Widely Linear System Estimation Using Superimposed Training

Author

Arriaga-Trejo, Israel A. ; Orozco-Lugo, Aldo G. ; Veloz-Guerrero, Arturo ; Guzmán, Manuel E.

Author_Institution

Commun. Sect., Cinvestav-IPN, Mexico City, Mexico

Volume

59

Issue

11

fYear

2011

Firstpage

5651

Lastpage

5657

Abstract

In this correspondence, the use of superimposed training (ST) as a mean to estimate the finite impulse response (FIR) components of a widely linear (WL) system is proposed. The estimator here presented is based on the first-order statistics of the signal observed at the output of the system and its variance is independent of the channel components if suitable designed training sequences are employed. The construction of such sequences having constant magnitude both in time and frequency domains is also addressed.

Keywords

FIR filters; estimation theory; linear systems; statistical analysis; FIR components; finite impulse response; first-order statistics; frequency domain; superimposed training; time domain; widely linear system estimation; Channel estimation; Equations; Estimation; Frequency domain analysis; Joints; Peak to average power ratio; Training; Joint channel I/Q imbalance estimation; optimum channel independent sequences; superimposed training; widely linear system estimation;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2011.2162834

Filename

5960800