770 research outputs found
Performance Analysis of Iterative Channel Estimation and Multiuser Detection in Multipath DS-CDMA Channels
This paper examines the performance of decision feedback based iterative
channel estimation and multiuser detection in channel coded aperiodic DS-CDMA
systems operating over multipath fading channels. First, explicit expressions
describing the performance of channel estimation and parallel interference
cancellation based multiuser detection are developed. These results are then
combined to characterize the evolution of the performance of a system that
iterates among channel estimation, multiuser detection and channel decoding.
Sufficient conditions for convergence of this system to a unique fixed point
are developed.Comment: To appear in the IEEE Transactions on Signal Processin
Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols
In this paper, we describe direct-sequence code-division multiple-access
(DS-CDMA) systems with quadriphase-shift keying in which channel estimation,
coherent demodulation, and decoding are iteratively performed without the use
of any training or pilot symbols. An expectation-maximization
channel-estimation algorithm for the fading amplitude, phase, and the
interference power spectral density (PSD) due to the combined interference and
thermal noise is proposed for DS-CDMA systems with irregular repeat-accumulate
codes. After initial estimates of the fading amplitude, phase, and interference
PSD are obtained from the received symbols, subsequent values of these
parameters are iteratively updated by using the soft feedback from the channel
decoder. The updated estimates are combined with the received symbols and
iteratively passed to the decoder. The elimination of pilot symbols simplifies
the system design and allows either an enhanced information throughput, an
improved bit error rate, or greater spectral efficiency. The interference-PSD
estimation enables DS-CDMA systems to significantly suppress interference.Comment: To appear, IEEE Transactions on Wireless Communication
Multiuser Detection and Channel Estimation for Multibeam Satellite Communications
In this paper, iterative multi-user detection techniques for multi-beam
communications are presented. The solutions are based on a successive
interference cancellation architecture and a channel decoding to treat the
co-channel interference. Beams forming and channels coefficients are estimated
and updated iteratively. A developed technique of signals combining allows
power improvement of the useful received signal; and then reduction of the bit
error rates with low signal to noise ratios. The approach is applied to a
synchronous multi-beam satellite link under an additive white Gaussian channel.
Evaluation of the techniques is done with computer simulations, where a noised
and multi-access environment is considered. The simulations results show the
good performance of the proposed solutions.Comment: 12 page
Turbo receivers for interleave-division multiple-access systems
In this paper several turbo receivers for Interleave-Division Multiple-Access (IDMA) systems will be discussed. The multiple access system model is presented first. The optimal, Maximum A Posteriori (MAP) algorithm, is then presented. It will be shown that the use of a precoding technique at the emitter side is applicable to IDMA systems. Several low complexity Multi-User Detector (MUD), based on the Gaussian approximation, will be next discussed. It will be shown that the MUD with Probabilistic Data Association (PDA) algorithm provides faster convergence of the turbo receiver. The discussed turbo receivers will be evaluated by means of Bit Error Rate (BER) simulations and EXtrinsic Information Transfer (EXIT) charts
Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression
This paper proposes a multistage decomposition for blind adaptive parameter estimation in the Krylov subspace with the code-constrained constant modulus (CCM) design criterion. Based on constrained optimization of the constant modulus cost function and utilizing the Lanczos algorithm and Arnoldi-like iterations, a multistage decomposition is developed for blind parameter estimation. A family of computationally efficient blind adaptive reduced-rank stochastic gradient (SG) and recursive least squares (RLS) type algorithms along with an automatic rank selection procedure are also devised and evaluated against existing methods. An analysis of the convergence properties of the method is carried out and convergence conditions for the reduced-rank adaptive algorithms are established. Simulation results consider the application of the proposed techniques to the suppression of multiaccess and intersymbol interference in DS-CDMA systems
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