DocumentCode
1939577
Title
Semi-Blind Multiuser Detection Based on Subspace Constrained LMS for MC-CDMA Uplink
Author
Meng, Yan ; Wang, Jinkuan ; Song, Xin ; Zhu, Jun
Author_Institution
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
Volume
3
fYear
2006
fDate
16-20 Nov. 2006
Abstract
In this paper, a new semi-blind multiuser detection algorithm based on subspace constrained least mean-squared (LMS) is proposed for multicarrier code division multiple access (MC-CDMA) uplink system. This proposed detector makes use of the spreading sequences of all known users to impose multiple constraints on the minimum output energy (MOE) multiuser detection so that the interference within the cell can be suppressed. A subspace constrained LMS algorithm is proposed to obtain the MOE weight vector adaptively. To reduce the computational complexity, an improved projecting approximation subspace tracking with deflation (PASTd) algorithm is developed for adaptive signal subspace estimation. Computer simulations show that the performance of the proposed semi-blind multiuser detection is significantly superior to that of the LMS-based blind multiuser detection
Keywords
code division multiple access; computational complexity; interference suppression; least mean squares methods; multiuser detection; MC-CDMA uplink; adaptive signal subspace estimation; computational complexity; interference suppression; least mean-square; minimum output energy multiuser detection; multicarrier code division multiple access uplink system; projecting approximation subspace tracking with deflation algorithm; semiblind multiuser detection; spreading sequences; subspace constrained LMS; Approximation algorithms; Computational complexity; Computer simulation; Detectors; Interference constraints; Interference suppression; Least squares approximation; Multicarrier code division multiple access; Multiuser detection; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2006 8th International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9736-3
Electronic_ISBN
0-7803-9736-3
Type
conf
DOI
10.1109/ICOSP.2006.345846
Filename
4129273
Link To Document