Search search
submit Submit
Publication Date
to
Vol. 127
Latest Volume
All Volumes
PIER 180 [2024] PIER 179 [2024] PIER 178 [2023] PIER 177 [2023] PIER 176 [2023] PIER 175 [2022] PIER 174 [2022] PIER 173 [2022] PIER 172 [2021] PIER 171 [2021] PIER 170 [2021] PIER 169 [2020] PIER 168 [2020] PIER 167 [2020] PIER 166 [2019] PIER 165 [2019] PIER 164 [2019] PIER 163 [2018] PIER 162 [2018] PIER 161 [2018] PIER 160 [2017] PIER 159 [2017] PIER 158 [2017] PIER 157 [2016] PIER 156 [2016] PIER 155 [2016] PIER 154 [2015] PIER 153 [2015] PIER 152 [2015] PIER 151 [2015] PIER 150 [2015] PIER 149 [2014] PIER 148 [2014] PIER 147 [2014] PIER 146 [2014] PIER 145 [2014] PIER 144 [2014] PIER 143 [2013] PIER 142 [2013] PIER 141 [2013] PIER 140 [2013] PIER 139 [2013] PIER 138 [2013] PIER 137 [2013] PIER 136 [2013] PIER 135 [2013] PIER 134 [2013] PIER 133 [2013] PIER 132 [2012] PIER 131 [2012] PIER 130 [2012] PIER 129 [2012] PIER 128 [2012] PIER 127 [2012] PIER 126 [2012] PIER 125 [2012] PIER 124 [2012] PIER 123 [2012] PIER 122 [2012] PIER 121 [2011] PIER 120 [2011] PIER 119 [2011] PIER 118 [2011] PIER 117 [2011] PIER 116 [2011] PIER 115 [2011] PIER 114 [2011] PIER 113 [2011] PIER 112 [2011] PIER 111 [2011] PIER 110 [2010] PIER 109 [2010] PIER 108 [2010] PIER 107 [2010] PIER 106 [2010] PIER 105 [2010] PIER 104 [2010] PIER 103 [2010] PIER 102 [2010] PIER 101 [2010] PIER 100 [2010] PIER 99 [2009] PIER 98 [2009] PIER 97 [2009] PIER 96 [2009] PIER 95 [2009] PIER 94 [2009] PIER 93 [2009] PIER 92 [2009] PIER 91 [2009] PIER 90 [2009] PIER 89 [2009] PIER 88 [2008] PIER 87 [2008] PIER 86 [2008] PIER 85 [2008] PIER 84 [2008] PIER 83 [2008] PIER 82 [2008] PIER 81 [2008] PIER 80 [2008] PIER 79 [2008] PIER 78 [2008] PIER 77 [2007] PIER 76 [2007] PIER 75 [2007] PIER 74 [2007] PIER 73 [2007] PIER 72 [2007] PIER 71 [2007] PIER 70 [2007] PIER 69 [2007] PIER 68 [2007] PIER 67 [2007] PIER 66 [2006] PIER 65 [2006] PIER 64 [2006] PIER 63 [2006] PIER 62 [2006] PIER 61 [2006] PIER 60 [2006] PIER 59 [2006] PIER 58 [2006] PIER 57 [2006] PIER 56 [2006] PIER 55 [2005] PIER 54 [2005] PIER 53 [2005] PIER 52 [2005] PIER 51 [2005] PIER 50 [2005] PIER 49 [2004] PIER 48 [2004] PIER 47 [2004] PIER 46 [2004] PIER 45 [2004] PIER 44 [2004] PIER 43 [2003] PIER 42 [2003] PIER 41 [2003] PIER 40 [2003] PIER 39 [2003] PIER 38 [2002] PIER 37 [2002] PIER 36 [2002] PIER 35 [2002] PIER 34 [2001] PIER 33 [2001] PIER 32 [2001] PIER 31 [2001] PIER 30 [2001] PIER 29 [2000] PIER 28 [2000] PIER 27 [2000] PIER 26 [2000] PIER 25 [2000] PIER 24 [1999] PIER 23 [1999] PIER 22 [1999] PIER 21 [1999] PIER 20 [1998] PIER 19 [1998] PIER 18 [1998] PIER 17 [1997] PIER 16 [1997] PIER 15 [1997] PIER 14 [1996] PIER 13 [1996] PIER 12 [1996] PIER 11 [1995] PIER 10 [1995] PIER 09 [1994] PIER 08 [1994] PIER 07 [1993] PIER 06 [1992] PIER 05 [1991] PIER 04 [1991] PIER 03 [1990] PIER 02 [1990] PIER 01 [1989]
All Journals
PIER PIER B PIER C PIER M PIER Letters
2012-04-11
Adaptive Beamforming with Low Side Lobe Level Using Neural Networks Trained by Mutated Boolean PSO
By
Zaharias D. Zaharis,

