Improvement on Blind Symbol Rate Detection under Unfavorable Conditions

The performance of the blind symbol rate detection through non-linearity degrades under some conditions, including small excess bandwidth, limited symbol length and low signal-to-noise ratio. The improved algorithm here considers the main disturbance-continuous part of the power spectral of non-linearity as its envelope layer and eliminates it by an envelope sifting process, thus greatly improve the performance of the detectors, especially under one or more unfavorable factors. Simulation results show that the modified method outperforms the original methods in all cases, especially under unfavorable conditions.

[3]  Philippe Loubaton,et al.  Asymptotic analysis of blind cyclic correlation based symbol rate estimation , 2000, 2000 10th European Signal Processing Conference.

[4]  A New Approach to Improved Hilbert-Huang Transform , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[5]  P. Loubaton,et al.  Cyclic correlation based symbol rate estimation , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[6]  J. Sorelius,et al.  Blind chip- and symbol rate CDMA receivers , 1999, 1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304).

[7]  M. Moeneclaey,et al.  ML rate detection for multi-rate TH-UWB impulse radio , 2005, 2005 IEEE International Conference on Ultra-Wideband.

[8]  Franz Quint,et al.  A robust baud rate estimator for noncooperative demodulation , 2000, MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat. No.00CH37155).

[9]  Thomas T. Fang.  I and Q decomposition of self-noise in square-law clock regenerators , 1988, IEEE Trans. Commun..

[10]  S. Hossein Mousavinezhad,et al.  The spectrum of the square of a synchronous random pulse train , 1990, IEEE Trans. Commun..

[11]  Wei Su,et al.  Symbol-rate estimation based on filter bank , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[12]  Georgios B. Giannakis,et al.  Statistical tests for presence of cyclostationarity , 1994, IEEE Trans. Signal Process..

[13]  Yiu-Tong Chan,et al.  Symbol rate estimation by the wavelet transform , 1997, Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS '97.

[14]  S. Sjoberg,et al.  Adaptive coded modulation for wireless packet data systems , 1999, Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324).

[15]  Hwang Soo Lee,et al.  Detection of symbol rate of unknown digital communication signals , 1993 .

[16]  Evren Terzi,et al.  Blind symbol rate estimation: a two stage algorithm , 2009, 2009 IEEE 17th Signal Processing and Communications Applications Conference.

[17]  W. Gardner.  Exploitation of spectral redundancy in cyclostationary signals , 1991, IEEE Signal Processing Magazine.

[18]  Robert J. Inkol,et al.  Estimation of symbol rate from the autocorrelation function , 2009, 2009 Canadian Conference on Electrical and Computer Engineering.

[19]  William A. Gardner,et al.  Signal interception: a unifying theoretical framework for feature detection , 1988, IEEE Trans. Commun..

[20]  M. Flohberger,et al.  Symbol Rate Estimation with Inverse Fourier Transforms , 2006, 2006 International Workshop on Satellite and Space Communications.

[21]  Jie Yang,et al.  Symbol Rate Estimation Using Cyclic Correlation and Haar Wavelet Transform , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[22]  Zhao Zhidong,et al.  A New Method for Processing End Effect In Empirical Mode Decomposition , 2007, 2007 International Conference on Communications, Circuits and Systems.

[23]  Yuan Kang Lee,et al.  A ML rate detection algorithm for IS-95 CDMA , 1999, 1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363).

[24]  M. A. Wickert,et al.  Symbol-rate detection by a power-series-nonlinear envelope detector receiver , 1988, Seventh Annual International Phoenix Conference on Computers an Communications. 1988 Conference Proceedings.

[25]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[26]  Jin Liang.  A New Nonlinear Filtering Algorithm for Colored Background Self-Noise Suppressing of Symbol Rate Estimation , 2007 .

[27]  D.E. Reed,et al.  Minimization of detection of symbol-rate spectral lines by delay and multiply receivers , 1988, IEEE Trans. Commun..

[28]  T. Truong,et al.  Performance of spectral line detection using integrated trispectrum , 1998, IEEE Military Communications Conference. Proceedings. MILCOM 98 (Cat. No.98CH36201).

[29]  D.E. Reed,et al.  A performance comparison of optimum and sub-optimum receiver structures for rate-line detection of digitally modulated carriers , 1988, IEEE Region 5 Conference, 1988: 'Spanning the Peaks of Electrotechnology'.