Adaptive Bayesian multiuser detection for synchronous CDMA withGaussian and impulsive noise

We consider the problem of simultaneous parameter estimation and data restoration in a synchronous CDMA system in the presence of either additive Gaussian or additive impulsive white noise with unknown parameters. The impulsive noise is modeled by a two-term Gaussian mixture distribution. Bayesian inference of all unknown quantities is made from the superimposed and noisy received signals. The Gibbs sampler (a Markov chain Monte Carlo procedure) is employed to calculate the Bayesian estimates. The basic idea is to generate ergodic random samples from the joint posterior distribution of all unknown and then to average the appropriate samples to obtain the estimates of the unknown quantities. Adaptive Bayesian multiuser detectors based on the Gibbs sampler are derived for both the Gaussian noise synchronous CDMA channel and the impulsive noise synchronous CDMA channel. A salient feature of the proposed adaptive Bayesian multiuser detectors is that they can incorporate the a priori symbol probabilities, and they produce as output the a posteriori symbol probabilities. (That is, they are “soft-input soft-output” algorithms.) Hence, these methods are well suited for iterative processing in a coded system, which allows the adaptive Bayesian multiuser detector to refine its processing based on the information from the decoding stage, and vice versa-a receiver structure termed the adaptive turbo multiuser detector     

Iterative (turbo) soft interference cancellation and decoding forcoded CDMA

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached     

Iterative Group-Blind Multiuser Detection and Decoding With Signal Rank Estimation for Coded CDMA Systems

In this paper, a turbo receiver structure is proposed for the uplink of coded code-division multiple-access (CDMA) systems in the presence of unknown users. The proposed receiver consists of two stages following each other. The first stage performs soft interference cancellation and group-blind linear minimum mean square error (MMSE) filtering, and the second stage performs channel decoding. The proposed group-blind linear MMSE filter suppresses the residual multiple-access interference (MAI) from known users based on the spreading sequences and the channel characteristics of these users while suppressing the interference from other unknown users using a subspace-based blind method. The proposed receiver is suitable for suppressing intercell interference in heavily loaded CDMA systems. Since the knowledge of the number of unknown users is crucial for the proposed receiver structure, a novel estimator is also proposed to estimate the number of unknown users in the system by exploiting the statistical properties of the received signal. Simulation results demonstrate that the proposed estimator can provide the number of unknown users with high accuracy; in addition, the proposed group-blind receiver integrated with the new estimator can significantly outperform the conventional turbo multiuser detector in the presence of unknown users.      

Bayesian Monte Carlo multiuser receiver for space-time codedmulticarrier CDMA systems

We consider the design of optimal multiuser receivers for space-time block coded (STBC) multicarrier code-division multiple-access (MC-CDMA) systems in unknown frequency-selective fading channels. Under a Bayesian framework, the proposed multiuser receiver is based on the Gibbs sampler, a Markov chain Monte Carlo (MCMC) method for numerically computing the marginal a posteriori probabilities of different users' data symbols. By exploiting the orthogonality property of the STBC and the multicarrier modulation, the computational complexity of the receiver is significantly reduced. Furthermore, being a soft-input soft-output algorithm, the Bayesian Monte Carlo multiuser detector is capable of exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel code decoders of all users, and successively improving the overall receiver performance. Several practical issues, such as testing the convergence of the Gibbs sampler in fading channel applications, resolving the phase ambiguity as well as the antenna ambiguity, and adapting the proposed receiver to multirate MC-CDMA systems, are also discussed. Finally, the performance of the Bayesian Monte Carlo multiuser receiver is demonstrated through computer simulations     

Iterative multiuser detection for turbo-coded synchronous CDMA inGaussian and non-Gaussian impulsive noise

