http://iet.metastore.ingenta.com
1887

DOA/MoM-based ABF algorithm for SINR enhancement

DOA/MoM-based ABF algorithm for SINR enhancement

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, a new non-iterative adaptive beamforming (ABF) algorithm for the signal-to-interference and noise ratio (SINR) enhancement is proposed. It is based on a combination between the direction of arrival (DOA) estimation and the method of moments (MoM). The proposed algorithm is denoted as DM/ABF which stands for DOA and MoM-based ABF. The DOA is used to provide accurate estimates for the directions of the desired and interfering signals. On the basis of the estimated DOAs, a dedicated shaped pattern version of the ordinary pattern is created and applied as the desired input to the MoM algorithm. The MoM is used for shaped pattern synthesis to estimate the weights vector required to provide deep nulls toward the interfering signals and directs the main beam toward the desired signal. In this case, the weights vector does not update iteratively at each received signal sample as in case of least mean square (LMS) and recursive least squares (RLSs) algorithms, but it is updated only when the estimated DOAs of the desired and interfering signals are changed. Furthermore, a large number of close nulls can be produced without the need for additional antenna elements compared with other algorithms.

References

    1. 1)
      • 1. Rajni, , Akash, T.: ‘Step size optimization of LMS algorithm using particle swarm optimization algorithm in system identification’, IJCSNS Int. J. Comput. Sci. Netw. Secur., 2013, 13, (6), pp. 125130.
    2. 2)
      • 2. Ana, J., Luka, L., Vesna, R.: ‘Adaptive array beamforming using a chaotic beamforming algorithm’, Hindawi Int. J. Antennas Propag., 2016, 2016, pp. 18.
    3. 3)
      • 3. Guruprasad, H.M., Kulkarni, S.B., Ramesh, K.: ‘Reduced complexity beamforming algorithm’. IEEE Int. Conf. Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT), Mysuru, India, 2016, pp. 115118.
    4. 4)
      • 4. Linzheng, Q., Yunlong, C., Minjian, Z.: ‘Low-complexity variable forgetting factor mechanisms for adaptive linearly constrained minimum variance beamforming algorithms’, IET Inst. Eng. Technol. Signal Process., 2015, 9, (2), pp. 154165.
    5. 5)
      • 5. Boya, Q., Yunlong, C., Benoit, C., et al: ‘Low-Complexity Variable forgetting factor constant modulus RLS-based algorithm for blind adaptive beamforming’. IEEE Asilomar Conf. Signals, Systems and Computers, Pacific Grove, CA, USA, 2013, pp. 171175.
    6. 6)
      • 6. Wei, S., Ting-Hui, Y., Fan-Qiu, M., et al: ‘A novel unitary beam space recursive least squares algorithm for fast adaptive beamforming’. IEEE Int. Congress on Image and Signal Processing (CISP), Hangzhou, China, 2013, pp. 12361240.
    7. 7)
      • 7. Mohammed, J.R.: ‘Controlling the element excitations of the smart antenna arrays using genetic algorithms’, Signal Image Process. Int. J. (SIPAIJ), 2016, 1, (1), pp. 16.
    8. 8)
      • 8. Smita, B., Ved, V.D.: ‘Performance analysis of adaptive beamforming using particle swarm optimization’. Int. Conf. Industrial and Information Systems (ICIIS), Roorkee, India, 2016, pp. 242246.
    9. 9)
      • 9. Majid, K., Gameel, S.: ‘Beamforming and power control for interference reduction in wireless communications using particle swarm optimization’, Int. J. Electron. Commun., 2010, 64, (6), pp. 489502.
    10. 10)
      • 10. Mohammed, J.R.: ‘Optimal null steering method in uniformly excited equally spaced linear arrays by optimising two edge elements’, IET Electron. Lett., 2017, 53, (13), pp. 835837.
    11. 11)
      • 11. Prajindra, S.K., Tiong, S.K., Johnny, K.S.P.: ‘Optimization of array pattern for efficient control of adaptive nulling and side lobe level’. IEEE Int. Conf. Communication, Networks and Satellite (COMNETSAT), Bandung, Indonesia, 2015, pp. 1621.
    12. 12)
      • 12. Santosh, K.M., Arvind, C., Sushmita, S., et al: ‘Synthesizing broad null in linear array by amplitude-only control using wind driven optimization technique’. IEEE (SAI) Intelligent Systems Conf., London, UK, 2015, pp. 6871.
    13. 13)
      • 13. Santosh, K.M., Arvind, C.: ‘A novel hybrid IWO/WDO algorithm for nulling pattern synthesis of uniformly spaced linear and non-uniform circular array antenna’, Int. J. Electron. Commun., 2016, 70, (6), pp. 750756.
    14. 14)
      • 14. Lakshman, P., Debalina, G.: ‘Linear antenna array synthesis using cat swarm optimization’, Int. J. Electron. Commun., 2014, 68, (6), pp. 540549.
    15. 15)
      • 15. Jalal, A.S., Kah-Seng, C., Ali, M.: ‘Adaptive array beamforming using a combined LMS–LMS algorithm’, IEEE Trans. Antennas Propag., 2010, 58, (11), pp. 35453557.
    16. 16)
      • 16. Aounallah, N., Bouziani, M., Taleb, A.A.: ‘A combined DMI–RLS algorithm in adaptive processing antenna system’, Arab. J. Sci. Eng., 2014, 39, (10), pp. 71097116.
    17. 17)
      • 17. Ashraf, A.M.K., Abdel-Rahman, B.M.E., Hesham, F.A.H.: ‘A hybrid NLMS/RLS algorithm to enhance the beamforming process of smart antenna systems’, J. Telecommun. Electron. Comput. Eng. (JTEC), 2018, 10, (1–4), pp. 1522.
    18. 18)
      • 18. Zhizhang, C., Gopal, G., Yiqiang, Y.: ‘Introduction to direction-of-arrival estimation’, 2010.
    19. 19)
      • 19. Ercument, A., Levent, S.: ‘A tutorial on the method of moments’, IEEE Antennas Propag. Mag., 2012, 54, (3), pp. 260275.
    20. 20)
      • 20. Basma, E., Amr, H.H., Salah, K.: ‘A new high-resolution and stable MV-SVD algorithm for coherent signals detection’, Prog. Electromagn. Res. M, 2014, 35, pp. 163171.
    21. 21)
      • 21. Jørgen, G.: ‘Beamforming algorithms – beamformers’ (Norsonic AS, Oslo, Norway, 2010), pp. 15.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2018.5246
Loading

Related content

content/journals/10.1049/iet-com.2018.5246
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address