Thinned Concentric Circular Antenna Array Synthesis using Particle Swarm Optimization

AbstractThis paper presents an optimal thinning of a large multiple concentric circular ring arrays of uniformly excited isotropic antennas based on Particle Swarm Optimization method. Circular Antenna Array (CAA) has gained immense popularity in the field of communications nowadays. It has proved to be a better alternative over other types of antenna array configuration due to its all-azimuth scan capability, and the beam pattern which can be kept invariant. In this paper, a 9 ringed Concentric Circular Antenna Array (CCAA) with central element feeding is considered. Extensive simulation results justify the optimization efficacy of the proposed approach for antenna array synthesis. The simulation results show that the number of effective antenna elements can be brought down from 279 to 139 with simultaneous reduction in Side Lobe Level by 20.37dB relative to the main beam with a fixed half power beamwidth using PSO. Real coded Genetic Algorithm (RGA) as well is also adopted to compare the results of PSO algorithm

Optimization of linear wire antenna arrays to increase MIMO capacity using swarm intelligence

Free standing linear arrays (FSLA) are analyzed and optimized to increase MIMO capacity. A MIMO channel model based on electric fields is used. The effects of mutual interactions among the array elements are included into the channel matrix using method of moments (MoM) based full-wave solvers. A tool to design an antenna array of superior MIMO capacity for any specified volume is developed. Particle swarm optimization is used as the main engine for the optimization tasks of the tool. Uniform linear arrays, uniform circular arrays and non-uniform arrays are analyzed and compared in terms of their channel capacity

IWO-based Synthesis of Log-Periodic Dipole Array

The Invasive Weed Optimization (IWO) is an effective evolutionary and recently developed method. Due to its better performance in comparison to other well-known optimization methods, IWO has been chosen to solve many complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO is applied to optimize the geometry of a realistic log-periodic dipole array (LPDA) that operates in the frequency range 800-3300 MHz and therefore is suitable for signal reception from several RF services. The optimization is applied under specific requirements, concerning the standing wave ratio, the forward gain, the gain flatness and the side lobe level, over a wide frequency range. The optimization variables are the lengths and the radii of the dipoles, the distances between them, and the characteristic impedance of the transmission line that connects the dipoles. The optimized LPDA seems to be superior compared to the antenna derived from the practical design procedure

Nature-inspired Cuckoo Search Algorithm for Side Lobe Suppression in a Symmetric Linear Antenna Array

In this paper, we proposed a newly modified cuckoo search (MCS) algorithm integrated with the Roulette wheel selection operator and the inertia weight controlling the search ability towards synthesizing symmetric linear array geometry with minimum side lobe level (SLL) and/or nulls control. The basic cuckoo search (CS) algorithm is primarily based on the natural obligate brood parasitic behavior of some cuckoo species in combination with the Levy flight behavior of some birds and fruit flies. The CS metaheuristic approach is straightforward and capable of solving effectively general N-dimensional, linear and nonlinear optimization problems. The array geometry synthesis is first formulated as an optimization problem with the goal of SLL suppression and/or null prescribed placement in certain directions, and then solved by the newly MCS algorithm for the optimum element or isotropic radiator locations in the azimuth-plane or xy-plane. The study also focuses on the four internal parameters of MCS algorithm specifically on their implicit effects in the array synthesis. The optimal inter-element spacing solutions obtained by the MCS-optimizer are validated through comparisons with the standard CS-optimizer and the conventional array within the uniform and the Dolph-Chebyshev envelope patterns using MATLABTM. Finally, we also compared the fine-tuned MCS algorithm with two popular evolutionary algorithm (EA) techniques include particle swarm optimization (PSO) and genetic algorithms (GA)

Emitter Location Finding using Particle Swarm Optimization

Using several spatially separated receivers, nowadays positioning techniques, which are implemented to determine the location of the transmitter, are often required for several important disciplines such as military, security, medical, and commercial applications. In this study, localization is carried out by particle swarm optimization using time difference of arrival. In order to increase the positioning accuracy, time difference of arrival averaging based two new methods are proposed. Results are compared with classical algorithms and Cramer-Rao lower bound which is the theoretical limit of the estimation error

