Adaptive Multiuser Research Articles

Steady-state performance analysis of HOS-based blind adaptive multiuser detection

The blind adaptive multiuser detections based on higher-order statistics (HOS) can obtain higher steady-state decorrelating performance than the conventional linear algorithm under the high SNR condition. However, the closed-form analysis for this steady-state performance is scarce due to the complication of analyzing the nonlinear updates of the adaptive algorithm. An analysis approach based on ordinary differential equation (ODE) method is proposed to get the closed-form excess mean-square error (EMSE) expression of the HOS-based multiuser detections. The simulation and the comparison verify the results of the analysis.

Blind Multiuser Detection in Frequency Domain for MC-CDMA Systems Using Particle Swarm Optimization

In digital communication systems, the constant modulus algorithm (CMA) for blind multiuser detector has some disadvantage such as slow convergence speed and weight phase rotation. In this paper, we put forward a novel receiver, which combines CMA blind adaptive multiuser detection and particle swarm optimization (PSO) technique in frequency domain for multi-carrier direct sequence code division multiple access (MC DS-CDMA) systems. By this approach we present an adaptive multistage structure based on PSO technique. In this structure, the weights are obtained by PSO technique between the received signal and its estimate through a CMA. The resulting weights contain reliability information for the hard decisions made in the previous stage. The simulation results show that BER performance of the PSO-based CMA blind multiuser detector is superior to that of steepest decreasing constant modulus algorithm (SDCMA), linearly constrained constant modulus algorithm (LCCMA), CMA based multiuser detection and is worthy due to its significant detection performance to achieve desirable improvement in convergence speed and tractability.

Blind Adaptive Multiuser Detection for the MC-CDMA Systems Using Orthogonalized Subspace Tracking

In this paper, we study the performance of subspace-based multiuser detection techniques for multicarrier code-division multiple access (MC-CDMA) systems. We propose an improvement in the PASTd algorithm by cascading it with the classical Gram-Schmidt procedure to orthonormalize the eigenvectors after their sequential extraction. The tracking of signal subspace using this algorithm, which we call OPASTd, has a faster convergence as the eigenvectors are orthonormalized at each discrete time sample. This improved PASTd algorithm is then used to implement the subspace blind adaptive multiuser detection for MC-CDMA. We also show that, for multiuser detection, the complexity of the proposed scheme is lower than that of many other orthogonalization schemes found in the literature. Extensive simulation results are presented and discussed to demonstrate the performance of the proposed scheme.

Large System Spectral Analysis of Covariance Matrix Estimation

Eigendecomposition of estimated covariance matrices is a basic signal processing technique arising in a number of applications, including direction-of-arrival estimation, power allocation in multiple-input/multiple-output (MIMO) transmission systems, and adaptive multiuser detection. This paper uses the theory of non-crossing partitions to develop explicit asymptotic expressions for the moments of the eigenvalues of estimated covariance matrices, in the large system asymptote as the vector dimension and the dimension of signal space both increase without bound, while their ratio remains finite and nonzero. The asymptotic eigenvalue distribution is also obtained from these eigenvalue moments and the Stieltjes transform, and is extended to first-order approximation in the large sample-size limit. Numerical simulations are used to demonstrate that these asymptotic results provide good approximations for finite systems of moderate size.

Error probability of direct sequence-code division multiple access systems with adaptive antenna minimum mean-square error multiuser receivers in Rayleigh-lognormal fading

In direct sequence-code division multiple access (DS-CDMA) cellular systems spreading codes, fading and positions of the users can be modelled as independent random variables and the corresponding multiuser interference (MUI) experienced by the base station is non-stationary. Here we evaluate in closed form the bit error probability for space-time linear minimum mean square error (MMSE) multiuser receivers for symbol-synchronous DS-CDMA system (bounds are provided for symbol-asynchronous system) by extending the known asymptotic results for random spreading sequences to non-stationary MUI. The analysis is based on the effective interference at the decision variable that is carried out to account for the non-stationary MUI that results from the multiuser beamforming that adapts each spatial filter to the randomness of the angle of arrivals of all the users. Propagation for each user is Rayleigh-lognormal faded channels as it is fairly general to model the imperfect power-control. The numerical validation proves that a simple geometrical model is accurate to evaluate the error probability for any arbitrary system loading.

