Blind multiuser detector based on orthogonal projection

For high-speed code division multiple access (CDMA) systems, interchip interference that is caused by multipath propagation becomes severe and cannot be ignored. Together with the multiple access interference due to nonideal conditions in CDMA, they become major obstacles to overall system performance. In this paper, both batch and adaptive algorithms based on linear prediction are proposed for joint blind equalization and multiuser detection for asynchronous CDMA systems. It is shown that the new methods are insensitive to estimation error of propagation delay or chip timing. In addition, the adaptive algorithm is computationally efficient. Simulation results show that the proposed methods are also near-far resistant and compare favorably to many existing methods.

The performance of blind multiuser detection methods is known to degrade severely in the presence of even small mismatches between the actual and the presumed desired user signatures. Such mismatches may occur in practical situations due to an imperfect knowledge of the channel impulse response. We propose a new robust approach to blind multiuser detection in the presence of unknown arbitrary-type mismatches of the desired user signature. Two different formulations of a robust multiuser receiver are considered. The proposed formulations are based on the explicit modeling of uncertainties in the covariance matrix of the desired user signature and/or data covariance matrix and optimization of the worst-case performance. Simple closed-form solutions to the considered robust multiuser detection problems are derived. The proposed methods have a computational complexity comparable to that of the traditional blind multiuser detection algorithms, and, at the same time, offer an improved robustness and faster convergence rates.

We treat utility-based joint power control and rate allocation in a downlink code division multiple access system, where either the matched-filter or the blind multiuser detection technique is employed at the mobile receivers. Rate allocation is performed on a per-frame basis; whereas within the frame, power control is performed at the symbol basis. A hierarchical rate allocation scheme is proposed, which together with the utility-based power control and the opportunistic fair scheduling scheme, maximizes the instantaneous weighted system throughput and the number of feasible users, and at the same time, guarantees the fairness among all users. In order to apply such a resource allocation framework to systems employing blind multiuser detection, we make use of the recent analytical results on the signal-to-interference-plus-noise-ratio performance of the blind multiuser detectors, assuming multiple spreading codes are used to realize multiple data rates. Our results show that under the utility-based joint power and rate allocation framework, the system capacity is significantly enhanced by using blind multiuser detection and the fairness can be well guaranteed.

In this paper, a new multiuser detection scheme for synchronous DS/CDMA system in AWGN channel is presented.Combining the characteristics ofthe minimum mean squared error (MMSE) blind adaptive multiuser detector and the grouppartitioned multiuser detector, this new detector can be viewed as a generalized multiuser detector. Its relationship withother detectors is also discussed. Good performance has been proven by simulations.This new group partition blind multiuser detector includes two separate parts, a blind adaptive part and a conventional non-adaptive one. All active users are divided into several groups in advance. In the first step, using the modified constrainedblind adaptive multiuser interference cancellation strategy, multi-access interference (MAI) contributed by the users who donot belong to the same group is suppressed. MAI from the users of the same group is suppressed in the second stage by aconventional non-adaptive multiuser detector, where nearly all kinds of previous proposed multiuser detectors can be used.In this way, all multiuser interference is reduced in the two stages. Only the information of the users belonging to the samegroup is needed for detection. Others users' information such as the signature sequences is not used by the detector, whichwill increase the convenience of implementation.Keywords: DS/CDMA, Multiuser detection, Blind adaptive algorithm, Group partition

In this paper, a new semi-blind multiuser detection based on a hybrid of Chebyshev approximation (CA) and subspace estimation is proposed for multicarrier code division multiple access (MC-CDMA) uplink. It is shown that the detector can be expressed as an anchored signal in the signal subspace and the coefficients can be estimated by CA algorithm. The spreading sequences of all known users are used to impose the linear vector constraints on the multiuser detector such that the interferers within the cell are suppressed effectively. To reduce the computational complexity, an improved projecting approximation subspace tracking with deflation (PASTd) algorithm is presented for adaptive subspace estimation. Simulation results demonstrate that the proposed semi-blind multiuser detection offers substantial performance gains over the blind multiuser detection in the MC-CDMA uplink environment.