We develop an iterative multiuser receiver for decoding turbo-coded synchronous code-division multiple-access signals in both Gaussian and non-Gaussian noise. A soft-input soft-output nonlinear multiuser detector is combined with a set of single-user channel decoders in an iterative detection/decoding structure. The nonlinear multiuser detector utilizes the prior probabilities of each user's bits to form soft estimates used for multiple-access interference cancellation. The channel decoders perform turbo-code decoding and produce posterior probabilities which are fed back to the multiuser detector for use as prior probabilities. Simulation results show that the proposed multiuser receiver performs well in both Gaussian and non-Gaussian noise. In particular, single-user turbo-code performance can be approached within a few iterations with medium to low cross correlation (ρ⩽0.5)     

A sequential Monte Carlo blind receiver for OFDM systems infrequency-selective fading channels

We consider the application of the sequential Monte Carlo (SMC) methodology to the problem of blind symbol detection in a wireless orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective fading channel. Bayesian inference of the unknown data symbols in the presence of an unknown multipath fading channel is made only from the observations over one OFDM symbol duration. A novel blind SMC detector built on the techniques of importance sampling and resampling is developed for differentially encoded OFDM systems. The performance of different schemes of delayed-weight estimation methods is studied. Furthermore, being soft-input and soft-output in nature, the proposed SMC detector is employed as the first-stage demodulator in a turbo receiver for a coded OFDM system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations     

Turbo编码DS/CDMA系统中的迭代多用户接收器

本文提出了一种用于Turbo编码DS/CDMA系统的迭代多用户接收器。该接收器由一个软输入/软输出（SISO）的多用户检测器和一组单用户SISO信道译码器组成。每次迭代过程中，多用户检测器和信道译码器都输出信息作为下一代迭代的先验信息，仿真结果表明，这种接收器的比特误码性能接近Turbo编码系统的单用户限。     

Iterative multiuser detection for asynchronous CDMA withconcatenated convolutional coding

We propose iterative multiuser detectors for asynchronous code-division multiple-access with parallel-concatenated convolutional codes (turbo codes) and with serially concatenated convolutional codes (SCCC). At each iteration we update and exchange the extrinsic information from the multiuser detector and channel decoders and regenerate soft information between constituent convolutional decoders. Simulation results show that with the proposed structure, near-single-user performance can be achieved. We also propose two reduced-complexity techniques, i.e., the reduced-state iterative multiuser detector based on the T-MAP algorithm and the iterative interference canceler based on a noise-whitening filter. Simulation results show a small performance degradation for these two techniques, particularly for the T-MAP receiver     

AMOUR-generalized multicarrier transceivers for blind CDMAregardless of multipath

Suppression of multiuser interference (MUI) and mitigation of multipath effects constitute major challenges in the design of third-generation wireless mobile systems. Most wide-band and multicarrier uplink code-division multiple-access (CDMA) schemes suppress MUI statistically in the presence of unknown multipath. For fading resistance, they all rely on transmit- or receive-diversity and multichannel equalization based on bandwidth-consuming training sequences or self-recovering techniques at the receiver end. Either way, they impose restrictive and difficult to check conditions on the finite-impulse response channel nulls. Relying on block-symbol spreading, we design a mutually-orthogonal usercode-receiver (AMOUR) system for quasi-synchronous blind CDMA that eliminates MUI deterministically and mitigates fading regardless of the unknown multipath and the adopted signal constellation. AMOUR converts a multiuser CDMA system into parallel single-user systems regardless of multipath and guarantees identifiability of users' symbols without restrictive conditions on channel nulls in both blind and nonblind setups. An alternative AMOUR design called Vandermonde-Lagrange AMOUR is derived to add flexibility in the code assignment procedure. Analytic evaluation and preliminary simulations reveal the generality, flexibility, and superior performance of AMOUR over competing alternatives     

