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A HGGSA Approach to Beam Forming for DOA Estimation in Smart Antenna Arrays

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Abstract

Beam forming is one of the most important processes in smart antenna systems for DOA estimation. The most important function in beam forming is changing beam pattern of antenna for a particular angle. If the antenna does not change the position for the specified angle, the signal losses will be high. For avoiding this, a hybrid method, called HGGSA (hybrid genetic and gravity search algorithm) is proposed that is developed by combining genetic algorithm and GSA to beam forming for DOA estimation in smart antenna arrays. In the proposed method, if an angle is given as input, it will give the maximum signal gain in the beam pattern of the antenna with corresponding position and phase angle after searching through the space based on the HGGSA algorithm.

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References

  1. Zhang, Z., Iskander, M. F., Yun, Z., et al. (2003). Hybrid smart antenna system using directional elements performance analysis in flat Rayleigh fading. International Journal of IEEE Transactions on Antennas and Propagation, 51(10), 1537–1540.

    Google Scholar 

  2. Jain, R. K., Katiyar, S., & Agrawal, N. K. (2011). Smart antenna for cellular mobile communication. VSRD International Journal of Electrical, Electronics & Communication Engineering, 1(9), 530–541.

    Google Scholar 

  3. Hussain, M. A., Varma, P. S., Rajesh, K. S., et al. (2010). Use of smart antennas in ad hoc networks. International Journal of Computer Science & Information Technology (IJCSIT), 2(6), 197–228.

    Google Scholar 

  4. Shaukat, S. F., Hassan, M., Farooq, R., et al. (2009). Sequential studies of beam forming algorithms for smart antenna systems. International Journal World Applied Sciences, 6(6), 754–758.

    Google Scholar 

  5. Radhakrishnan, K., Unnikrishnan, A., Balakrishnan, K. G., et al. (2010). Performance evaluation of an algorithm for estimation of DOA using model estimation technique. International Journal of Computer Applications, 1(1), 0975–8887.

    Google Scholar 

  6. Jan covic, P., Zou, X., Kokuer, M. (2010) Underdetermined DOA estimation via independent component analysis and time-frequency masking. International Journal of Electrical and Computer Engineering.

  7. Liu, Y., Wan, Q., & Chu, X. (2010). A robust beam former based on weighted sparse constraint. Progress in Electromagnetic Research Letters, 16, 53–60.

    Article  Google Scholar 

  8. Liu, W., Ding, S., Jin, M., et al. (2012). A robust DOA/beam forming algorithm using the constant modulus feature. International Journal of Innovative Computing, Information and Control, 8(3), 2137–2148.

    Google Scholar 

  9. Wan, L., Han, G., Rodrigues, J., Si, W., & Feng, N. (2014). An energy efficient DOA estimation algorithm for uncorrelated and coherent signals in virtual MIMO systems. Telecommunication Systems, 59(1), 93–110.

    Article  Google Scholar 

  10. Liu, W., Liu, Q., Jin, M., et al. (2011). An iterative algorithm for joint beam forming and DOA estimation. International Journal of Innovative Computing, Information and Control, 7(5), 3019–3032.

    Google Scholar 

  11. Abdulrahman, O., Rahman, M., Hassnawi, L., & Ahmad, R. (2015). Modifying MVDR beamformer for reducing direction-of-arrival estimation mismatch. Arabian Journal for Science and Engineering, 41(9), 3321–3334.

    Article  MathSciNet  MATH  Google Scholar 

  12. Hamza, S. A., & Amin, M. G. (2019). Hybrid sparse array beam forming design for general rank signal models. IEEE Transactions on Signal Processing, 67(24), 6215–6226.

    Article  MathSciNet  MATH  Google Scholar 

  13. Raja, M., et al. (2016). A new computing paradigm for the optimization of parameters in adaptive beam forming using fractional processing. The European Physical Journal Plus, 134(6), 1–13.

    Google Scholar 

  14. Yerriswamy, T., & Jagadeesha, S. N. (2011). Fault tolerant matrix pencil method for direction of arrival estimation. Signal & Image Processing: An International Journal (SIPIJ), 2(3), 55–67.

    Google Scholar 

  15. Mondal, D. K. (2013). Studies of different direction of arrival (DOA) estimation algorithm for smart antenna in wireless communication. International Journal of Electronics and Communication, 4(1), 43–44.

    Google Scholar 

  16. Yasin, M., Akhtar, P., Khan, M. J., et al. (2010). CMA an optimum beam former for a smart antenna system. International Journal of Computer Applications, 5(7), 0975–8887.

    Google Scholar 

  17. Sanudin, R., Noordin, N. H., & Arslan, T. (2012). DOA estimation using modified covariance matrix. International Conference on Antennas & Propagation, 2012, 1–4.

    Google Scholar 

  18. Li, P., Zhang, M., & Zhong, Z. (2011). Integrative wideband DOA estimation method based on sparse representation. Electronics Letters, 47(22), 1251–1252.

    Article  Google Scholar 

  19. Cao, S., Ye, Z., Xu, D., et al. (2013). A Hadamard product based method for DOA estimation and gain-phase error calibration. International Journal of IEEE Transactions on Aerospace and Electronic Systems, 49(2), 1224–1233.

    Article  Google Scholar 

  20. Liu, A., Liao, G., Zeng, C., et al. (2011). An eigen structure method for estimating DOA and sensor gain-phase errors. International Journal of IEEE Transactions on Signal Processing, 59(12), 5944–5956.

    Article  MATH  Google Scholar 

  21. Ali, R. L., Ali, A., Khan, S. A., et al. (2011). Adaptive beam forming algorithms for anti-jamming. International Journal of Signal Processing, Image Processing and Pattern Recognition, 4(1), 193–196.

    Google Scholar 

  22. Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009). GSA: a gravitational search algorithm. Information Sciences, 179, 2232–2248.

    Article  MATH  Google Scholar 

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Authors and Affiliations

  1. JNTUK, Kakinada, India

    S. Venkata Rama Rao

  2. Electronics and Communication Engineering, University College of Engineering, JNTUK, Kakinada, India

    A. Mallikarjuna Prasad

  3. Electronics and Communication Engineering, USHA RAMA College of Engineering and Technology, Telaprolu, India

    Ch. Santhi Rani

Authors
  1. S. Venkata Rama Rao
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  2. A. Mallikarjuna Prasad
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  3. Ch. Santhi Rani
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Correspondence to S. Venkata Rama Rao.

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Venkata Rama Rao, S., Mallikarjuna Prasad, A. & Santhi Rani, C. A HGGSA Approach to Beam Forming for DOA Estimation in Smart Antenna Arrays. Wireless Pers Commun 115, 2391–2413 (2020). https://doi.org/10.1007/s11277-020-07687-3

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  • DOI: https://doi.org/10.1007/s11277-020-07687-3

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