Thinning of concentric two-ring circular array antenna using fire fly algorithm

AbstractThe paper describes the application of novel meta-heuristics of the fire fly algorithm for reduction of the maximum Side Lobe Level (SLL) with specific First Null Beam Width (FNBW) of thinned two-ring Uniform Concentric Circular Arrays (UCCA) of isotropic elements. The effect of thinning is analyzed in the four subsequent examples using uniform and non-uniform excitations for different FNBW. Optimization is carried out without and with prefixing the value of the percentage of thinning. The UCCA containing 35 and 70 elements in the two successive concentric rings is optimized using FFA. The example using non-uniform excitation is proved more efficient to reduce SLL for same FNBW. Simulation results show the SLL performance improves as we chose the FNBW wider in the designing problem. Fixing the percentage of thinning at a higher value increases the power efficiency of the feeding network with little compromise on the design specifications. The non-uniformly excited thinned concentric array is again optimized using two more state-of-the-art algorithms, namely, Particle Swarm Optimization (PSO) and Differential Evolution (DE) to compare the effectiveness of each algorithm in a statistically meaningful way. Design results using fire fly algorithm shows better performances compared to PSO and DE provided the same number of function evaluation has been considered for all the algorithms

Reduce side lobes using linear Antenna Arrays by comparing PSO, GA, and FPA algorithms

ان مصفوفات الهوائي الخطي هي نظام كهرومغناطيسي يستخدم على نطاق واسع في الاتصالات اللاسلكية الحديثة، وقد تم استخدام خوارزميات الميتاهوريستس لتقليل مستوى الفص الجانبي والوصول إلى الحل الأمثل. يستخدم هذه البحث ثلاث خوارزميات: الأولى، تحسين سرب الجسيمات، والثانية، الخوارزمية الجينية، والثالثة، خوارزمية تلقيح الزهور. يتكون كل اختبار من عدد العناصر 8و16و32و64و128و256. عنصرًا من مجموعة عناصر الهوائي. لتقليل مستوى الفص الجانبي وتركيز الطاقة المشعة في الفص الرئيسي، تقارن كل خوارزمية نمط الحزمة بنمط الحزمة النظرية. بالإضافة إلى ذلك، تمت مقارنة الخوارزميات بوجود نمط الحزمة النظرية، وتم اكتشاف وجود خوارزمية فائقة لكل عدد من عناصر الهوائي؛ في ن= 8 عند مقارنة خوارزمية التلقيح بالخوارزميات الأخرى، تم اكتشاف أنها قللت مستوى الفص الجانبي بقيمة 20.8492- ديسبل، والتي كانت متفوقة على الخوارزميات الأخرى. انخفض مستوى الفص الجانبي بمقدار 27.2992- ديسبل، عند مقارنة خوارزمية تحسين سرب الجسيمات مع الخوارزميات الأخرى عند ن=16, عندما ن = 32,64 يمثل خوارزمية تلقيح الجسيمات بشكل أكثر دقة من الخوارزميات الأخرى حيث انخفض الفص الجانبي إلى 28.3071-ديسبل و 28.0148- ديسبل، على التوالي. ان الخوارزمية الجينية متفوقة على الخوارزميات الأخرى عندما ن= 128و256، مما يقلل الفصوص الجانبية بنسبة 28.5568- ديسبل -28.6204- ديسبل، على التوالي.Linear Antenna Arrays (LAAs) are widely used electromagnetic systems in modern wireless communication, and Metaheuristics algorithms have been utilized to reduce side lobe level SLL and reach the optimal solution. This paper employs three algorithms: the first, Particle Swarm Optimization PSO, the second, Genetic Algorithm GA, and the third, Flower Pollination Algorithm FPA. Each test consists of N = 8, 16, 32, 64, 128, and 256 antenna array elements. To reduce SLL and the concentration of radioactive energy in the main lobe, each algorithm compares the beam pattern to the theoretical beam pattern. In addition, the algorithms were compared with the existence of the theoretical beam pattern, and it was discovered that there is a superior algorithm for each number of antenna elements; in N = 8, when comparing FPA to other algorithms, it was discovered that FPA reduced SLL by a value of -20.8492dB, which was superior to the other algorithms. SLL decreased by -27.2992dB when comparing PSO with other algorithms at N = 16. When N = 32,64 represents FPA more accurately than other algorithms where the SLL plummeted to -28.3071dB and -28.0148dB, respectively. GA is superior to other algorithms when N = 128,256, reducing SLL by -28.5568 dB and -28.6204 dB, respectively