    Dr. Zaharias D. Zaharis

    Telecommunications Centre

    Aristotle University of Thessaloniki

    Greece

    Homepage

Konstantinos A. Gotsis,

    Dr. Konstantinos A. Gotsis

    Department of Physics

    Aristotle University of Thessaloniki

    Greece

    Homepage

John Sahalos

    Prof. John Sahalos

    Department of Physics

    Aristotle University of Thessaloniki

    Greece

    Homepage

Progress In Electromagnetics Research, Vol. 127, 139-154, 2012
doi:10.2528/PIER12022806
Abstract
A new adaptive beamforming technique based on neural networks (NNs) is proposed. The NN training is accomplished by applying a novel optimization method called Mutated Boolean PSO (MBPSO). In the beginning of the procedure, the MBPSO is repeatedly applied to a set of random cases to estimate the excitation weights of an antenna array that steer the main lobe towards a desired signal, place nulls towards several interference signals and achieve the lowest possible value of side lobe level. The estimated weights are used to train efficiently a NN. Finally, the NN is applied to a new set of random cases and the extracted radiation patterns are compared to respective patterns extracted by the MBPSO and a well-known robust adaptive beamforming technique called Minimum Variance Distortionless Response (MVDR). The aforementioned comparison has been performed considering uniform linear antenna arrays receiving several interference signals and a desired one in the presence of additive Gaussian noise. The comparative results show the advantages of the proposed technique.
Citation
Zaharias D. Zaharis, Konstantinos A. Gotsis, and John Sahalos, "Adaptive Beamforming with Low Side Lobe Level Using Neural Networks Trained by Mutated Boolean PSO," Progress In Electromagnetics Research, Vol. 127, 139-154, 2012.
doi:10.2528/PIER12022806
References

1. Gross, F. B., Smart Antennas for Wireless Communications with Matlab, McGraw-Hill, New York, 2005.

2. Viani, F., L. Lizzi, M. Donelli, D. Pregnolato, G. Oliveri, and A. Massa, "Exploitation of parasitic smart antennas in wireless sensor networks," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 7, 993-1003, 2010.
doi:10.1163/156939310791285227

3. Jabbar, A. N., "A novel ultra-fast ultra-simple adaptive blind beamforming algorithm for smart antenna arrays," Progress In Electromagnetics Research B, Vol. 35, 329-348, 2011.
doi:10.2528/PIERB11091504

4. Li, J. and P. Stoica, Robust Adaptive Beamforming, John Wiley & Sons, Inc., Hoboken, New Jersey, 2006.

5. Castaldi, G., V. Galdi, and G. Gerini, "Evaluation of a neural-network-based adaptive beamforming scheme with magnitude-only constraints," Progress In Electromagnetics Research B, Vol. 11, 1-14, 2009.
doi:10.2528/PIERB08092303

6. Umrani, A. W., Y. Guan, and F. A. Umrani, "Effect of steering error vector and angular power distributions on beamforming and transmit diversity systems in correlated fading channel," Progress In Electromagnetics Research, Vol. 105, 383-402, 2010.
doi:10.2528/PIER10042902

7. Byrne, D., M. O'Halloran, M. Glavin, and E. Jones, "Data independent radar beamforming algorithms for breast cancer detection," Progress In Electromagnetics Research, Vol. 107, 331-348, 2010.
doi:10.2528/PIER10061001

8. Byrne, D., M. O'Halloran, E. Jones, and M. Glavin, "Transmitter-grouping robust capon beamforming for breast cancer detection," Progress In Electromagnetics Research, Vol. 108, 401-416, 2010.
doi:10.2528/PIER10090205

9. Lee, J.-H., Y.-S. Jeong, S.-W. Cho, W.-Y. Yeo, and K. S. J. Pister, "Application of the newton method to improve the accuracy of TOA estimation with the beamforming algorithm and the music algorithm," Progress In Electromagnetics Research, Vol. 116, 475-515, 2011.

