18 half-wave dipole elements are examined; also planar (2 concentric rings of radiators) uniform circular (PUCA) and hexagonal arrays (PUHA) are considered. The effect of rotating the outer ring of the PUCA is studied. In our analysis, the method of moments is used to compute the response of the uniform circular and hexagonal dipole arrays in a mutual coupling environment. The particle swarm optimization (PSO) algorithm is used to optimize the complex excitations, amplitudes and phases, of the adaptive arrays elements for beamforming.

Displaced Sensor Array for Improved Signal Detection Under Grazing Incidence Conditions

“…However, a ULA does not work equally well for all azimuth directions [7,8]. This major drawback can be resolved by employing other array geometries, such as circular and hexagonal, at the price of a more complex array structure and large array aperture making such array geometries inappropriate to be used at the antenna base stations.…”

“…Recent research efforts into smart antennas have varied from array pattern synthesis based on null steering and multi-user beamforming using a phase control method [5], to augmentation of anti-jam GPS smart antenna system using direction estimation algorithm [6], to a performance study of circular and hexagonal array geometries for smart antenna applications [7], to a comparison between circular and hexagonal array geometries for smart antenna systems using particle swarm optimization [8]. Other research efforts have recently focused on the development of an adaptive and a switched beam smart antenna system for wireless communications [9], tapered beamforming method for uniform circular arrays [10], optimization of the radiation pattern of the antenna array in the direction finding system [11], beam steering with null and excitation constraints for linear antenna arrays [12], and finally DOA estimation bias from inaccurate knowledge of the antnenna array response [13].…”

Low RCS Dipole Array Synthesis Based on Mom-Pso Hybrid Algorithm

“…PSO is an evolutionary algorithm based on the wisdom of crowds, since 1995 Kenndey and Eberhart have presented it [7,8], this algorithm has been widely applied for its faster convergence, clear concept and easy to program [9][10][11][12][13][14]. Its basic idea originates from the study of birds behavior: Birds could find food successfully is the result that each individual analyses its own searching process and all individuals exchange information.…”

Pso-Based Fast Optimization Algorithm for Broadband Ayyray Antenna by Using the Cubic Spline Interpolation

“…In 1995, Kennedy and Eberhart firstly introduced particle swarm optimization (PSO), which is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms [3][4][5][6][7][8][9][10][11][12]. The PSO algorithm is based on a social-psychological principle.…”

“…As a result, the base station antenna should have a 60 • half power beam width (HPBW) and adaptive main lobe direction. Many array antenna pattern synthesis methods have been studied [3,4,7,8,10,11], however, most literatures mainly focus on single frequency or narrowband optimization. In modern communication system, frequency hopping spread spectrum is usually adopted to further increase the data transmission rate.…”