Adaptive Multiuser Research Articles

Adaptive transmitter optimization for blind and group-blind multiuser detection

The linear subspace-based blind and group-blind multiuser detectors recently developed represent a robust and efficient adaptive multiuser detection technique for code-division multiple-access (CDMA) systems. In this paper, we consider adaptive transmitter optimization strategies for CDMA systems operating in fading multipath environments in which these detectors are employed. We make use of more recent results on the analytical performance of these blind and group-blind receivers in the design and analysis of the transmitter optimization techniques. In particular, we develop a maximum-eigenvector-based method of optimizing spreading codes for given channel conditions and a utility-based power control algorithm for CDMA systems with blind or group-blind multiuser detection. We also design a receiver incorporating joint optimization of spreading codes and transmitter power by combining these algorithms in an iterative configuration. We will see that the utility-based power control algorithm allows us to efficiently set performance goals through utility functions for users in heterogeneous traffic environments and that spreading code optimization allows us to achieve these goals with lower transmit power. The signal processing algorithms presented here maintain the blind (or group-blind) nature of the receiver and are distributed, i.e., all power and spreading code adjustments can be made using only locally available information.

Prolog to: Burst-by-burst adaptive multiuser detection CDMA: a framework for existing and future wireless standards

Prolog to: Burst-by-burst adaptive multiuser detection CDMA: a framework for existing and future wireless standards

Adaptive Near-Optimal Multiuser Detection Using a Stochastic and Hysteretic Hopfield Net Receiver

This paper proposes a novel adaptive MUD algorithm for a wide variety (practically any kind) of interference limited systems, for example, code division multiple access (CDMA). The algorithm is based on recently developed neural network techniques and can perform near optimal detection in the case of unknown channel characteristics. The proposed algorithm consists of two main blocks: one estimates the symbols sent by the transmitters and the other identifies each channel of the corresponding communication links. The estimation of symbols is carried out either by a stochastic Hopfield net (SHN), by a hysteretic neural network (HyNN) or by both. The channel identification is based on either the self-organizing feature map (SOM) or the learning vector quantization (LVQ). The combination of these two blocks yields a powerful real-time detector with near optimal performance. The performance is analyzed by extensive simulations.

Detection-aided recursive least squares adaptive multiuser detection in DS/CDMA

This letter develops a sequential composite hypotheses test for detecting failure of a decision-directed recursive least square (RLS) adaptive multiuser detector (MUD) and convergence of a blind RLS (BLRS) MUD when used in the downlink of direct-sequence/code division multiple access (DS/CDMA) systems. Simulations are provided to demonstrate the effectiveness of the test and to characterize the SIR improvement achievable in a dynamic environment where the number of interferers is time-varying.

An adaptive asynchronous CDMA multiuser detector for frequency-selective Rayleigh fading channels

An adaptive asynchronous code-division multiple-access (CDMA) multiuser detector is proposed that uses a recently derived extended Kalman filter based algorithm (see Lim, T.J. and Rasmussen, L.K., IEEE Trans. Commun., vol.45, p.213-20, 1997) to perform joint data detection and parameter tracking in frequency-selective Rayleigh fading channels. A receiver structure based on this adaptive multiuser detector is presented and its performance in terms of parameter tracking and bit error rate (BER) is investigated. The receiver is a form of an adaptive RAKE that exploits multipaths to achieve performance gain.

A Non-Canonical Linearly Constrained Constant Modulus Algorithm for a Blind Multiuser Detector

We investigate an alternative blind adaptive multiuser detection scheme based on a non-canonical linearly constrained constant modulus (LCCM) criterion and prove that, under the constrained condition, the non-canonical linearly constrained constant modulus algorithm (LCCMA) can completely remove multiple-access interference. We further demonstrate that the non-canonical LCCM criterion function is strictly convex in the noise-free state, and that under the constrained condition, it is also strictly convex even where small noise is present. We present a simple method for selecting the constant as well as a stochastic gradient algorithm for implementing our scheme. Numerical simulation results verify the scheme's efficiency.

Blind adaptive multiuser detection based on Kalman filtering

Although several Kalman filtering algorithms have been presented for adaptive multiuser detection, none is due to requiring training data sequences and/or more knowledge than the spreading waveform and delay of the desired user. This paper proposes a novel blind adaptive multiuser detector based on Kalman filtering and compares it with previously published LMS and RLS algorithms for blind adaptive multiuser detection. It is shown that the steady-state excess output energy of the Kalman filtering algorithm is identically zero for a stationary environment. Simulation results show the effectiveness of the new Kalman filtering algorithm.

A hybrid interference cancellation scheme for blind multiuser detection in multipath fading channels

This paper introduces and analyzes a detection scheme for adaptive suppression of Multiuser Access Interference (MAI) and MultiPath Distortion (MPD) for mobile station of DS/CDMA system. The proposed detection scheme may amount to a RAKE receiver structure, wherein each branch is considered as a linear multiuser filter designed under a Linear Constrained Minimum Variance (LCMV) optimization strategy to suppress MAI, followed by a proper combining rule to suppress MPD. The adaptive blind multiuser detecting and optimum combining of the proposed receiver are realized, based on the Least-Mean-Square (LMS) algorithm and an adaptive vector tracking algorithm respectively. Finally, the feasibility of the above two algorithms is proved by the numerical results provided by computer simulation.

