Direct-sequence Code-division Multiple-access Channels Research Articles

Tracking of dispersive DS-CDMA channels: an AR-embedded modified interacting multiple-model approach

In this paper, we consider the channel tracking problem for a direct-sequence code division multiple-access (DS-CDMA) communication under Gaussian noise. This problem is important in the design of a receiver over multipath time-varying fading channels. The main contribution of this paper is two-fold. The first one is a multiple-model framework for modeling the channel, composed of a set of known first- and second-order auto-regressive models (AR(i), i = 1,2) with the transitions between models obeying a Markov chain. Each AR model assumes a velocity sub-range of mobile users, and the set covers the range of possible dynamics of the time-varying fading channel. The second contribution is the adaptation of the known interacting multiple-model (EMM) estimation algorithm for channel tracking based on the above modeling framework. This tracking solution in combination with Kalman-based symbol detector leads to a feasible receiver architecture for attaining satisfactory performance

Reduced complexity joint iterative equalization and multiuser detection in dispersive DS-CDMA channels

Communication through dispersive direct-sequence code-division multiple-access channels suffers from intersymbol and multiple-access interference, which can significantly impair performance. Joint maximum a posteriori probability equalization and multiuser detection with error control decoding can be used to mitigate this interference and to achieve the optimal bit-error rate. Unfortunately, such optimal detection typically requires prohibitive computational complexity. This problem is addressed in this paper through the development of a reduced state trellis search detection algorithm, based on decision feedback from channel decoders. The performance of this algorithm is analyzed in the large-system limit. This analysis and simulations show that this reduced complexity algorithm can exhibit near-optimal performance under moderate signal-to-noise ratio and attains larger system load capacity than parallel interference cancellation.

Scalable Video Transmission Over Wireless DS-CDMA Channels Using Minimum TSC Spreading Codes

In this letter, we report results on the relative performance of scalable video transmission via a single-rate or a multirate direct sequence code-division multiple-access channel using minimum total squared correlation spreading codes. Our findings demonstrate the superiority of the multirate system on a wide range of chip rates of practical interest.

Minimum Probability of Error-Based Methods for Adaptive Multiuser Detection in Multipath DS-CDMA Channels

Direct-sequence code-division multiple-access (DS-CDMA) is a popular multiple-access technology for wireless communications. However, its performance is limited by multiple-access interference and multipath distortion. Multiuser detection and space-time processing are two signal processing techniques employed to improve the performance of DS-CDMA. Two minimum probability of error-based space-time multiuser detection algorithms are proposed in this paper. The first algorithm, minimum joint probability of error (MJPOE), aims to minimize the joint probability of error for all users. The second algorithm, minimum conditional probability of error (MCPOE), minimizes the probability of error of each user conditioned on the transmitted bit vector, for each user individually. In both the algorithms, the optimal filter weights are computed adaptively using a gradient descent approach. The MJPOE algorithm is blind and offers a bit-error-rate (BER) performance better than the nonadaptive minimum mean squared error (MMSE) algorithm, at the cost of higher computational complexity. An approach for reducing the computational overheads of MJPOE using Gram-Schmidt orthogonalization is suggested. The BER performance of the MCPOE algorithm is slightly inferior to MMSE, however, it has a computational complexity linear in the number of users. Both blind and training-based implementations for MCPOE are proposed. Both MJPOE and MCPOE have a convergence rate much faster than earlier known adaptive implementations of the MMSE detector, viz. least mean square and recursive least squares. Simulation results are presented for synchronous single path channels as well as asynchronous multipath channels, with multiple antennas employed at the receiver.

A sequential monte carlo filter for joint linear/nonlinear state estimation with application to DS-CDMA

A sequential Monte Carlo filter is considered which combines previously developed sequential importance sampling (SIS) techniques for conditional linear Gaussian models with measurement linearization for construction of approximate simulation densities. The resulting sequential Monte Carlo Kalman filter (SMC-KF) consists of a bank of conventional Kalman filters individually tuned to sampled trajectories of the nonlinear state variables. Sampling is according to a Gaussian distribution, with mean and covariance determined by extended Kalman filter-type equations. The SMC-KF is then applied to joint delay and multipath channel estimation in direct-sequence code-division multiple access (DS-CDMA). A combined analytical/simulation technique is employed to compare performance of the SMC-KF and a previously derived extended Kalman filter (EKF)-based DS-CDMA channel estimator.

Advanced ICA-based receivers for block fading DS-CDMA channels

In this paper we propose two types of receivers, which perform blind interference suppression. The receivers are suitable for the third generation mobile communications systems, which are based on direct-sequence code division multiple access (DS-CDMA). We especially consider the statistical technique called independent component analysis (ICA) as a tuning element attached to an existing single-user or blind multiuser detector. By doing this, the statistical independence of the users’ signals can be exploited. In addition, it makes it possible to alleviate the performance drop due to the erroneous parameters estimation in the receiver. From the ICA point of view, the receiver observes a mixture of users’ original signals, determined by the user-specific spreading codes, the data symbols, and the state of the propagation channel. Since all of them might be complex valued by nature, complex ICA is needed. In the paper, a proof of global convergence is given for the kurtosis-based FastICA algorithm in the case of complex valued source signals with circular distribution, and considered as the ICA component of the advanced receivers. Two types of receivers, RAKE-ICA and MMSE-ICA, are proposed and studied in a Rayleigh block fading channel. Extensive numerical simulations indicate that the performance of RAKE and subspace MMSE detector, respectively, can be greatly improved. Quite significantly, their performance is close to the theoretical bound of an equal length MMSE detector.