Performance Analysis of Blind Multiuser Detector with Fuzzy Kalman Filter in IR-UWB

With on-going widespread deployment of UWB systems, multi-user detection has received increasing attention. In order to successfully decode the users in a UWB system, the most important issue is to be solved, apart from the multi-path and multiple-access channel. Most existing approaches employ correlators to correlate the received signal with a template signal. This technique appears very powerful, but not so satisfactory in a multi-path and multiple-access channel. A novel multi-user detection algorithm relying on the theory of canonical representation of multi-user receivers and fuzzy Kalman filtering (FKF) is proposed for impulse radio ultra-wideband systems. Dynamical systems of time-hopping BPSK in ultra-wideband are developed separately in the paper. Although the Kalman filtering algorithm is conditioned on perfect knowledge of some system parameters, we have used the fuzzy technique to overcome the difficulties. It is presumed that both, the process noise and the measurement noise, are zero-mean white sequences with their known covariance. If the Kalman filter is based on a complete and perfect model, the innovation should be a zero-mean white noise process, otherwise there is something erroneous with the design and the filter is not performing optimally, thus making the filter to diverge or coverage to a large bound. In practice, it is difficult to know the exact values for covariance. In order to reduce computation, we have to ignore some errors, but sometimes those unmodeled errors will remain significant. The adaptation of the filter uses a fuzzy inference system based on a covariance matching scheme that adjusts the measurement noise covariance matrix online. The basic idea behind this technique is to make the residual consistent with their theoretical covariance. The fuzzy Kalman filter method is proposed in the previous subsection is related to many existing algorithms for adaptive multiuser detector. Now, some performances are given to compare the differences from other prior algorithms. Since the Kalman filter scheme and the RLS one are similar, it is necessary to compare the proposed algorithm with the before RLS algorithms. Theoretical analysis and numerical results show that the new scheme has a better bit error rate performance compared with the conventional detector, and the effectiveness of the novel Kalman filtering algorithm.

Throughput analysis of multi-user OFDMA-systems using imperfect CQI feedback and diversity techniques

In this paper, the throughput of an adaptive multiuser SISO-OFDMA/FDD system with channel quality information (CQI) signalled digitized over a feedback channel to the transmitter is investigated, where the instantaneous signal-to-noise ratio (SNR) of the different subcarriers is used as CQI to exploit multi-user diversity using adaptive subcarrier allocation. The CQI available at the transmitter is assumed to be imperfect due to estimation errors and quantization at the receiver side, time delay and feedback errors. In this paper, a closed form expression of the average throughput of an adaptive multi-user OFDMA system using imperfect CQI and uncoded M-QAM modulation is derived. Furthermore, a closed form expression of the average throughput of an OFDMA system exploiting frequency diversity, which does not require CQI at the transmitter, is presented. Both throughput performances are compared in order to identify the optimal transmission strategy depending on the grade of CQI imperfectness.

Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523---1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.

A Blind Adaptive MMSE Multiuser Detector over Multipath CDMA Channels and its Analysis

Based on the refinement-only fast subspace tracking (RO-FST) algorithm to adaptively estimate the signal sub-space, a blind adaptive SVD-based minimum-mean-square-error (MMSE) multiuser detector is proposed in this paper for asynchronous direct-sequence code-division-multiple-access (DS-CDMA) systems over multipath fading channels. Numerical results show that the proposed detector gives low computational complexity and good performance in terms of signal-to-interference-plus-noise ratio (SINR) and bit-error-rate (BER). In addition, we apply the perturbation analysis of the proposed adaptive detector to derive the closed-form expressions for the mean-square error (MSE) and SINR. The analytical results are shown to match well with the simulation results.

Adaptive multiuser receiver with joint channel and time delay estimation of CDMA signals based on the square-root unscented filter

The paper discusses an adaptive multiuser receiver for CDMA systems in which the scaled unscented filter (SUF) and the square root unscented filter (SURF) are used for joint estimation and tracking of the code delays and multipath coefficients of the received CDMA signals. The proposed channel estimators are more near-far resistant than the conventional extended Kalman filter (EKF) and present lower complexity than the conventional particle filter (PF) based methods. To present meaningful performance measures, the modified Cramer-Rao lower bound (CRLB) and computational complexity metrics are derived for the proposed and existing channel estimators. Computer simulation results demonstrate the superior performance of the proposed channel estimators. The proposed estimators are also shown to exhibit lower complexity relative to the PF.

Power-Controlled CDMA Cell Sectorization with Multiuser Detection: A Comprehensive Analysis on Uplink and Downlink

We consider the joint optimization problem of cell sectorization, transmit power control and multiuser detection for a CDMA cell. Given the number of sectors and user locations, the cell is appropriately sectorized such that the total transmit power, as well as the receiver filters, is optimized. We formulate the corresponding joint optimization problems for both the uplink and the downlink and observe that in general, the resulting optimum transmit and receive beamwidth values for the directional antennas at the base station are different. We present the optimum solution under a general setting with arbitrary signature sets, multipath channels, realistic directional antenna responses and identify its complexity. We propose a low-complexity sectorization algorithm that performs near optimum and compare its performance with that of optimum solution. The results suggest that by intelligently combining adaptive cell sectorization, power control, and linear multiuser detection, we are able to increase the user capacity of the cell. Numerical results also indicate robustness of optimum sectorization against Gaussian channel estimation error.