In this paper, two independent component analysis (ICA) based algorithms are proposed for blind multiuser detection (BMUD) in DS-CDMA systems. The first algorithm is Per-processing for Noisy ICA Based Blind Multiuser Detection that can reduce the noise in the detection system but it still has the accumulation of error. The second algorithm is Estimation and Elimination of Noise for ICA Based Blind Multiuser Detection which converses nonlinear noisy model into linear model to utilize some special characters of the new mixing matrix, and estimate the noise signal and eliminate the noise signal. This proposed approach can work well under low SNR conditions. The performances of the algorithms are evaluated using computer simulation. Simulations indicate improvements in terms of error probability and stability performance in detection.

A new adaptive quasi-Newton eigen-estimation method is applied to blind multiuser detection. Computer simulation results are provided to compare its performance with the PASTd algorithm. The results show that the proposed approach performs identically to the PASTd algorithm and is significantly superior to it. Especially, the proposed approach has a relatively fast convergence rate, which may pose a problem for a time varying system, so it is a good adaptive multiuser detection algorithm.

This paper presents a blind multi-user detection technique for multi-antenna quadrature amplitude modulation (QAM) receivers with Inphase/Quadrature phase (I/Q) imbalances. The estimation of multiple users in the presence of I/Q imbalances is performed by Blind Source Separation (BSS) methods. While the complex-valued signal model for multi-antenna QAM receivers does not lend itself to BSS due to the effect of I/Q imbalances, reformulating the signal model to a real-valued equivalent form enables the application of BSS. The proposed method enables multiple users to share the same bandwidth simultaneously in different geographical locations, and avoids the need for the knowledge of the channel state information. In addition, despite of the presence of I/Q imbalances in all receiver branches, the number of antenna required in the receiver is equal to the number of users. Computer simulations are conducted using the popular Fast-ICA (Independent Component Analysis) algorithm, and the simulation results confirmed the effectiveness of the proposed technique.

In this paper we consider blind signal detection for an asynchronous code division multiple access (CDMA) system with Principal component analysis (PCA) in impulsive noise. The blind multiuser detector requires no training sequences compared with the conventional multiuser detection receiver. The proposed PCA blind multiuser detector is robust when compared with knowledge based signature waveforms and the timing of the user of interest. PCA is a statistical method for reducing the dimension of data set, spectral decomposition of the covariance matrix of the dataset i.e first and second order statistics are estimated. Principal component analysis makes no assumption on the independence of the data vectors PCA searches for linear combinations with the largest variances and when several linear combinations are needed, it considers variances in decreasing order of importance. PCA improves SNR of signals used for differential side channel analysis. In different to other approaches, the linear minimum mean-square-error (MMSE) detector is obtained blindly; the detector does not use any training sequence like in subspace methods to detect multi user receiver. The algorithm need not estimate the subspace rank in order to reduce the computational complexity. Simulation results show that the new algorithm offers substantial performance gains over the traditional subspace methods.

In the multicarrier code division multiple access (MC-CDMA) uplink, the base station receiver has the knowledge of the spreading sequences of all the users within the cell, but not that of the users from other cells. In this paper, we present a novel semi-blind adaptive MMSE multi-user detector based on subspace tracking for MC-CDMA systems in such scenarios. We develop an modified MMSE detector which can combat the performance deterioration induced by eigenvalues estimation errors. Moreover, the proposed method exploits the orthogonal projection approximation subspace tracking (OPAST) algorithm for adaptive subspace estimation. This proposed detector makes use of the spreading sequences of all known users to suppress the intracell interference, while suppresses the intercell interference using the modified MMSE detector. Simulation results demonstrate that the proposed semi-blind multi-user detector offers substantial performance gains over the blind multi-user detection and the traditional semi-blind method in a MC-CDMA uplink environment.