10. Zaharis, Z. D. and T. V. Yioultsis, "A novel adaptive beamforming technique applied on linear antenna arrays using adaptive mutated boolean PSO," Progress In Electromagnetics Research, Vol. 117, 165-179, 2011.

11. Mallipeddi, R., J. P. Lie, P. N. Suganthan, S. G. Razul, and C. M. S. See, "A differential evolution approach for robust adaptive beamforming based on joint estimation of look direction and array geometry," Progress In Electromagnetics Research, Vol. 119, 381-394, 2011.
doi:10.2528/PIER11052205

12. Mallipeddi, R., J. P. Lie, P. N. Suganthan, S. G. Razul, and C. M. S. See, "Near optimal robust adaptive beamforming approach based on evolutionary algorithm," Progress In Electromagnetics Research B, Vol. 29, 157-174, 2011.
doi:10.2528/PIERB10110810

13. Lee, J.-H., G.-W. Jung, and W.-C. Tsai, "Antenna array beamforming in the presence of spatial information uncertainties," Progress In Electromagnetics Research B, Vol. 31, 139-156, 2011.

14. Lee, J.-H., "Robust antenna array beamforming under cycle frequency mismatch ," Progress In Electromagnetics Research B, Vol. 35, 307-328, 2011.
doi:10.2528/PIERB11082207

15. Liu, Y., Q. Wan, and X. Chu, "A robust beamformer based on weighted sparse constraint," Progress In Electromagnetics Research Letters, Vol. 16, 53-60, 2010.
doi:10.2528/PIERL10062308

16. Liu, Y. and Q. Wan, "Total difference based partial sparse LCMV beamformer," Progress In Electromagnetics Research Letters, Vol. 18, 97-103, 2010.
doi:10.2528/PIERL10092705

17. Mallipeddi, R., J. P. Lie, S. G. Razul, P. N. Suganthan, and C. M. S. See, "Robust adaptive beamforming based on covariance matrix reconstruction for look direction mismatch," Progress In Electromagnetics Research Letters, Vol. 25, 37-46, 2011.

18. Christodoulou, C. and M. Georgiopoulos, Applications of Neural Networks in Electromagnetics, Artech House, Boston-London, 2001.

19. Gotsis, K. A., K. Siakavara, and J. N. Sahalos, "On the direction of arrival (DoA) estimation for a switched-beam antenna system using neural networks," IEEE Transactions on Antennas and Propagation, Vol. 57, No. 5, 1399-1411, May 2009.
doi:10.1109/TAP.2009.2016721

20. Bregains, J. C., J. Dorado, M. Gestal, J. A. Rodriguez, F. Ares, and A. Pazos, "Avoiding interference in planar arrays through the use of artificial neural networks," IEEE Antennas and Propagation Magazine, Vol. 44, No. 6, 61-65, August 2002.
doi:10.1109/MAP.2002.1043149

21. Luo, M. and K.-M. Huang, "Prediction of the electromagnetic field in metallic enclosures using artificial neural networks," Progress In Electromagnetics Research, Vol. 116, 171-184, 2011.

22. Kim, Y. and H. Ling, "Direction of arrival estimation of humans with a small sensor array using an artificial neural network," Progress In Electromagnetics Research B, Vol. 27, 127-149, 2011.

23. Vakula, D. and N. V. S. N. Sarma, "Using neural networks for fault detection in planar antenna arrays," Progress In Electromagnetics Research Letters, Vol. 14, 21-30, 2010.
doi:10.2528/PIERL10030401

24. Peng, H., Z. Yang, and T. Yang, "Calibration of a six-port receiver for direction ¯nding using the artificial neural network technique," Progress In Electromagnetics Research Letters, Vol. 27, 17-24, 2011.
doi:10.2528/PIERL11081504

25. Sacha, G. M., F. B. Rodr¶³guez, E. Serrano, and P. Varona, "Generalized image charge method to calculate electrostatic magnitudes at the nanoscale powered by artificial neural networks ," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 8-9, 1145-1155, 2010.
doi:10.1163/156939310791586160