An adaptive multiuser detector for DS-CDMA systems in multipath fading channels

In this paper, we investigate the performance of an adaptive multistage detection scheme for direct-sequence code-division multiple-access (DS-CDMA) systems. The first stage consists of an adaptive...

Multiuser channel estimation using robust recursive filters for CDMA system

In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

An adaptive multiuser detector for DS‐CDMA systems in multipath fading channels

AbstractIn this paper, we investigate the performance of an adaptive multistage detection scheme for direct‐sequence code‐division multiple‐access (DS‐CDMA) systems. The first stage consists of an adaptive multiuser detector which is based on the linear constrained minimum variance (LCMV) criterion. The interference cancellation (IC) occurs in the second stage. The performance of the iterative receiver over both flat and frequency‐selective fading channels is investigated and compared to the single‐user bound. In all cases, and under heavy system loads with near‐far problems, the iterative receiver is shown to offer substantial performance improvement and large gain in user‐capacity relative to the standard LCMV. In flat‐fading channels, our results show that the performance of the iterative detector is very close to the single‐user bound. For the frequency‐selective channel, this performance is noted to be in the order of 1 dB far from the single‐user bound. Copyright © 2007 John Wiley & Sons, Ltd.

The LSCM_SUB algorithm for blind multiuser detection in multipath CDMA channels

In this article, the least square constant modulus algorithm (LSCMA) is combined with the subspace approach and a LSCM_SUB (Subspace) blind adaptive multiuser detection in multipath code division multiple access (CDMA) channels is presented. The poor performance of LSCMA in the low signal to noise ratio (SNR) is improved by the LSCM_SUB algorithm. The performance of the proposed LSCM_SUB algorithm is compared with that of LSCMA. Simulation results show that the LSCM_SUB algorithm is superior to the LSCMA, especially in the low SNR.

Diversity Reception of an Asynchronous Blind Adaptive Multiuser Detector Through Correlated Nakagami Fading Channel

In this paper, blind adaptive multiuser detection (MUD) technique is developed for uplink transmission in multiuser space diversity DS-CDMA system to overcome multipath fading effect and multiple access interference. The system consists of a space diversity, a precombining blind adaptive detector (PBAD), and a weight adaptation technique based on the minimization of the mean output energy (MOE). The bit error rate (BER) performance of this receiver for asynchronous DS-CDMA signals with independent and correlated antenna branches under Nakagami fading channel for BPSK system is evaluated. It has been seen that the use of antenna diversity can yield substantial improvement in performance even if the correlation between the antenna elements is relatively large (up to 0.795). However, the large correlation values pose a significant reduction in the diversity gain in comparison with the zero correlation situation. It has also been confirmed by simulations that the PBAD provides a significant receiver performance in comparison with the RAKE receiver employing antenna diversity.

Low complexity constant modulus based cyclic blind adaptive multiuser detection

Low complexity constant modulus based cyclic blind adaptive multiuser detection

Blind adaptive multiuser detector for nonlinearly modulated satellite mobile CDMA systems

This paper presents a novel blind adaptive noncoherent decorrelative multiuser detector for nonlinearly modulated satellite mobile Code Division Multiple Access (CDMA) systems. By using the known signature waveforms of the counterpart earth station in the blind adaptive multiuser detector, the system performance has been improved obviously. The computation results about the convergence properties of the new detector and the previous detectors demonstrate that the proposed multiuser detector has better performance than previous multiuser detectors for nonlinearly modulated CDMA systems.

Minimum probability of error-based adaptive multiuser decision feedback detection

For synchronous direct-sequence code-division multiple access (DS-CDMA) systems, a new criterion based on minimum probability of error (MPE) is proposed for designing decision feedback detectors (DFDs) instead of the conventional minimum mean-squared error criterion. The MPE criterion-based DFD (MPEDFD) tries to minimize the average/conditional probability of error adaptively. Study of bit-error rate and convergence performance shows that the MPEDFDs work pretty well after a short training sequence. Moreover, the modified MPEDFD is applicable for the asynchronous DS-CDMA systems with multipath.

Nonparametric multiuser detection in non-Gaussian channels

Existing multiuser detection techniques in wireless systems are based on the assumption that some information on the parameters of the probability density function (pdf) of ambient noise is available. Such information may not be available in all cases, particularly for non-Gaussian and impulsive noises, or may change depending on circumstances. In this paper, we present a technique for multiuser detection that does not require any a priori knowledge about the noise parameters. This method is based on using pseudo norms for linear nonparametric regression. Analytical and simulation results show that the proposed method offers an improved, or at least comparable, performance over existing robust techniques in the absence of any information on the nature of noise in the environment. The increased computational complexity is marginal compared to existing parametric detectors. In addition, the proposed nonparametric detector is portable in the sense that it does not need to be tuned for different noise models without any considerable degradation of performance. We also show that in non-Gaussian noise, the performance of blind adaptive nonparametric multiuser detectors is better than that of robust multiuser detectors.