Blind equalization and multiuser detection in dispersive CDMAchannels

The problem of blind demodulation of multiuser information symbols in a high-rate code-division multiple-access (CDMA) network in the presence of both multiple-access interference (MAI) and intersymbol interference (ISI) is considered. The dispersive CDMA channel is first cast into a multiple-input multiple-output (MIMO) signal model framework. By applying the theory of blind MIMO channel identification and equalization, it is then shown that under certain conditions the multiuser information symbols can be recovered without any prior knowledge of the channel or the users' signature waveforms (including the desired user's signature waveform), although the algorithmic complexity of such an approach is prohibitively high. However, in practice, the signature waveform of the user of interest is always available at the receiver. It is shown that by incorporating this knowledge, the impulse response of each user's dispersive channel can be identified using a subspace method. It is further shown that based on the identified signal subspace parameters and the channel response, two linear detectors that are capable of suppressing both MAI and ISI, i.e., a zero-forcing detector and a minimum-mean-square-error (MMSE) detector, can be constructed in closed form, at almost no extra computational cost. Data detection can then be furnished by applying these linear detectors (obtained blindly) to the received signal. The major contribution of this paper is the development of these subspace-based blind techniques for joint suppression of MAI and ISI in the dispersive CDMA channels     

Turbo multiuser detection with unknown interferers

We consider the problem of turbo multiuser detection for synchronous and asynchronous code-division multiple-access (CDMA) in the presence of unknown users. Turbo multiuser detectors, as previously developed, typically require knowledge of the signature waveforms of all of the users in the system and ignore users whose signature sequences are unknown, e.g., users outside the cell. We develop turbo multiuser detection for CDMA uplink systems and other environments in which the receiver has knowledge of the signature waveforms of only K˘⩽ K users. Subspace techniques are used to estimate the interference from the unknown-users and the interference estimate is subtracted from the received signal. We see that the new receiver significantly outperforms the conventional turbo multiuser receiver for moderate and high signal-to-noise ratios. It is also seen that the traditional turbo receiver provides little gain through iteration when unknown users are present     

Iterative Equalization using Improved Block DFE for Synchronous CDMA Systems

Iterative equalization using optimal multiuser detector and optimal channel decoder in coded CDMA systems improves the bit error rate (BER) performance tremendously. However, given large number of users employed in the system over multipath channels causing significant multiple-access interference (MAI) and intersymbol interference (ISI), the optimal multiuser detector is thus prohibitively complex. Therefore, the sub-optimal detectors such as low-complexity linear and non-linear equalizers have to be considered. In this paper, a novel low-complexity block decision feedback equalizer (DFE) is proposed for the synchronous CDMA system. Based on the conventional block DFE, the new method is developed by computing the reliable extrinsic log-likelihood ratio (LLR) using two consecutive received samples rather than one received sample in the literature. At each iteration, the estimated symbols by the equalizer is then saved as a priori information for next iteration. Simulation results demonstrate that the proposed low-complexity block DFE algorithm offers good performance gain over the conventional block DFE.     

Blind turbo equalization in Gaussian and impulsive noise

We consider the problem of simultaneous parameter estimation and restoration of finite-alphabet symbols that are blurred by an unknown linear intersymbol interference (ISI) channel and contaminated by additive Gaussian or non-Gaussian white noise with unknown parameters. Non-Gaussian noise is found in many wireless channels due to the impulsive phenomena of radio-frequency interference. Bayesian inference of all unknown quantities is made from the blurred and noisy observations. The Gibbs sampler, a Markov chain Monte Carlo procedure, is employed to calculate the Bayesian estimates. The basic idea is to generate ergodic random samples from the joint posterior distribution of all unknowns and then to average the appropriate samples to obtain the estimates of the unknown quantities. Blind Bayesian equalizers based on the Gibbs sampler are derived for both Gaussian ISI channel and impulsive ISI channel. A salient feature of the proposed blind Bayesian equalizers is that they can incorporate the a priori symbol probabilities, and they produce as output the a posteriori symbol probabilities. (That is, they are “soft-input soft-output” algorithms.) Hence, these methods are well suited for iterative processing in a coded system, which allows the blind Bayesian equalizer to refine its processing based on the information from the decoding stage and vice versa-a receiver structure termed as blind turbo equalizer     

