Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31105
Impulse Response Shortening for Discrete Multitone Transceivers using Convex Optimization Approach

Authors: Ejaz Khan, Conor Heneghan


In this paper we propose a new criterion for solving the problem of channel shortening in multi-carrier systems. In a discrete multitone receiver, a time-domain equalizer (TEQ) reduces intersymbol interference (ISI) by shortening the effective duration of the channel impulse response. Minimum mean square error (MMSE) method for TEQ does not give satisfactory results. In [1] a new criterion for partially equalizing severe ISI channels to reduce the cyclic prefix overhead of the discrete multitone transceiver (DMT), assuming a fixed transmission bandwidth, is introduced. Due to specific constrained (unit morm constraint on the target impulse response (TIR)) in their method, the freedom to choose optimum vector (TIR) is reduced. Better results can be obtained by avoiding the unit norm constraint on the target impulse response (TIR). In this paper we change the cost function proposed in [1] to the cost function of determining the maximum of a determinant subject to linear matrix inequality (LMI) and quadratic constraint and solve the resulting optimization problem. Usefulness of the proposed method is shown with the help of simulations.

Keywords: Convex optimization, equalizer, target impulse response, matrix inequality

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1434


[1] N. Al-Dahir,and J.M. Cioffi, "Optimum finite-length equalization for multicarrier transceivers", IEEE trans. on communications, vol.44, no.1, Jan, 1996.
[2] G. Arsalan, B. L. Evans and S. Kiaei, "Equalization for discrete multitone transceivers to maximize bit rate", IEEE Trans. on signal processing , vol.49,no.12,Dec. 2001.
[3] N. Al-Dahir,and J.M. Cioffi, "A bandwidth-optimized reduced complexity equalized multicarrier transreceiver", IEEE Trans. on communications, vol. 45, no. 8, Aug. 1997.
[4] F. Alizadeh, "Interior point methods in semidefinite programming with applications to combinatorial optimization", SIAM journal of optimization, 5, pp.13-51, 1995.
[5] L. Vandenberghe, S. Boyd, and S. Wu, " Determinant maximization with linear matrix inequality constraints", SIAM journal on matrix analysis and applications, 19(2), pp. 499-533, 1998.
[6] P. S. Bullen, D. S. Mitrinovic, and P. M. Vasic, (eds), "Means and their inequalities", D. Reidel pub. co., 1988.
[7] R. A. Horn and C. R. Johnson, "Matrix analysis", Cambridge Univ. Press, 1999.
[8] J. M. Cioffi, "A multicarrier primer", Amati. Commun. Corp., Stanford Univ. Stanford, CA, T1E1.4/91-157, 1991.
[9] D. Daly, C. Heneghan, and A. D. Fagan, "Minimum mean squared error impulse response shortening for discrete multitone transceivers", IEEE Trans. on signal proc. vol.52, no.1, Jan. 2004.