IJCNS  Vol.4 No.5 , May 2011
A New On-Line/Off-Line Adaptive Antenna Array Beamformer for Tracking the Mobile Targets
Abstract: An adaptive antenna array system adjusts the main lobe of radiation pattern in the direction of desired signal and points the nulls in the direction of undesired signals or interferers. The essential goal of beamforming is to reduce the complexity of weighting process and to decrease the time needed for adjusting the antenna radiation pattern. In this article a new adaptive weighting algorithm is proposed for both least mean squares (LMS) and constant modulus (CM) algorithms. It is appropriate and applicable for antenna array systems with moving targets and also mobile applications as well as sensor networks. By predicting the relative velocity of source, the next location of the source will be estimated and the array weights will be determined using LMS or CM algorithm before arriving to the new point. For the next time associated to the new sampling point, evaluated weights will be used. Furthermore, by updating these weights between two consecutive times the effects of error propagation will be eliminated. Therefore, in addition to reduction in computational complexity at the time of weight allocation, relatively accurate weight allocation can be obtained. Simulation results of this investigation show that the angular error related to both LMS-based and CM-based algorithms is less than the conventional LMS and CM algorithms at different signal to noise ratios (SNRs). On the other hand, due to considering off-line process, online computational complexity of new algorithms is slightly low with respect to previous ones.
Cite this paper: nullS. Moghaddam and M. Moghaddam, "A New On-Line/Off-Line Adaptive Antenna Array Beamformer for Tracking the Mobile Targets," International Journal of Communications, Network and System Sciences, Vol. 4 No. 5, 2011, pp. 304-312. doi: 10.4236/ijcns.2011.45035.

[1]   S. Shirvani-Moghaddam and M. Shirvani-Moghaddam, “A Comprehensive Survey on Antenna Array Signal Processing,” Journal of Trends in Applied Science Research, Vol. 6, No. 6, 2011, pp. 507-536. doi:10.3923/tasr.2011.507.536

[2]   C. A. Balanis and P. I. Ioannides, “Introduction to Smart Antennas,” Morgan & Claypool, San Rafael, 2007.

[3]   T. K. Sarkar, M. C. Wicks, M. Salazar-Palma and R. J. Bonneau, “Smart Antennas,” John Wiley and Sons, Hoboken, 2003.

[4]   C. Sun, J. Cheng and T. Ohira, “Handbook on Advancements in Smart Antenna Technologies for Wireless Networks,” Idea Group Inc., Hershey, 2009.

[5]   J. Fuhl and E. Bonek, “Temporal Reference Algorithms versus Spatial Reference Algorithms for Smart Antennas,” Wireless Personal Communications, Vol. 9, No. 3, 1998, pp. 271-293. doi:10.1023/A:1018332029467

[6]   S. Haykin, “Adaptive Filter Theory,” Prentice Hall, Upper Saddle River, 1996.

[7]   A. Bouacha, F. Debbat and F. T. Bendimerad, “Modified Blind Beamforming Algorithm for Smart Antenna System,” Journal of Radio Electronics, No. 1, 2008.

[8]   P. C. Parini, D. X. Chen, D. J. Bigham, P. I. Liewellyn, D. L. Samuel, D. L. Ho and B. Collins, “Final Report on Semi-Smart Antenna Technology Project,” 2nd Edition, BSC Associates Ltd., Semi-Smart Antenna Project, Ofcom Project No. 830000081, July 2006.

[9]   J. Homer, P. J. Kootsookos and V. Selvaraju, “Enhanced NLMS Adaptive Array via DOA Detection,” IET Communications Magazine, Vol. 1, No. 1, 2007, pp. 19-26.

[10]   X. Sun, X. Lian and J. Zhou, “Robust Adaptive Beamforming Based on Maximum Likelihood Estimation,” International Conference on Microwave and Millimeter Wave Technology, Nanjing, 21-24 April 2008, pp. 1137- 1140.

[11]   H. Chen, D. Kasilingam, “Performance Analysis of Super-Resolution Bamforming in Smart Antennas,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, 17-21 May 2004, pp. 353-356. doi:10.1109/ICASSP.2004.1327120

[12]   R. M. Shubair, M. A. Al-Qutayri and J. M. Sa, “A Setup for the Evaluation of MUSIC and LMS Algorithms for a Smart Antenna System,” Journal of Communications, Vol. 2, No. 4, June 2007, pp. 71-77.

[13]   C. S. Rani, P. V. Subbaiah, K. C. Reddy and S. S. Rani, “LMS and RLS Algorithms for Smart Antennas in a W-CDMA Mobile Communication Environment,” ARPN Journal of Engineering and Applied Sciences, Vol. 4, No. 6, August 2009, pp. 77-88.

[14]   M. Islam and Z. Rashid, “MI-NLMS Adaptive Beamforming Algorithm for Smart Antenna System Applications,” Journal of Zhejiang University Science A, Vol. 7, No. 10, 2006, pp. 1709-1716. doi:10.1631/jzus.2006.A1709

[15]   M. T. Islam and N. Misran, “MI-NLMS Adaptive Beamforming Algorithm with Tracking Ability,” Journal of Applied Sciences, Vol. 9, No. 12, 2009, pp. 2335-2339. doi:10.3923/jas.2009.2335.2339

[16]   S. F. Shaukat, M. Hassan, R. Farooq, H. U. Saeed and Z. Saleem, “Sequential Studies of Beamforming Algorithms for Smart Antenna Systems,” World Applied Sciences Journal, Vol. 6, No. 6, 2009, pp. 754-758. doi:10.1109/ISWCS.2007.4392422

[17]   X. Wang and G. Z. Feng, “Performance Analysis of RLS Linearly Constrained Constant Modulus Algorithm for Multiuser Detection,” Elsevier Signal Processing, Vol. 89, No. 2, 2009, pp. 181-186.

[18]   L. Wang, R. C. de Lamare and Y. L. Cai, “Low-Com- plexity Adaptive Step Size Constrained Constant Modulus SG Algorithms for Adaptive Beamforming,” Elsevier Signal Processing, Vol. 89, No. 12, 2009, pp. 2503- 2513.

[19]   L. Wang and R. C. Lamare, “Constrained Constant Modulus RLS-based Blind Adaptive Beamforming Algorithm for Smart Antennas,” 4th International Symposium on Wireless Communication Systems, Trondheim, 17-19 October 2007, pp. 657-661.

[20]   H. Sadeghi, S. Shirvani-Moghaddam and V. T. Vakili, “Appropriate CCM-Based Algorithm for Adaptive Antenna Array Beamforming,” Proceedings of 5th International Symposium on Telecommunications, Tehran, 4-6 December 2010, pp. 69-75.