Multiuser detection in asynchronous CDMA frequency-selective fading channels

Multipath fading severely limits the performances of conventional code division multiple-access (CDMA) systems. Since every signal passes through an independent frequency-selective fading channel, even modest cross-correlations among signature sequences may induce severe near-far effects in a central multiuser receiver. This paper presents a systematic approach to the detection problem in CDMA frequency-selective fading channels and proposes a low complexity linear multiuser receiver, which eliminates fading induced near-far problem.We initially analyze an optimal multiuser detector, consisting of a bank of RAKE filters followed by a dynamic programming algorithm and evaluate its performance through error probability bounds. The concepts of error sequence decomposition and asymptotic multiuser efficiency, used to characterize the optimal receiver performance, are extended to multipath fading channels.The complexity of the optimal detector motivates the work on a near-far resistant, low complexity decorrelating multiuser detector, which exploits multipath diversity by using a multipath decorrelating filter followed by maximal-ratio combining. Analytic expressions for error probability and asymptotic multiuser efficiency of the suboptimal receiver are derived that include the effects of multipath fading, multiple-access interference and signature sequences correlation on the receiver's performance.The results indicate that multiuser detectors not only alleviate the near-far problem but approach single-user RAKE performance, while preserving the multipath diversity gain. In interference-limited scenarios multiuser receivers significantly outperform the RAKE receiver.This paper was presented in part at the Twenty-Sixth Annual Conference on Information Sciences and Systems, Princeton, NJ, March 1992 and MILCOM'92, San Diego, CA, October 1992. This work was performed while author was with the Department of Electrical and Computer Engineering, Northeastern University, Boston, USA.     

Directly estimated adaptive detectors for code-division multiple-access signals

This paper presents adaptive multiuser detectors for code-division multiple-access (CDMA) signals in wireless communication systems. Directly estimated adaptive (DEA) detectors are developed by formulating CDMA detection as an inverse problem in the presence of channel-induced interference and noise. The detector parameters are computed by a fully sequential adaptive algorithm that requires no matrix inversion, and can be implemented online as the data arrive at the receiver. The proposed DEA detector is experimentally evaluated in terms of its robustness to noise, resistance to the near-far problem, and ability to handle multipath fading signals. This experimental study indicates that the proposed DEA detector requires shorter training sequences of bits to achieve the performance levels attained by existing adaptive implementations of the minimum mean-square error detector.     

Decision-feedback soft-input/soft-output multiuser detector foriterative decoding of coded CDMA

The optimal decoding scheme for a code-division multiple-access (CDMA) system that employs convolutional codes results in a prohibitive computational complexity. To reduce the computational complexity, an iterative receiver structure was proposed for decoding multiuser data in a convolutional coded CDMA system. At each iteration, extrinsic information is exchanged between a soft-input/soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders. However, a direct implementation of the full-complexity SISO multiuser detector also has the exponential computational complexity in terms of the number of users. This paper proposes a low-complexity SISO multiuser detector based on tentative hard decisions that are made and fed back from the channel decoders in the previous iteration. The computational complexity of the proposed detector is linear in terms of the number of users and can be adjusted according to the complexity/performance tradeoff. Simulation results show that even with this simple feedback scheme, the performance of the coded multiuser system approaches that of the single-user system for moderate to high signal-to-noise ratios (SNRs)     

Subspace methods for blind joint channel estimation and multiuser detection in CDMA systems

