volume | PIER Journals

Abstract

Random antenna array (RAA) that uses the conventional beamforming method produces a poor beam pattern with high sidelobe level. This greatly reduces the performance and the efficiency of the antenna. The use of Genetic Algorithm (GA) to find the best positions for the antenna elements in RAA to lower the sidelobes has been widely researched. However, there has been no solution proposed for the reduction of sidelobes when the user has no autonomy over the position of the radiating elements, for instance in cases such as emergency communications. This paper proposes a novel Pareto Elite Selection Genetic Algorithm (PESGA) optimization method to reduce the sidelobes in an RAA that has fixed elements' position. The proposed method uses a single fitness function (peak sidelobe level) for parent selection while an additional function (number of sidelobes above a threshold level) is introduced to select the elitist in every generation via Pareto Front (PF) selection. Results indicate that the proposed PESGA method is best used for scenarios where the array size is small. In such cases, the proposed method provides much reduced sidelobe compared to the conventional RAA beamforming method and up to 200% improvements in terms of mainlobe to peak sidelobe ratio compared to GA weight optimized beamforming method.

1. John, L. and K. L. Titus, Digital Beamforming in Wireless Communications, Artech House, Inc., 1996.

2. Dahrouj, H. and Y. Wei, "Coordinated beamforming for the multicell multi-antenna wireless system," IEEE Transactions on Wireless Communications, Vol. 9, 1748-1759, 2010.
doi:10.1109/TWC.2010.05.090936 Google Scholar

3. Muhammad, N., et al. "Beam forming networks using reduced size butler matrix," Wireless Personal Communications, 1-20, 2010. Google Scholar

4. Li, Q., et al. "MIMO techniques in WiMAX and LTE: A feature overview," IEEE Communications Magazine, Vol. 48, 86-92, 2010.
doi:10.1109/MCOM.2010.5458368 Google Scholar

5. Shilo, S., A. J. Weiss, and A. Averbuch, "Performance of optimal beamforming with partial channel knowledge," IEEE Transactions on Wireless Communications, Vol. 10, 4035-4040, 2011.
doi:10.1109/TWC.2011.101211.110124 Google Scholar

6. Huang, Y., "WiMAX dynamnic beamforming antenna," IEEE Aerospace and Electronic Systems Magazine, Vol. 23, 26-31, 2008.
doi:10.1109/MAES.2008.4607896 Google Scholar

7. Constantine, A. B., Antenna Theory: Analysis and Design, Wiley-Interscience, 2005.

8. Huang, J. Y., P. Wang, and Q. Wan, "Collaborative beamforming for wireless sensor networks with arbitrary distributed sensors," IEEE Communications Letters, Vol. 16, 1118-1120, 2012.
doi:10.1109/LCOMM.2012.050912.120370 Google Scholar

9. D'Urso, M., M. G. Labate, A. Buonanno, and P. Vinetti, "Effective beam forming networks for large arbitrary array of antennas," IEEE Transactions on Antennas and Propagation, Vol. 60, 5129-5135, 2012.
doi:10.1109/TAP.2012.2208091 Google Scholar

10. Gerstoft, P. and W. S. Hodgkiss, "Improving beampatterns of two-dimensional random arrays using convex optimization," Journal of the Acoustical Society of America, Vol. 129, EL135-EL140, 2011.
doi:10.1121/1.3556896 Google Scholar

11. Young, W. F., E. F. Kuester, and C. L. Holloway, "Measurements of randomly placed wireless transmitters used as an array for receivers located within the array volume with application to emergency responders," IEEE Transactions on Antennas and Propagation, Vol. 57, 241-247, 2009.
doi:10.1109/TAP.2008.2009651 Google Scholar

12. Fuchs, B. and J. J. Fuchs, "Optimal narrow beam low sidelobe synthesis for arbitrary arrays," IEEE Transactions on Antennas and Propagation, Vol. 58, 2130-2135, 2010.
doi:10.1109/TAP.2010.2046863 Google Scholar

13. Krishnamurthy, S., D. W. Bliss, and V. Tarokh, "Sidelobe level distribution computation for antenna arrays with arbitrary element distributions," 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2045-2050, 2011.

