Performance Enhancement for Adaptive Beam-Forming Application Based Hybrid PSOGSA Algorithm

Ahmed Magdy¹, Osama M. EL-Ghandour², Hesham F. A. Hamed^1*

¹Department of Electrical Engineering, Minia University, Minia, Egypt.
²Department of Electronics, Communications and Computer Engineering, Helwan University, Cairo, Egypt.

DOI: 10.4236/jemaa.2015.74014                

Abstract

Recently researchers were interested in hybrid algorithms for optimization problems for several communication systems. In this paper, a novel algorithm based on hybrid PSOGSA technique (combination of Gravitational Search Algorithm and Particle Swarm Optimization) is presented to enhance the performance analysis of beam-forming for smart antennas systems using N elements for Uniform Circular Array (UCA) geometry. Complex excitations (phases) of the array radiation pattern are optimized using hybrid PSOGSA technique for a set of simultaneously incident signals. Our results have shown tremendous improvement over the previous work was done using Uniform Linear Array (ULA) geometry and standard GSA in terms of normalized array factor and computational speed for normalized fitness values.

Keywords

Smart Antennas, UCA, Optimization Techniques, Beam-Forming

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Lehne, P.H. and Pettersen, M. (1999) An Overview of Smart Antenna Technology for Mobile Communications Systems. IEEE Communications Surveys and Tutorials, 2, 2-13.
[2]	Chryssomallis, M. (2000) Smart Antennas. IEEE Antennas and Propagation Magazine, 42, 129-136. http://dx.doi.org/10.1109/74.848965
[3]	Kennedy, J. and Eberhart, R. (1995) Particle Swarm Optimization. Proceedings of IEEE International Conference on Neural Networks, Perth, 27 November-01 December 1995, 4, 1942-1948. http://dx.doi.org/10.1109/ICNN.1995.488968
[4]	Mahmoud, K.R., Eladawy, M., Bansal, R., Zainud-Deen, S.H. and Ibrahem, S.M.M. (2008) Analysis of Uniform Circular Arrays for Adaptive Beamforming Applications Using Particle Swarm Optimization Algorithm. International Journal of RF and Microwave Computer-Aided Engineering, 18, 42-52. http://dx.doi.org/10.1002/mmce.20265
[5]	Formato, R.A. (2007) Central Force Optimization: A New Metaheuristic with Applications in Applied Electromagnetics. Progress in Electromagnetics Research, 77, 425-491. http://dx.doi.org/10.2528/PIER07082403
[6]	Mahmoud, K.R. (2011) Central Force Optimization: Nelder-Mead Hybrid Algorithm for Rectangular Microstrip Antenna Design. Electromagnetics, 31, 578-592. http://dx.doi.org/10.1080/02726343.2011.621110
[7]	Rashedi, E., Nezamabadi-Pour, H. and Saryazdi, S. (2009) GSA: A Gravitational Search Algorithm. Information Sciences, 179, 2232-2248. http://dx.doi.org/10.1016/j.ins.2009.03.004
[8]	Chatterjee, A., Mahanti, G.K. and Pathak, N.N. (2010) Comparative Performance of Gravitational Search Algorithm and Modified Particle Swarm Optimization Algorithm for Synthesis of Thinned Scanned Concentric Ring Array Antenna. Progress in Electromagnetics Research B, 25, 331-348. http://dx.doi.org/10.2528/PIERB10080405
[9]	Chatterjee, A., Mahanti, G.K. and Mahapatra, P.R.S. (2011) Design of Fully Digital Controlled Reconfigurable Dual-Beam Concentric Ring Array Antenna Using Gravitational Search Algorithm. Progress in Electromagnetics Research C, 18, 59-72. http://dx.doi.org/10.2528/PIERC10101806
[10]	Altinoz, O.T. and Yilmaz, A.E. (2011) Calculation of Optimized Parameters Of Rectangular Patch Antenna Using Gravitational Search Algorithm. 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA), Istanbul, 15-18 June 2011, 349-353. http://dx.doi.org/10.1109/INISTA.2011.5946090
[11]	Magdy, A., Mahmoud, K.R., Abdel-Gawad, S.G. and Ibrahim, I.I. (2013) Direction of Arrival Estimation Based on Maximum Likelihood Criteria Using Gravitational Search Algorithm. Progress in Electromagnetics Research Symposium Proceedings, Taipei, 25-28 March 2013, 1162-1167.
[12]	Mahmoud, K.R. (2013) UWB Antenna Using Gravitational Search Algorithm. Journal of Engineering Sciences, 41, 1890-1903.
[13]	Mahmoud, K.R. and Hamad, S. (2014) Parallel Implementation of Hybrid GSA-NM Algorithm for Adaptive Beam-Forming Applications. Progress in Electromagnetics Research B, 58, 47-57. http://dx.doi.org/10.2528/PIERB13102106
[14]	Ram, G., Mandal, D., Kar, R. and Ghoshal, S.P. (2013) Optimized Hyper Beamforming of Linear Antenna Arrays Using Collective Animal Behaviour. The Scientific World Journal, 2013, Article ID: 982017.
[15]	Mirjalili, S. and Hashim, S.Z.M. (2010) A New Hybrid PSOGSA Algorithm for Function Optimization. International Conference on Computer and Information Application (ICCIA), Tianjin, 3-5 December 2010, 374-377.
[16]	Talbi, E.G (2002) A Taxonomy of Hybrid Metaheuristic. Journal of Heuristics, 8, 541-546. http://dx.doi.org/10.1023/A:1016540724870