Recently developed subspace techniques for blind adaptive multiuser detection are briefly reviewed first. In particular, blind methods based on signal subspace tracking for adapting linear multiuser detectors in AWGN CDMA channels are considered, as well as extensions of these techniques to frequency selective fading channels, dispersive channels, and antenna array spatial processing. In addition, subspace‐based nonlinear adaptive techniques for robust blind multiuser detection in non‐Gaussian ambient noise channels are also described. Several new techniques are then developed within the subspace framework for blind joint channel estimation and multiuser detection, under some specific channel conditions. These include (1) an adaptive receiver structure for joint multiuser detection and equalization in dispersive CDMA channels, (2) a subspace method for joint multiuser detection and equalization in unknown correlated noise, and (3) a method for joint interference suppression and channel tracking in time‐varying fading channels. This revised version was published online in August 2006 with corrections to the Cover Date.     

Group-blind intersymbol multiuser detection for downlink CDMA with multipath

Group-blind multiuser detectors for uplink code-division multiple-access (CDMA) were recently developed by Wang and Host-Madsen. These detectors make use of the spreading sequences of known users to construct a group constraint to suppress the intracell interference. However, such techniques demand the estimation of the multipath channels and the delays of the known users. In this paper, several improved blind linear detectors are developed for CDMA in fading multipath channels. The proposed detectors utilize the correlation information between consecutively received signals to generate the corresponding group constraint. It is shown that by incorporating this group constraint, the proposed detectors can provide different performance gains in both uplink and downlink environments. Compared with the previously reported group-blind detectors, our new methods only need to estimate the multipath channel of the desired user and do not require the channel estimation of other users. Simulation results demonstrate that the proposed detectors outperform the conventional blind linear multiuser detectors.     

A generalized RAKE receiver for interference suppression

Currently, a global third-generation cellular system based on code-division multiple-access (CDMA) is being developed with a wider bandwidth than existing second-generation systems. The wider bandwidth provides increased multipath resolution in a time-dispersive channel, leading to higher frequency-selectivity. A generalized RAKE receiver for interference suppression and multipath mitigation is proposed. The receiver exploits the fact that time dispersion significantly distorts the interference spectrum from each base station in the downlink of a wideband CDMA system. Compared to the conventional RAKE receiver, this generalized RAKE receiver may have more fingers and different combining weights. The weights are derived from a maximum likelihood formulation, modeling the intracell interference as colored Gaussian noise. This low-complexity detector is especially useful for systems with orthogonal downlink spreading codes, as orthogonality between own cell signals cannot be maintained in a frequency-selective channel. The performance of the proposed receiver is quantified via analysis and simulation for different dispersive channels, including Rayleigh fading channels. Gains on the order of 1-3.5 dB are achieved, depending on the dispersiveness of the channel, with only a modest increase in the number of fingers. For a wideband CDMA (WCDMA) system and a realistic mobile radio channel, this translates to capacity gains of the order of 100%     

A maximum likelihood approach to blind multiuser interferencecancellation

This paper addresses the problem of blind multiple access interference (MAI) and intersymbol interference (ISI) suppression in direct sequence code division multiple access (DS CDMA) systems. A novel approach to obtain the coefficients of a linear receiver using the maximum likelihood (ML) principle is proposed. The method is blind because it only exploits the statistical features of the transmitted symbols and Gaussian noise in the channel. We demonstrate that an adequate linear constraint on these coefficients ensures that the desired user is extracted and the resulting linearly constrained maximum likelihood linear (LCMLL) receiver can be efficiently implemented using the iterative space alternating generalized expectation-maximization (SAGE) algorithm. In order to take advantage of the diversity inherent to multipath channels, we also introduce a blind RAKE multiuser receiver that proceeds in two steps. First, soft estimates of the desired user transmitted symbols are obtained from each propagation path using a bank of appropriate LCMLL receivers. Afterwards, these estimates are adequately combined to enhance the signal-to-interference-and-noise ratio (SINR). Computer simulations show that the proposed blind algorithms for multiuser detection are near-far resistant and attain convergence using small blocks of data, thus outperforming existing linearly constrained minimum variance (LCMV) blind receivers