Regularized successive interference cancellation (SIC) under mismatched modeling

Author

Jun Tong ; Li Li ; Qinghua Guo ; Schreier, Peter J. ; Jiangtao Xi

Author_Institution

Sch. of Electr., Comput. & Telecommun. Eng., Univ. of Wollongong, Wollongong, WA, Australia

fYear

2014

fDate

June 29 2014-July 2 2014

Firstpage

328

Lastpage

331

Abstract

Successive interference cancellation (SIC) has been extensively applied to estimate transmit signals in communication systems. When the channel state information (CSI) and noise statistics are imperfectly estimated, the standard SIC estimators that ignore the model mismatch may perform poorly. This paper introduces regularized SIC estimation to provide robustness against the model mismatch. Suboptimal, low-complexity implementations using (sorted) QR decomposition and approximate choice of regularization parameters are also introduced. Simulation examples demonstrate that the regularized SIC estimators can significantly outperform the standard version.

Keywords

interference suppression; matrix decomposition; CSI; QR decomposition; channel state information; communication systems; mismatched modeling; noise statistics; regularization parameter; regularized SIC estimation; regularized successive interference cancellation; standard SIC estimators; suboptimal low-complexity implementation; transmit signal estimation; Complexity theory; Estimation; Noise; Robustness; Silicon carbide; Standards; Uncertainty; Mismatched modeling; regularization; successive interference cancellation (SIC);

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing (SSP), 2014 IEEE Workshop on

Conference_Location

Gold Coast, VIC

Type

conf

DOI

10.1109/SSP.2014.6884642

Filename

6884642