Blind adaptive multiuser detection for cellular systems using stochastic approximation with averaging

We consider blind adaptive multiuser detection in correlated waveform multiple-access-based cellular radio networks. A common stochastic approximation (SA)-based framework is proposed from which three blind adaptive algorithms for linear minimum mean squared error detection are obtained. Two of them coincide with previously proposed algorithms and the third is shown to be best suited for implementation at a base station. The work here also improves these SA-based adaptation algorithms in the context of cellular radio networks, in terms of the convergence properties by using the results on the SA technique with averaging. Convergence issues of the different adaptations are investigated and numerical examples are presented to demonstrate the performance improvement due to averaging.

Implementation of multiuser detection strategies for coherent underwater acoustic communication

This paper presents multiple access interference cancellation techniques based on joint implementation of spatial-beamforming and multiuser detection strategies for coherent underwater acoustic communication network. Performances of adaptive multiuser detection strategies based on weighted parallel, successive, and recursive successive interference cancellation techniques are compared using experimental sea-trial data. Results show that the receiver structure adopting weighted recursive successive interference cancellation (RSIC) exhibits robustness in extracting useful data for weak users in the presence of co-channel interference from strong users. In addition, this type of structure simultaneously suppresses the summed interference effects contributed by weaker users toward the strongest user. The RSIC structure is therefore a potential candidate for multiple access interference suppression in coherent shallow water acoustic communication systems.

Multiple Model Adaptive Estimation for Multiuser Detection in CDMA Communication

This paper introduces a blind adaptive multiuser detection scheme for code division multiple acces (CDMA) communication, based on the interacting multiple model algorithm. The system estimates the received power and input data sequence which are corrupted by multiple access interference (MAI) and noise. A hybrid system is used to model the synchronous code division multiple access, and multiuser detection is implemented using the interacting multiple model (IMM) technique. The performance of the IMM based multiuser detector is studied and simulations are used to compare with the decorrelating decision feedback detector (DDFD) and decision-feedback blind adaptive multiuser detector (DFBD).

Subspace-based multiuser detection for antenna array CDMA systems

In this paper, an adaptive multiuser detector based on signal subspace estimation is proposed for synchronous CDMA systems with an antenna array. Based on a training sequence transmitted by the desired user, we obtain a linear MMSE detector which does not require knowledge of the code sequences and the channel impulse response. The proposed spatial-temporal adaptive multiuser detection technique is shown to be robust against the near-far problem and computationally efficient by using subspace tracking algorithm.

Blind adaptive multiuser detection for DS/SSMA communications with generalized random spreading

A new spreading scheme and an accompanying blind adaptive receiver structure are proposed for direct-sequence spread-spectrum multiple-access communications in a slowly-varying, frequency-selective fading channel. Each user's spreading sequence is given by the Kronecker product of a long-period pseudonoise (PN) sequence, which is accurately modeled by a random sequence, and a short-length deterministic signature code. This spreading scheme bridges the gap between pure PN spreading and pure short-code spreading schemes. It is shown that with this spreading scheme, the channel response to the desired signal component is easily estimated without relying on the spectral decomposition of the signal correlation matrix. With the estimate of the channel response, the receiver suppresses interference based on the maximum signal-to-interference ratio criterion. The blind adaptive receiver requires only coarse timing information and a priori knowledge of the desired user's PN sequence for adaptation. Numerical results show that the adaptive receiver significantly suppresses interference by successfully estimating the channel response and the interference statistics with a low computational complexity. An extension to spatio-temporal processing using an array antenna is also discussed.

Optimal adaptive multiuser detection in unknown multipath channels

An optimal multiuser detector in the weighted least squares (WLS) sense is derived. This detector, which includes the maximum likelihood multiuser detector as a special case, consists of two parts: a bank of linear fractionally chip spaced minimum mean squared error (MMSE) filters, and a nonlinear WLS metric minimizer. It is shown that the symbol spaced samples at the output of the MMSE filter bank provide a set of sufficient statistics for WLS detection. The relationship between the taps of a centralized decision feedback detector and the MMSE filter bank is derived. It is proven that all the necessary parameters for implementing the WLS detector can be realized by adaptively training a centralized decision feedback detector. Therefore, the WLS detector achieves optimal joint synchronization and data detection even in the presence of colored noise, such as narrowband interference, without any a priori knowledge of the users' signatures, multipath channel taps or statistics of the colored noise. Significant features of the WLS detector are that: (1) the WLS detector is a generalization of the maximum likelihood multiuser detector that employs a bank of matched filters; (2) it is implemented adaptively; and (3) it has structural flexibility in terms of implementation complexity.

