Lars Kildehöj Rasmussen

Linear interference cancellation in CDMA based on iterative techniques for linear equation systems

It has previously been shown that well known iterations for solving a set of linear equations correspond to linear interference cancellation structures. Here, we suggest applying a block-wise iteration that consists of an outer and an inner iteration. The outer iteration used is the Gauss-Seidel (GS) method, while for the inner iteration, we study direct matrix inversion, the Jacobi over-relaxation iteration, and the conjugate gradient iteration. When a true inner iteration is used, this approach allows for a timely derivation of the acceleration parameters required by advanced iterations. The block iteration is based on a symbol-level implementation which leads to the same detection delay profile for both parallel and serial structures at the expense of differences in the amount of serial processing required. This is discussed in some detail and quantified for comparison. The performance of the detectors is studied via computer simulations where it is found that the block approach can provide significantly faster convergence, leading to improved detection delay over the simpler GS iteration. The improvements are obtained at the expense of an increase in the required serial processing speed.

Convergence analysis and optimal scheduling for multiple concatenated codes

An interesting practical consideration for decoding of serial or parallel concatenated codes with more than two components is the determination of the lowest complexity component decoder schedule which results in convergence. This correspondence presents an algorithm that finds such an optimal decoder schedule. A technique is also given for combining and projecting a series of three-dimensional extrinsic information transfer (EXIT) functions onto a single two-dimensional EXIT chart. This is a useful technique for visualizing the convergence threshold for multiple concatenated codes and provides a design tool for concatenated codes with more than two components.

A matrix-algebraic approach to successive interference cancellation in CDMA

In this paper, we describe linear successive interference cancellation (SIC) based on matrix-algebra. We show that linear SIC schemes (single stage and multistage) correspond to linear matrix filtering that can be performed directly on the received chip-matched filtered signal vector without explicitly performing the interference cancellation. This leads to an analytical expression for calculating the resulting bit-error rate which is of particular use for short code systems. Convergence issues are discussed, and the concept of /spl epsiv/-convergence is introduced to determine the number of stages required for practical convergence for both short and long codes.

A matrix-algebraic approach to linear parallel interference cancellation in CDMA

Linear parallel interference cancellation (PIC) schemes are described and analyzed using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the chip-matched filtered received signal vector. An expression for the exact bit-error rate (BER) is obtained, and conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence are derived. The close relationship between the linear multistage PIC and the steepest descent method (SDM) for minimizing the mean squared error (MSE) is demonstrated. A modified weighted PIC structure that resembles the SDM is suggested which approaches the minimum MSE (MMSE) detector rather than the decorrelator. It is shown that for a K-user system, only K PIC stages are required for the equivalent matrix filter to be identical to the the MMSE filter. For fewer stages, techniques are devised for optimizing the choice of weights with respect to the MSE. One unique optimal choice of weights is found, which will lead to the minimum achievable MSE at the final stage. Simulation results show that a few stages are sufficient for near-MMSE performance.

Asymptotic normality of linear multiuser receiver outputs

This paper proves large-system asymptotic normality of the output of a family of linear multiuser receivers that can be arbitrarily well approximated by polynomial receivers. This family of receivers encompasses the single-user matched filter, the decorrelator, the minimum mean square error (MMSE) receiver, the parallel interference cancelers, and many other linear receivers of interest. Both with and without the assumption of perfect power control, we show that the output decision statistic for each user converges to a Gaussian random variable in distribution as the number of users and the spreading factor both tend to infinity with their ratio fixed. Analysis reveals that the distribution conditioned on almost all spreading sequences converges to the same distribution, which is also the unconditional distribution. This normality principle allows the system performance, e.g., the multiuser efficiency, to be completely determined by the output signal-to-interference ratio (SIR) for large linear systems.

