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Adaptive Rake Multiuser Receiver with Linearly Constrained Sliding Window RLS Algorithm for DS-CDMA SystemsLee, Hsin-Pei 04 July 2003 (has links)
The technique of direct sequence code division multiple access (DS-CDMA) cellular system has been the focus of increased attention. In this thesis, we will consider the environment of DS-CDMA systems, where the asynchronous narrow band interference due to other systems is joined suddenly to the CDMA system. The suddenly joined narrow band interference will make the system crush down. The main concern of this thesis is to deal with suddenly joined narrow band interference cancellation.
An adaptive filtering algorithm based on sliding window criterion and variable forgetting factor is known to be very attractive for violent changing environment. In this thesis, a new sliding window linearly constrained recursive least squares (SW LC-RLS) algorithm and variable forgetting factor linearly constrained recursive least squares (VFF LC-RLS) algorithm on the modified minimum mean squared error (MMSE) structure [9] is devised for RAKE receiver in direct sequence code-division multiple access (DS-CDMA) system over multipath fading channels. Where the channel estimation scheme is accomplished at the output of adaptive filter. The proposed SW LC-RLS algorithm and VFF LC-RLS has the advantage of having faster convergence property and tracking ability, and can be applied to the environment, where the narrow band interference is suddenly joined to the system, to achieve desired performance. Via computer simulation, we show that the performance, in terms of mean square errors (MSE) and signal to interference plus noise ratio (SINR), is superior to the conventional LC-RLS and orthogonal decomposition-based LMS algorithms based on the MMSE structure [9].
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Blind Adaptive Multiuser Detection for DS-CDMA System Based on Sliding Window RLS AlgorithmPan, Wei-Hung 10 September 2004 (has links)
Direct sequence code division multiple access (DS-CDMA) technique is one of the significant multiplexing technologies used in wireless communication services. In the DS-CDMA framework, all users have been assigned distinct signature code sequence to achieve multiple accesses within the same frequency band, and allow signal separating at the receiver. Under multipath fading environment with near-far effect, the current CDMA systems employed the RAKE receiver, to enhance the system performance. It is known that if training data is available the minimum mean squares error (MMSE) multiuser receiver, in which the average power of the receiver output is minimized subject to appropriate constraints, could be obtained by solving directly by the constrained Wiener estimation solution. However, if this is not the case, the blind multiuser receiver is an alternative approach to achieve desired performance closed to the one with the MMSE approach.
In this thesis, based on the max/min criterion, the blind multiuser receiver, with linear constraints, is devised. Here constraint equations are written in parametric forms, which depend on the multipath structure of the signal of interest. Constraint parameters are jointly optimized with the parameters of the linear receiver to obtain the optimal parameters. In consequence, the sliding window linearly constrained RLS (SW-LC-RLS) algorithm is employed to implement the optimal blind receiver, with max/min approach. This new proposed scheme can be used to deal with multiple access interference (MAI) suppression for the environments, in which the narrow band interference (NBI) due to other systems is joined suddenly to the DS-CDMA systems, and having serious near-far effect. Under such circumstance, the channel character due to the NBI and near-far effect will become violent time varying, such that the conventional LC-RLS algorithm as well as LC-LMS algorithms could not perform well. Via computer simulation it confirms that our proposed scheme has better capability for MAI suppression in DS-CDMA systems than other existing schemes, and is more robust against the NBI and near-far problems.
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