Abstract
This paper presents a tool for the analysis, and simulation of direction-of-arrival estimation in wireless mobile communication systems over the Rayleigh fading channel. It reviews three subspace based methods of Direction of arrival estimation algorithms. The standard Multiple Signal Classification (MUSIC) can be obtained from the subspace based methods. In improved MUSIC procedure called Cyclic MUSIC, it can automatically classify the signals as desired and undesired based on the known spectral correlation property and estimate only the desired signal’s DOA. The next method is an extension of the Cyclic MUSIC algorithm called Extended Cyclic MUSIC by using an extended array data vector. By exploiting cyclostationarity, the signal’s DOA estimation can be significantly improved. In this paper, the DOA estimation algorithm using the de-noising pre-processing based on time-frequency conversion analysis is proposed, and the performances are analyzed. This is focused on the improvement of DOA estimation at a lower SNR and interference environment. This paper provides a fairly complete image of the performance and statistical efficiency of each of above three methods with QPSK signal model for coherent system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lee Swindlehurst, A., member, IEEE, Stoica, P., Fellow, IEEE: Maximum likelihood methods in radar signal processing (February 1998)
Krim, A., Viberg, M.: Two decades of array signal processing Research. IEEE Signal Processing Magazine (July 1996)
McCloud, M.L., Varanasi, K.: Beamforming, Diversity,and Interference Rejection for Multiuser communication over fading channels with a receive antenna array. IEEE Trans. on Comm. 51 (January 2003)
Kumaresan, R., Tufts, D.W.: Estimating the angles arrival of multiple plane waves. IEEE Trans. Aerosp. Electron. Syst. AES-19 (January 1983)
Sharman, K.C., Durrani, T.S.: Maximum Likelihood parameter estimation by simulated anneling. In: Proc. IEEE Int. Conf. Acoust. Speech Processing (April 1988)
Miller, M., Fuhrmann, D.: Maximum Likelihood Direction of Arrival Estimation for multiple narrow band signals in noise. In: Proc. 1987 Conf. Inform. Sciences, Syst., pp. 710–712 (March 1987)
Schell, S.V., member, IEEE: Performance analysis of the Cyclic MUSIC method of Direction Estimation for Cyclostationary Signals. Trans. (November 1994)
Stoica, P., Sharman, K.C.: A novel eigenanalysis method for direction estimation. In: Proc. Inst. Elec. Eng., pt. (February 1990)
Schmidt, R.O.: Multiple emitter location and signal (August 2000)
Pesavento, M., Gershman, A.B., Wong, K.M.: Direction of arrival estimation in partly calibrated time-varying sensor arrays. In: Proc ICASSP, Salt Lake City, UT, pp. 3005–3008 (May 2001)
Pesavento, M., Gershman, A.B., Wong, K.M.: Direction finding in partly-calibrated sensor arrays composed of multiple subarrays. IEEE Trans. Signal Processing 50, 2103–2115 (2002)
See, C.M.S., Gershman, A.B.: Subspace-based direction finding in partly calibrated arrays of arbitrary geometry. In: Proc. ICASSP, pp. 3013–3016 (April 2002)
Pesavento, M., Gershman, A.B., Wong, K.M.: On uniqueness of direction of arrival estimates using rank reduction estimator (RARE). In: Proc. ICASSP, Orlando, FL, pp. 3021–3024 (April 2002)
Pesavento, M., Gershman, A.B., Wong, K.M., Böhme, J.F.: Direction finding in partly calibrated arrays composed of nonidentical subarrays: A computationally efficient algorithm for the RARE estimator. In: Proc. IEEE Statist. Signal Process. Workshop, Singapore
Boubaker, N., Letief, K.B., Much, R.D.: Performance of BLAST over frequency-selective wireless Communication channels. IEEE Trans. on Communications 50(2), 196–199 (2002)
Choi, J.: Beamforming for the multiuser detection with decorrelator in synchronous CDMA systems: Approaches and performance analysis. IEEE Signal Processing 60, 195–211 (1997)
Sathish, R., Anand, G.V.: Spatial wavelet packet denoising for improved DOA estimation. In: Proceedings of the 14th IEEE Signal Processing Society Workshop on Machine Learning for Signal Process., pp. 745–754 (October 2004)
ITU-R SM.1794, Wideband Instantaneous Bandwidth Spectrum Monitoring Systems, International Telecommunication Union (January 2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this paper
Cite this paper
Meenakshi, A.V., Kayalvizhi, R., Asha, S. (2012). Performance Analysis of Fast DOA Estimation Using Wavelet Denoising over Rayleigh Fading Channel on MIMO System. In: Wyld, D., Zizka, J., Nagamalai, D. (eds) Advances in Computer Science, Engineering & Applications. Advances in Intelligent Systems and Computing, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30111-7_92
Download citation
DOI: https://doi.org/10.1007/978-3-642-30111-7_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30110-0
Online ISBN: 978-3-642-30111-7
eBook Packages: EngineeringEngineering (R0)