In this paper, we introduce a novel fuzzy adaptive algorithm for blind detection of direct sequence code division multiple access (DS-CDMA) signals in a multiuser communication scenario. We make use of fuzzy control systems to wisely determine the appropriate step size of the adaptive algorithm based on the quality of the received signal. We have used the popular minimum output energy (MOE) blind detector proposed by Honig et al. as our blind adaptive detector whose step size is to be determined by the fuzzy control system. This blind detector requires no more knowledge than does the conventional single-user receiver, i.e. the desired user's signature waveform and its timing. We have proposed to use signal to interference ratio (SIR) and its variations as the key inputs to our fuzzy algorithm. By simulation, we show the competency of our algorithm in terms of the convergence characteristics of the adaptive algorithm. Likewise, by simulation results we show that these convergence improvements yield to a lower bit error rate (BER) for the demodulation process in the receiver.

This paper is concerned with a new subspace tracking method by using an accelerated RLS algorithm for time-varying parameters, and its application to direction-of-arrival (DOA) estimation and blind multiuser detection (MUD) in the case that the spatial information of users rapidly changes. The proposed subspace tracker is derived by combining the projection approximation subspace tracking (PAST) with the internal model principle, approximately expressing the changing parameters with an expansion of polynomial time functions. It can still maintain the linear computational complexity to the number of users, similar to the PAST. The effectiveness is validated through some numerical simulations of DOA estimation in a narrowband source scenario and blind MUD in a synchronous DS-CDMA system, respectively

Orthogonal subspace projection (OSP) has been successfully applied to hyperspectral image processing. In order for OSP to be effective, the number of bands must be no less than that of signatures to be classified so that there are sufficient dimensions to accommodate individual signatures to discriminate one another via orthogonal projection. This intrinsic constraint is not an issue for hyperspectral images since they generally have hundreds of bands which are more than the number of signatures resident within images. It, however, may not be true for multispectral images where the number of signatures to be classified is greater than the number of bands such as 3-band SPOT images. This paper presents a generalization of OSP, called generalized OSP (GOSP) to relax this constraint in such a fashion that OSP can be extended to multispectral image processing in an unsupervised fashion. The idea of GOSP is to create new additional band images nonlinearly from original multispectral images so as to achieve sufficient dimensionality prior to OSP classification. It is then followed by an unsupervised OSP classifier, called automatic target detection and classification algorithm (ATDCA) for classification. The effectiveness of the proposed GOSP is evaluated by a 3-band SPOT and a 4-band Landsat MSS images. The experimental results has shown that GOSP significantly improves the classification performance of OSP.

The multicarrier code division multiple access (MC-CDMA) technique has received considerable interest for its potential application to future wireless communication systems due to its high data rate. A common problem regarding the blind multiuser detectors used in MC-CDMA systems is that they are extremely sensitive to the complex channel environment. Besides, the perturbation of colored noise may negatively affect the performance of the system. In this paper, a new coherent detection method will be proposed, which utilizes the modified fast independent component analysis (FastICA) algorithm, based on approximate negentropy maximization that is subject to the second-order cone programming (SOCP) constraint. The aim of the proposed coherent detection is to provide robustness against small-to-medium channel estimation mismatch (CEM) that may arise from channel frequency response estimation error in the MC-CDMA system, which is modulated by downlink binary phase-shift keying (BPSK) under colored noise. Noncoherent demodulation schemes are preferable to coherent demodulation schemes, as the latter are difficult to implement over time-varying fading channels. Differential phase-shift keying (DPSK) is therefore the natural choice for an alternative modulation scheme. Furthermore, the new blind differential SOCP-based ICA (SOCP-ICA) detection without channel estimation and compensation will be proposed to combat Doppler spread caused by time-varying fading channels in the DPSK-modulated MC-CDMA system under colored noise. In this paper, numerical simulations are used to illustrate the robustness of the proposed blind coherent SOCP-ICA detector against small-to-medium CEM and to emphasize the advantage of the blind differential SOCP-ICA detector in overcoming Doppler spread.

SUMMARYThis paper proposes affine‐projection blind multiuser detection with block length control for improvement of convergence speed in DS‐CDMA (direct sequence code division multiple access) systems in a multipath environment. The traditional method of controlling the block length is discussed for the situation in which the desired signal of the system is given. But due to the difficulty of the application of the above method to blind multiuser detection, some suitable improvements are performed in the proposed method. These give the proposed method advantages over the traditional detectors.