Near optimum tree-search detection schemes for bit-synchronous multiuser CDMA systems over Gaussian and two-path Rayleigh-fading channels

Simple reduced tree-search detection schemes of the breadth-first type are applied to suboptimal joint multiuser detection in bit-synchronous code-division multiple access (CDMA) systems over both Gaussian and two-path Rayleigh-fading channels. It is pointed out that in contrast to the case of the optimal multiuser detector, the choice of the receiver filter severely influences the performance of suboptimal multiuser detectors. Simulation results supported by analysis show that breadth-first tree-search algorithms using a decorrelating noise whitening receiver filter perform better than similar receivers, which solely use a matched filter (MF) for virtually all nonsingular spreading code sets studied. Most of the code sets are randomly generated. The M- and T-algorithm detectors based on decorrelating noise whitening filter (WF) outputs can achieve near optimum performance at a very low complexity compared to the optimal detector, although the proposed detectors are more complex than some known suboptimum detectors. Furthermore, the use of combining techniques is considered for a two-path Rayleigh-fading channel, and a semi-synchronous CDMA structure is proposed. It is shown that if maximum ratio combining (MRC) is employed, the decorrelating noise WF still exists. The corresponding suboptimal combining detector with a decorrelating noise WF outperforms a similar noncombining detector.

Linear parallel interference cancellation in long-code CDMA multiuser detection

Parallel interference cancellation (PIC) is a promising detection technique for code division multiple access (CDMA) systems. It has previously been shown that the weighted multistage PIC can be seen as an implementation of the steepest descent algorithm used to minimize the mean squared error (MSE). Following this interpretation, a unique set of weights, based on the eigenvalues of the correlation matrix, was found to lead to the minimum achievable MSE for a given number of stages in a short-code system. In this paper, we introduce a method for finding an appropriate set of time-invariant weights for systems using long codes. The weights are dependent on moments of the eigenvalues of the correlation matrix, exact expressions of which can be derived. This set of weights is optimal in the sense that it minimizes the ensemble averaged MSE over all code-sets. The loss incurred by averaging rather than using the optimal, time-varying weights is practically negligible, since the eigenvalues of sample correlation matrices are tightly clustered in most cases of interest. The complexity required for computing the weights increases linearly with the number of users but is independent of the processing gain, hence on-line weight updating is possible in a dynamic system. Simulation results show that a few stages is usually sufficient for near-MMSE performance.

Constrained maximum-likelihood detection in CDMA

The detection strategy usually denoted optimal multiuser detection is equivalent to the solution of a (0, 1)-constrained maximum-likelihood (ML) problem, a problem which is known to be NP-hard. In contrast, the unconstrained ML problem can be solved quite easily and is known as the decorrelating detector. In this paper, we consider the constrained ML problem where the solution vector is restricted to lie within a closed convex set (CCS). Such a design criterion leads to detector structures which are ML under the constraint assumption. A close relationship between a sphere-constrained ML detector and the well-known minimum mean square error detector is found and verified. An iterative algorithm for solving a CCS constraint problem is derived based on results in linear variational inequality theory. Special cases of this algorithm, subject to a box-constraint, are found to correspond to known, nonlinear successive and parallel interference cancellation structures, using a clipped soft decision for making tentative decisions, while a weighted linear parallel interference canceler with signal-dependent weights arises from the sphere constraint. Convergence issues are investigated and an efficient implementation is suggested. The bit-error rate performance is studied via computer simulations and the expected performance improvements over unconstrained ML are verified.

Multiuser detection in CDMA - a comparison of relaxations, exact, and heuristic search methods

In this paper, we compare several optimization methods for solving the optimal multiuser detection problem exactly or approximately. The purpose of using these algorithms is to provide complexity constraint alternatives to solving this nondeterministic polynomial-time (NP)-hard problem. An approximate solution is found either by relaxation or by heuristic search methods, while the branch and bound algorithm is used to provide an exact solution. Simulations show that these approaches can have bit-error rate (BER) performance which is indistinguishable from the maximum likelihood performance. A tabu search method is shown to be an effective (in terms of BER performance) and efficient (in terms of computational complexity) heuristic when compared to other heuristics like local search and iterative local search algorithms. When the number of users increases, the tabu search method is more effective and efficient than the semidefinite relaxation approach.

Adaptive symbol and parameter estimation in asynchronous multiuser CDMA detectors

Existing multiuser code-division multiple-access (CDMA) detectors either have to rely on strict power control or near-perfect parameter estimation for reliable operation. A novel adaptive multiuser CDMA detector structure is introduced. Using either an extended Kalman filter (EKF) or a recursive least squares (RLS) formulation, adaptive algorithms which jointly estimate the transmitted bits of each user and individual amplitudes and time delays may be derived. The proposed detectors work in a tracking mode after initial delay acquisition is accomplished using other techniques not discussed here. Through computer simulations, we show that the algorithms perform better than a bank of single-user (SU) receivers in terms of near-far resistance. Practical issues such as the selection of adaptation parameters are also discussed.