14. Li, W. T., X. W. Shi, L. Xu, and Y. Q. Hei, "Improved GA and PSO culled hybrid algorithm for antenna array pattern synthesis," Progress In Electromagnetics Research, Vol. 80, 461-476, 2008.
doi:10.2528/PIER07121503 Google Scholar

15. Li, R., L. Xu, X. W. Shi, N. Zhang, and Z. Q. Lv, "Improved differential evolution strategy for antenna array pattern synthesis problems," Progress In Electromagnetics Research, Vol. 113, 429-441, 2011. Google Scholar

16. Lu, B., S. X. Gong, S. A. Zhang, Y. Guan, and J. Ling, "Optimum spatial arrangement of array elements for suppression of grating-lobes of radar cross section," IEEE Antennas and Wireless Propagation Letters, Vol. 9, 114-117, 2010.
doi:10.1109/LAWP.2010.2087003 Google Scholar

17. Steinberg, B., "The peak sidelobe of the phased array having randomly located elements," IEEE Transactions on Antennas and Propagation, Vol. 20, 129-136, 1972.
doi:10.1109/TAP.1972.1140162 Google Scholar

18. Zaharis, Z. D., K. A. Gotsis, and J. N. 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 Google Scholar

19. Zaharis, Z. D., C. Skeberis, and T. D. Xenos, "Improved antenna array adaptive beamforming with low side lobe level using a novel adaptive invasive weed optimization method ," Progress In Electromagnetics Research, Vol. 124, 137-150, 2012.
doi:10.2528/PIER11120202 Google Scholar

20. Son, S. H. and U. H. Park, "Sidelobe reduction of low-profile array antenna using a genetic algorithm," ETRI Journal, Vol. 29, 95-98, 2007.
doi:10.4218/etrij.07.0206.0128 Google Scholar

21. Lin, Z. Q., M. L. Yao, and X. W. Shen, "Sidelobe reduction of the low profile multi-subarray antenna by genetic algorithm," AEU --- International Journal of Electronics and Communications, Vol. 66, 133-139, 2012.
doi:10.1016/j.aeue.2011.06.006 Google Scholar

22. Rocca, P., R. L. Haupt, and A. Massa, "Sidelobe reduction through element phase control in uniform subarrayed array antennas," IEEE Antennas and Wireless Propagation Letters, Vol. 8, 437-440, 2009.
doi:10.1109/LAWP.2009.2015899 Google Scholar

23. Li, X., W.-T. Li, X.-W. Shi, J. Yang, and J.-F. Yu, "Modified differential evolution algorithm for pattern synthesis of antenna arrays," Progress In Electromagnetics Research, Vol. 137, 371-388, 2013. Google Scholar

24. Bevelacqua, P. J. and C. A. Balanis, "Optimizing antenna array geometry for interference suppression," IEEE Transactions on Antennas and Propagation, Vol. 55, 637-641, 2007.
doi:10.1109/TAP.2007.891509 Google Scholar

25. Ahmed, M. F. A. and S. A. Vorobyov, "Sidelobe control in collaborative beamforming via node selection," IEEE Transactions on Signal Processing, Vol. 58, 6168-6180, 2010.
doi:10.1109/TSP.2010.2077631 Google Scholar

26. Liu, D., Q. Feng, and W.-B. Wang, "Discrete optimization problems of linear array synthesis by using real number particle swarm optimization," Progress In Electromagnetics Research, Vol. 133, 407-424, 2013. Google Scholar

27. Li, R., L. Xu, X.-W. Shi, N. Zhang, and Z.-Q. Lv, "Improved differential evolution strategy for antenna array pattern synthesis problems," Progress In Electromagnetics Research, Vol. 113, 429-441, 2011. Google Scholar

28. Mandal, A., H. Zafar, S. Das, and A. V. Vasilakos, "Efficient circular array synthesis with a memetic differential evolution algorithm," Progress In Electromagnetics Research B, Vol. 38, 367-385, 2012. Google Scholar

29. 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 Google Scholar

30. 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 Google Scholar

31. Mallipeddi, R., J. P. Lie, P. N. Suganthan, S. G. Razul, 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. Google Scholar

32. Zitzler, E. and L. Thiele, "Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach," IEEE Trans. Evol. Comput., 257-271, 1999.
doi:10.1109/4235.797969 Google Scholar

33. Haupt, R. L. and S. E. Haupt, Practical Genetic Algorithms, 2nd Ed., John Wiley & Sons Inc., Hoboken, New Jersey, 2004.

34. Goudos, S. K., K. Siakavara, E. Vafiadis, and J. N. Sahalos, "Pareto optimal Yagi-Uda antenna design using multi-objective differential evolution," Progress In Electromagnetics Research, Vol. 105, 231-251, 2010.
doi:10.2528/PIER10052302 Google Scholar

35. Ochiai, H., P. Mitran, H. V. Poor, and V. Tarokh, "Collaborative beamforming for distributed wireless ad HOC sensor networks," IEEE Transactions on Signal Processing, Vol. 53, 4110-4124, 2005.
doi:10.1109/TSP.2005.857028 Google Scholar

36. Dikmese, S., A. Kavak, K. Kucuk, S. Sahin, and A. Tangel, "FPGA based implementation and comparison of beamformers for CDMA2000," Wirel. Pers. Commun., Vol. 57, 233-253, 2011.
doi:10.1007/s11277-009-9855-4 Google Scholar

37. 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. Google Scholar

Ms. Suhanya Jayaprakasam

Dr. Sharul Kamal Bin Abd Rahim

Dr. Chee Yen Leow