Blind, adaptive channel shortening by sum-squared auto-correlation minimization (SAM)

被引：77

作者：

Balakrishnan, J ^{[1
]}

Martin, RK ^{[1
]}

Johnson, CR ^{[1
]}

机构：

[1] Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14853 USA

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2003年 / 51卷 / 12期

关键词：

adaptive; blind; channel shortening; DMT; equalization; multicarrier; OFDM;

D O I：

10.1109/TSP.2003.818892

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We propose a new blind, adaptive channel shortening algorithm for updating the coefficients of a time-domain equalizer in a system employing multicarrier modulation. The technique attempts to minimize the sum-squared auto-correlation terms of the effective channel impulse response outside a window of desired length. The proposed algorithm, known as "sum-squared auto-correlation minimization" (SAM), requires the source sequence to be zero-mean, white, and wide-sense stationary, and it is implemented as a stochastic gradient descent algorithm. Simulation results have been provided, demonstrating the success of the SAM algorithm in an AUTHOR: What does ADSL stand for? (ADSL) system.

引用

页码：3086 / 3093

页数：8

共 40 条

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