Evaluating the effectiveness of adaptive antenna array in weight coefficients discretization

Authors

DOI:

https://doi.org/10.15587/2312-8372.2017.100307

Keywords:

discretization of quadrature components, weight coefficients, antenna array, loss rate

Abstract

Currently, there is a shortage of using radio resources in the world and there is an acute need for using additional physical resources that increase the bandwidth of communication channels and increase the productivity of mobile communication systems in general. The use of space-time physical parameters in the organization of multiple access (STA) of subscribers is becoming relevant.

The methods of subscriber stations (SSs) STA to the resources of the base station (BS) are based on the use of -element adaptive antenna arrays (AAA). The methods and algorithms of AAA synthesis are based on the evaluation of the complex vector of weight coefficients (VWC) included in the reception paths of each antenna element (AE) and controlled by various algorithms. Therefore, the object of research is the process of discretization of the weight coefficients in the adaptive antenna array.

The main disadvantage identified during the audit in this study is the calculation of the computational complexity of the quantization algorithm for weight coefficients for different variations in the parameters of the signal-interference situation at the AAA input.

Complex, systemic evaluation of the effectiveness of AAA functioning taking into account the chosen criterion of the effectiveness of the AAA operation, using the procedure for quantizing the weight coefficients, is possible with a broader and precise specification of the parameters of the operating signal-interference environment. This will allow to obtain reliable results.

The required dimensionality of the adaptive array antenna weights is determined depending on the ratio of the total interference power to the internal noise power at the input of the bandpass filter, based on the allowable decrease in the average output signal-to-interference-plus-noise ratio.

On the basis of the obtained analytical estimation of the loss rate, an expression for calculating the required quantizer capacity is proposed. It is possible to show that, regardless of the amount of allowable losses, the required quantizer capacity is increased by 1 bit with an increase in the input interference/noise ratio by 6 dB.

Author Biography

Mykola Moskalets, Kharkiv National University of Radio Electronics, 14, Nauky ave., Kharkiv, Ukraine, 61166

PhD, Associate Professor

Department of Infocommunication Systems

References

  1. Genefiko, T. A., Lishak, M. Yu. (2009). Sravnitel'nyi analiz tsifrovyh algoritmov adaptivnoi prostranstvennoi fil'tratsii. Radiotehnicheskie tetradi, 38, 33–37.
  2. Ratynskii, M. V. (2016). Vybor reguliarizatora v zadache adaptivnoi prostranstvennoi fil'tratsii. Uspehi sovremennoi radioelektroniki, 7, 53–63.
  3. Nitzberg, R. (1976). Effect of Errors in Adaptive Weights. IEEE Transactions on Aerospace and Electronic Systems, AES-12 (3), 369–373. doi:10.1109/taes.1976.308238
  4. Nitzberg, R. (1980). Computational Precision Requirements for Optimal Weights in Adaptive Processing. IEEE Transactions on Aerospace and Electronic Systems, AES-16 (4), 418–425. doi:10.1109/taes.1980.308969
  5. Ivandich, S. (1994). Quantisation error modelling of narrowband adaptive arrays using projected perturbation sequences. Proceedings of ICASSP ’94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2, 309–312. doi:10.1109/icassp.1994.389658
  6. Monzingo, R. A., Haupt, R. L., Miller, T. W. (2011). Introduction to Adaptive Arrays. Ed. 2. SciTech Publishing, 530. doi:10.1049/sbew046e
  7. Gabidulin, E. M., Liovshin, V. P., Pilipchuk, N. I. (1982). Ob effektivnosti adaptivnogo kompensatora meshaiushchih signalov. Trudy Radiotehnicheskogo instituta AN SSSR, 44, 236–249.
  8. Whittle, P. (2000). Probability. Probability via Expectation. New York: Springer, 39–50. doi:10.1007/978-1-4612-0509-8_3
  9. Hudson, J. E. (1977). The Effects of Signal and Weight Coefficient Quantisation in Adaptive Array Processors. Aspects of Signal Processing With Emphasis on Underwater Acoustics, Part 2, 423–428. doi:10.1007/978-94-011-3036-3_3
  10. Yu, S.-J., Lee, J.-H. (1994). Effect of random weight errors on the performance of partially adaptive array beamformers. Signal Processing, 37 (3), 365–380. doi:10.1016/0165-1684(94)90005-1

Published

2017-03-30

How to Cite

Moskalets, M. (2017). Evaluating the effectiveness of adaptive antenna array in weight coefficients discretization. Technology Audit and Production Reserves, 2(2(34), 12–18. https://doi.org/10.15587/2312-8372.2017.100307

Issue

Section

Information Technologies: Original Research