Performance Analysis of Existing Beam forming Methods for Various Antenna Elements and Interference Sources

Main Article Content

Yashoda B.S
Dr. K.R. Nataraj

Abstract

Antenna arrays make use of techniques like Maximal Ratio Combining or Diversity Combining to achieve a high Signal-to-Noise Ratio (SNR). The two major algorithms used are Direction of Arrival (DOA) and Beamforming. This paper studies and performs a performance analysis of existing beamforming algorithms, namely, Least Mean Square (LMS), Recursive Least Mean Square (RLS), Griffiths, and Variable Step Size Griffiths (VSSG). The algorithms are simulated for various cases, including Low RF Sources and Single Interference, Large RF Source and Single Interference, Low RF Sources and Multiple Interference angles, and finally, in the case of Large RF Sources and Multiple Interference angles.

Article Details

How to Cite
[1]
Yashoda B.S and Dr. K.R. Nataraj, “Performance Analysis of Existing Beam forming Methods for Various Antenna Elements and Interference Sources”, Int. J. Comput. Eng. Res. Trends, vol. 4, no. 4, pp. 142–149, Apr. 2017.
Section
Research Articles

References

El-Keyi, A., Kirubarajan, T., & Gershman, A. B. (2005). Robust adaptive beamforming based on the Kalman filter. IEEE Transactions on Signal Processing, 53(8), Aug.

Khalaf, A. A. M., El-Daly, A. B. M., & Hamed, H. F. A. (2016). Different adaptive beamforming algorithms for performance investigation of smart antenna system. In Software, Telecommunications and Computer Networks (SoftCOM), 2016 24th International Conference.

Patel, D. N., Makwana, B. J., & Parmar, P. B. (2016). Comparative analysis of adaptive beamforming algorithm LMS, SMI, and RLS for ULA smart antenna. In Communication and Signal Processing (ICCSP), 2016 International Conference on.

Griffiths, L. J. (n.d.). A simple adaptive algorithm for real-time processing of in antenna arrays. Proceedings of the IEEE, 57, 1696–1704.

Narasimhan, S. V., Veena, S., & Lokesha, H. (2010). Variable step-size Griffiths‟ algorithm for improved performance of feedforward/feedback active noise control. Signal, Image and Video Processing, 4(3), 309.

Kim, I.-S., Na, H.-S., Kim, K.-J., & Park, Y. (1994). Constraint filtered-X and filtered-U LMS algorithms for the active control of noise in ducts. Journal of the Acoustical Society of America, 95(6).

Kuo, S. M., & Morgan, D. R. (1996). Active noise control systems, algorithms, and DSP implementations. Wiley, New York.

Kuo, S. M., & Vijayan, D. (1997). A secondary path modeling technique for active noise control. IEEE Transactions on Speech and Audio Processing, 5(4).

Kwong, R. H., & Johnston, E. W. (1992). A variable step-size LMS algorithm. IEEE Transactions on Signal Processing, 40(7), 1633–1642.