Application of Non-Linear Functions at Distribution of Output SINR Gaussian Interference Channels

journal of Artificial Intelligence in Electrical Engineering

مقاله 3، دوره 2، شماره 7، بهمن 2013، صفحه 16-23   

نویسندگان

Tohid Sedghi؛ Shahin Shafei

چکیده

We have examined the convergence behavior of the LSCMA in some simple environments. Algorithms such as Multi¬ Target CMA, Multistage CMA, and Iterative Least Squares with Projection can be used for this purpose. The results presented here can form a basis for analysis of these multi-signal extraction techniques. Clearly, the variance and distribution of output SINR obtained with the LSCMA is also an important area for investigation. We finally comment on the hard-limit non-linearity. For high SIR, the hard-limiter is the optimal non-linearity when the desired signal has a constant envelope. However, at low SIR other non-linearities can yield greater SIR gain. Thus, it is possible that non-linear functions other than the hard-limit can be used to develop blind adaptive algorithms, which converge faster for low initial SINR.

مراجع

[1] T. E. Biedka, W. H. Tranter, and J. H. Reed, "Convergence analysis of the least squares constant modulus algorithm Application of Non-Linear Functions at Distribution … 23 interference cancellation applications", IEEE Trans. on Commun., vol. 48, no. 3, pp. 491-501, March 2011.

[2] A.L. Swindlehurst, S. Daas, and J. Yang, "Analysis of a decision directed beamformer",IEEE Trans. on Signal Processing., vol. 43, no. 12, pp. 2920- 2927, December 2005.

[3] 1. S. Reed, J. D. Mallett, and L. E. Brennan, "Rapid convergence rate in adaptive arrays", IEEE Trans. Aerospace Electron. Syst., vol. AES-10, pp. 853-863, Nov. 2004.

[4] B. G. Agee, "Convergent behavior of modulus-restoring adaptive arrays in gaussian interference environments", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 818-822, Dec. 2008.

[5] J. Lundell and B. Widrow, "Application of the constant modulus adaptive beamformer to constant and nonconstant modulus signals", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 432- 436, Nov. 2007 [6] ] J. R. Treichler and B. G. Agee, "A new approach to multipath correction of constant modulus signals", IEEE Trans. on Acous., Speech, and Signal Process., vol. ASSP-31, no. 2, pp. 459-471, April 2003.

[7] R. Gooch and J. Lundell, "The CM array: An adaptive beamformer for constant modulus signals", Proc. of Inter. Conf. on Acous., Speech, and Signal Process., pp. 2523-2526, April 2006.

[8] B. G. Agee, "The least-squares CMA: A new technique for rapid correction of constant modulus signals", Proc. of Inter. Conf. on Acous., Speech, and Signal Process., pp. 953-956, April 2006.

[9] B.G. Agee, "Maximum likelihood approaches to blind adaptive signal extraction using narrowband arrays", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 716-720, Nov. 2011.

[10] Alle-Jan van der Veen and A. Paulraj, "An analytical constant modulus algorithm", IEEE Trans. Signal Processing, vol. 44, no. 5, pp. 1136-1155, May 2006.