Support vector machine multiuser receiver for DS-CDMA signals in multipath channels

The problem of constructing an adaptive multiuser detector (MUD) is considered for direct sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. The emerging learning technique, called support vector machines (SVM), is proposed as a method of obtaining a nonlinear MUD from a relatively small training data block. Computer simulation is used to study this SVM MUD, and the results show that it can closely match the performance of the optimal Bayesian one-shot detector. Comparisons with an adaptive radial basis function (RBF) MUD trained by an unsupervised clustering algorithm are discussed.

Adaptive multiuser DFE with Kalman channel estimation for DS-CDMA systems in multipath fading channels

An adaptive multiuser decision-feedback equalizer (DFE) companioned with a Kalman channel estimation algorithm is presented for DS-CDMA systems in multipath fading channels. The Kalman channel estimation algorithm is employed to estimate the multipath fading channels, then the estimates are used to adjust the tap coefficients of the multiuser DFE via a minimum mean-square error design criterion. In this study, we present a novel state-space equation, which is different from the joint multiuser detection/channel estimation method (Wang and Poor, Wireless Networks 4(6) (1998) 453–470), for the multipath fading channel estimation of multiuser DS-CDMA systems. We take not only the estimates of channels but also the statistics of the channel estimation errors into consideration of the multiuser DFE design. We also derive the output signal-to-interference-and-noise ratio and the bit-error-rate for the multiuser detection, in which the influence of multiuser interference, channel estimation errors and channel noise is included. Finally, two fading channel models, i.e., the land-mobile model and the Butterworth model, are simulated to demonstrate our results. The sensitivity of the proposed method to the uncertainties of fading channel parameters is also presented in the simulations.

A modified constrained constant modulus approach to blind adaptive multiuser detection

An alternative blind adaptive multiuser detection is investigated based on modified constrained constant modulus (CM) criterion. It is shown that the performance of a CM-based receiver is limited by the received power of the desired user. In this paper, we show that the limitation can be avoided using the noncanonical constraint CM criterion and that in the presence of channel noise the modified CM criterion function is strictly convex by properly selecting some constant. With analyzing the extrema of the cost function, we point out how to select the constant. Moreover, a simple stochastic gradient algorithm for implementing our scheme is presented, and the convergence properties of the algorithm are analyzed. Simulation examples are given to demonstrate the performance of the proposed scheme.

Adaptive space-time feedforward/feedback detection for high data rate CDMA in frequency-selective fading

We investigate linear and nonlinear space-time minimum mean-square-error (MMSE) multiuser detectors for high data rate wireless code-division multiple-access (CDMA) networks. The centralized reverse-link detectors comprise a space-time feedforward filter and a multiuser feedback filter which processes the previously detected symbols of all in-sector users. The feedforward filter processes chip-rate samples from a bank of chip-matched filters which operate on the baseband outputs from an array of antennas. We present an adaptive multiuser recursive least squares (RLS) algorithm which determines the MMSE adjusted filter coefficients with less complexity than individual adaptation for each user. We calculate the outage probabilities and isolate the effects of antenna, diversity, and interference suppression gains for linear and nonlinear filtering and for CDMA systems with varying levels of system control (e.g., timing control, code assignment, cell layout). For eight users transmitting uncoded 2-Mb/s quadrature phase-shift keying with a spreading gain of eight chips per symbol over a fading channel with a multipath delay spread of 1.25 /spl mu/s, the performance of a three-antenna feedforward/feedback detector was within 1 dB (in signal-to-noise ratio per antenna) of ideal detection in the absence of interference. By training for 10% of a 5-ms frame, RLS adaptation enabled the same detector to suffer less than a 0.5-dB penalty due to the combined effects of imperfect coefficients and error propagation. The advantage of nonlinear feedforward/feedback detection over linear feedforward detection was shown to be significantly larger for a CDMA system with enhanced system control.

Adaptive recursive algorithm for complementary subspace-based blind multiuser detection

A novel blind adaptive multiuser detection scheme, the linear decorrelating detector (LDD), based on a concept of the complementary subspace is proposed. Under this scheme, the information bits can be estimated from the received signal with the prior knowledge of the desired user's signature waveform and its timing. The technique has two key elements: a geometric notion of the LDD and the subspace-based concept to estimate the orthogonal complement of the interfering space. It is then shown that the LDD can be formulated in terms of the interference space constructed from the received signal, and the desired user's signature waveform. The interference space components can be adaptively estimated using the modified power-based methods with only O((K-1) N) flops of computation at each iteration, where N is the processing gain, and K is the number of active users in the channel. The novel blind adaptive detector offers lower computational complexity. The proposed blind multiuser detection offers the optimal near-far resistance, low computational complexity, and resistance against the orthogonality error of the estimated interference space.

The constrained conjugate gradient algorithm

Based on the condition for equivalence between linearly constrained minimum-variance (LCMV) filters and their generalized sidelobe canceler (GSC) implementations, we derive the new constrained conjugate gradient (CCG) algorithm. We discuss the use of orthogonal and nonorthogonal blocking matrices for the GSC structure and how the choice of this matrix may affect the relationship with the LCMV counterpart. The newly derived algorithm was tested in a computer experiment for adaptive multiuser detection and showed excellent results.