A statistical analysis of random polyphase signature sequences in multipath fading DS-CDMA channels

Direct sequence code division multiple access (DS-CDMA) communication systems using random polyphase sequences with coherent reception in multipath fading channels are considered. By examining the asymptotic characteristics of the multiple access interference and multipath interference, we show that the DS-CDMA system performance with random m p -phase sequences of m p ⩾3 is better than that with random binary sequences in multipath fading environment.

An improved blind adaptive MMSE receiver for fast fading DS-CDMA channels

Blind adaptive minimum mean-squared errors (MMSE) receivers for multiuser direct-sequence code-division multiple access (DS-CDMA) systems that assume knowledge of the steering vector, i.e., the cross-correlation between the desired output and the input signal, are known for their robustness against channel fading as they do not attempt to explicitly track the channel of the user of interest. However, these receivers often have higher excess mean squared error and, hence, poorer performance than training-sequence based adaptive MMSE receivers. In this paper, an improved correlation matrix estimation scheme for blind adaptive MMSE receivers is provided. The new scheme takes advantage of the fact that the desired linear receiver can be expressed as a function of the interference correlation matrix only, rather than the total data correlation matrix. A theoretical analysis is performed for the flat fading case which predicts that the new estimation scheme will result in significant performance improvement. Blind adaptive MMSE receivers with the new estimation scheme appear to achieve performance comparable to the training-sequence based adaptive MMSE receivers. Detailed computer simulations for the fast multipath fading environment verify that the proposed scheme yields strong performance gains over previous methods.

Joint Iterative Multiuser and Narrowband Interference Suppression inCoded Asynchronous DS-CDMA Channels

Multiuser interference suppression in coded direct sequence code division multiple access (DS-CDMA) uplink channels is significantly impacted by the application of the turbo processing concept. This paradigm essentially involves the iterative exchange of soft information between a multiuser demodulator and a bank of single-user decoders, to their mutual benefit. The present work proposes a joint iterative minimum mean square error (MMSE) multiuser and narrowband interference suppressor for coded asynchronous DS-CDMA channels. Since the parameters of the narrowband interference are unknown a priori, the first iteration in this scheme is effectively just MMSE multiuser interference suppression. The outputs of all users' soft decoders (available at the end of each iteration) are fed back to subtract their (estimated) cumulative contribution from the received signal vector. The residue comprises the narrowband interference embedded in wideband noise, so that the former can be piecewise interpolated over chip intervals of appropriate duration, and then subtracted from the received signal, to provide a narrowband-interference-free input signal for the next iteration. The soft-decoded feedback estimates of the interferers' signals are used in each iteration also to perform soft MMSE multiuser interference suppression, in conjunction with subtractive interference cancellation. This scheme performs well at both low and high received signal powers, and displays the successive cancellation property across iterations, exhibiting good near-far resistance. Introducing multisensor arrays at the receiver relaxes the limitations imposed by the inherent suboptimality of MMSE multiuser demodulation, insofar as it enhances interuser separation, now in the spatial sense. Simulations indicate that the performance of the proposed technique surpasses that of all existing suboptimal algorithms in this context.

Decision feedback sequence estimation for unwhitened ISI channels with applications to multiuser detection

Decision feedback sequence estimation (DFSE), which is a reduced-complexity alternative to maximum likelihood sequence estimation (MLSE), can be used effectively for equalization of intersymbol interference (ISI) as well as for multiuser detection. The algorithm performs very well for whitened (minimum-phase) channels. For nonminimum-phase channels, however, the algorithm is not very effective. Moreover, DFSE requires a noise-whitening filter, which may not be feasible to compute for time-varying channels such as a multiuser direct-sequence code division multiple access (DS-CDMA) channel. Noise-whitening is also cumbersome for applications that involve bidirectional equalization such as the global system for mobile communication (GSM) system. In such conditions, it is desirable to use the Ungerboeck (1974) formulation for sequence estimation, which operates directly on the discrete-time unwhitened statistic obtained from conventional matched filtering. Unfortunately, DFSE based on matched filter statistics is severely limited by untreated interference components. We identify the anticausal interference components, using an error probability analysis. This leads us to a modified unwhitened decision feedback sequence estimator (MUDFSE) in which the components are canceled, using tentative decisions. We obtain approximate error probability bounds for the proposed algorithm. Performance results indicate that the modified algorithm, used on unwhitened channels with relatively small channel correlations, provides similar performance/complexity tradeoffs as the DFSE used on the corresponding whitened minimum-phase channels. The algorithm is especially attractive for multiuser detection for asynchronous DS-CDMA channels with long spreading codes, where it can achieve near-MLSE performance with exponentially lower complexity.

Multistage linear receivers for DS-CDMA systems

A new family of multistage low-complexity linear receivers for direct sequence code division multiple access (DS-CDMA) communications is introduced. The objective of the proposed design is to mitigate the effect of multiple access interference (MAI), the most significant limiting factor of user capacity in the conventional DS-CDMA channel. The receivers presented here employ joint detection of multiple users and therefore require knowledge of all the signature codes and their timing. In addition, for a multipath environment, reliable estimates of the received powers and phases are assumed available for maximal ratio RAKE combining. Each stage of the underlying design recreates the overall modulation, noiseless channel, and demodulation process. The outputs of these stages are then linearly combined. The combining weights can be chosen to implement different linear detectors, including the decorrelating and minimum mean square error (MMSE) detectors. In this paper, we focus on implementing the MMSE detector. Simulation results illustrate that significant performance gains can be achieved in both synchronous and asynchronous systems.