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

被引：0

作者：

Balakrishnan, J ^{[1
]}

Martin, RK ^{[1
]}

Johnson, CR ^{[1
]}

机构：

[1] Texas Instruments Inc, Dallas, TX 75243 USA

来源：

THIRTY-SIXTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS - CONFERENCE RECORD, VOLS 1 AND 2, CONFERENCE RECORD | 2002年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a new blind, adaptive channel shortening algorithm for updating a time-domain equalizer (TEQ) in a system employing multicarrier modulation. The technique attempts to minimize the sum-squared auto-correlation of the combined channel-TEQ impulse response outside a window of desired length. The proposed algorithm, ''Sum-squared Auto-correlation Minimization'' (SAM), assumes the source sequence to be white and wide-sense stationary, and it is implemented as a stochastic gradient descent algorithm. Simulation results demonstrating the success of the SAM algorithm are provided.

引用

页码：398 / 402

页数：5

共 13 条

[1] Optimum finite-length equalization for multicarrier transceivers [J].