26. Guo, L. and L. Parsa, "Geometry optimization of IPM machines using orthogonal experimental design method and artificial neural network ," Journal of Electromagnetic Waves and Applications, Vol. 25, No. 7, 901-912, 2011.
doi:10.1163/156939311795254028

27. Carro Ceballos, P. L., J. De Mingo Sanz, and P. G. Dúcar, "Radiation pattern synthesis for maximum mean effective gain with spherical wave expansions and particle swarm techniques ," Progress In Electromagnetics Research, Vol. 103, 355-370, 2010.
doi:10.2528/PIER10031808

28. Zhang, Y., S. Wang, and L. Wu, "A novel method for magnetic resonance brain image classification based on adaptive chaotic PSO ," Progress In Electromagnetics Research, Vol. 109, 325-343, 2010.
doi:10.2528/PIER10090105

29. Wang, W.-B., Q. Feng, and D. Liu, "Application of chaotic particle swarm optimization algorithm to pattern synthesis of antenna arrays," Progress In Electromagnetics Research, Vol. 115, 173-189, 2011.

30. Li, W.-T., Y.-Q. Hei, and X.-W. Shi, "Pattern synthesis of conformal arrays by a modified particle swarm optimization," Progress In Electromagnetics Research, Vol. 117, 237-252, 2011.

31. Liu, D., Q. Feng, W.-B.Wang, and X. Yu, "Synthesis of unequally spaced antenna arrays by using inheritance learning particle swarm optimization," Progress In Electromagnetics Research, Vol. 118, 205-221, 2011.
doi:10.2528/PIER11050502

32. Wang, D., H. Zhang, T. Xu, H. Wang, and G. Zhang, "Design and optimization of equal split broadband microstrip Wilkinson power divider using enhanced particle swarm optimization algorithm," Progress In Electromagnetics Research, Vol. 118, 321-334, 2011.
doi:10.2528/PIER11052303

33. Lin, D.-B., F.-N. Wu, W. S. Liu, C. K. Wang, and H.-Y. Shih, "Crosstalk and discontinuities reduction on multi-module memory bus by particle swarm optimization," Progress In Electromagnetics Research, Vol. 121, 53-74, 2011.
doi:10.2528/PIER11080302

34. Kennedy, J. and R. C. Eberhart, "A discrete binary version of the particle swarm algorithm," Proc. World Multiconference on Systemics, Cybernetics and Informatics, 4104-4109, 1997.

35. Afshinmanesh, F., A. Marandi, and M. Shahabadi, "Design of a single-feed dual-band dual-polarized printed microstrip antenna using a Boolean particle swarm optimization ," IEEE Transactions on Antennas and Propagation, Vol. 56, No. 7, 1845-1852, July 2008.
doi:10.1109/TAP.2008.924684

36. Yang, P., F. Yang, and Z.-P. Nie, "DOA estimation with sub-array divided technique and interporlated esprit algorithm on a cylindrical conformal array antenna," Progress In Electromagnetics Research, Vol. 103, 201-216, 2010.
doi:10.2528/PIER10011904

37. Park, G. M., H. G. Lee, and S. Y. Hong, "Doa resolution enhancement of coherent signals via spatial averaging of virtually expanded arrays ," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 1, 61-70, 2010.
doi:10.1163/156939310790322127

38. Lui, H. S. and H. T. Hui, "Effective mutual coupling compensation for direction-of-arrival estimations using a new, accurate determination method for the receiving mutual impedance," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 2-3, 271-281, 2010.
doi:10.1163/156939310790735598

39. Liang, J. and D. Liu, "Two L-shaped array-based 2-D DOAs estimation in the presence of mutual coupling," Progress In Electromagnetics Research, Vol. 112, 273-298, 2011.

40. Bencheikh, M. L. and Y. Wang, "Combined esprit-rootmusic for DOA-dod estimation in polarimetric bistatic MIMO radar," Progress In Electromagnetics Research Letters, Vol. 22, 109-117, 2011.

41. Neural Network ToolboxTM User's Guide R2010a, MATLAB, The MathWorks, Inc..

Download Full Article (313) View Full Article volume
The EM Academy piers.org jpier.org Who's Who in EM
Copyright © 2022 The Electromagnetics Academy. All Rights Reserved.