Title
Adaptive soft-input soft-output multiuser detection for asynchronous coded DS-CDMA systems
Abstract
In this paper, we apply adaptive algorithms in the SISO multiuser detector in order to avoid the need for a priori information. First, we present the optimum SISO parallel decision feedback detector for asynchronous DS-CDMA systems, which requires many system parameters. Then, we propose two adaptive versions of this SISO detector which are based on the normalized least mean square (NLMS) and recursive least squares (RLS) algorithms, respectively. The signature waveforms and relative delays of multiple users are unknown to the adaptive SISO detector. Only a training sequence is required for each user. Our SISO adaptive detectors effectively exploit the a priori information of coded symbols, which is based on soft inputs from a bank of single user decoders, to further improve their convergence performance. Furthermore, we consider how to select practical finite feedforward and feedback filter lengths to obtain good tradeoff between the performance and computational complexity of the receiver. Finally, Monte-Carlo simulation results are presented and compared.
Year
DOI
Venue
2005
10.1109/WCNC.2005.1424504
WCNC
Keywords
Field
DocType
adaptive signal detection,recursive least squares algorithms,normalized least mean square algorithms,asynchronous coded ds-cdma systems,training sequence,monte carlo simulation,finite feedforward filter lengths,adaptive siso multiuser detector,adaptive soft-input soft-output multiuser detection,coded symbol a priori information,spread spectrum communication,convergence,least mean squares methods,finite feedback filter lengths,code division multiple access,monte carlo methods,multiuser detection,recursive estimation,single user decoder soft inputs,parallel decision feedback detector,detectors,propagation delay,computational complexity,feedback,decoding
Least mean squares filter,Asynchronous communication,Computer science,Multiuser detection,Real-time computing,Detector,Recursive least squares filter,Computational complexity theory,Feed forward,Spread spectrum
Conference
Volume
ISSN
ISBN
1
1525-3511
0-7803-8966-2
Citations 
PageRank 
References 
0
0.34
9
Authors
3
Name
Order
Citations
PageRank
Wei Zhang114312.84
Claude D'Amours24412.78
Abbas Yongaçoglu310723.19