Condition number-constrained matrix approximation with applications to signal estimation in communication systems

Authors

Jun Tong, University of WollongongFollow
Qinghua Guo, University of WollongongFollow
Sheng Tong, University of WollongongFollow
Jiangtao Xi, University of WollongongFollow
Yanguang Yu, University of WollongongFollow

RIS ID

90562

Publication Details

J. Tong, Q. Guo, S. Tong, J. Xi & Y. Yu, "Condition number-constrained matrix approximation with applications to signal estimation in communication systems," IEEE Signal Processing Letters, vol. 21, (8) pp. 990-993, 2014.

Abstract

This letter introduces condition number-constrained approximation to matrices used for signal estimation and detection. Under a Frobenius norm criterion, the closed-form solution to the optimal approximation is derived, which can be found efficiently for arbitrary condition number constraints. The resulting approximation techniques are applied to the imperfectly estimated covariance and channel matrices used for estimating transmit signals in communication systems. With an appropriately chosen value of condition number, the robustness of the linear and decision-feedback estimators (DFE) against model mismatch can be significantly improved.

Grant Number

ARC/DE120101266

Additional Grant Number

http://purl.org/au-research/grants/arc/DE120101266