Decorrelating decision-feedback multiuser detector for synchronouscode-division multiple-access channel

A decorrelating decision-feedback detector (DF) for synchronous code-division multiple-access (CDMA) that uses decisions of the stronger users when forming decisions for the weaker ones is described. The complexity of the DF is linear in the number of users, and it requires only one decision per user. It is shown that performance gains with respect to the linear decorrelating detector are more significant for relatively weak users and that the error probability of the weakest user approaches the single-user bound as interferers grow stronger. The error rate of the DF is compared to those of the decorrelator and the two-stage detector     

CDMA移动通信系统中的分组并行多用户信号检测器

该文提出了一种新的分组并行多用户信号检测器结构,推导了这种多用户信号检测器的检测算法,算法的计算复杂度与用户数呈线性关系,而性能优于解相关检测器,检测器的总延时小于判决反馈多用户信号检测器。数值及仿真结果表明,当接收到的干扰信号功率高于有用信号:3dB以上时,分组并行多用户信号检测器的误码性能趋于某一值,因而该检测器可以有效地克服CDMA移动通信中的远近效应。     

Blind adaptive energy estimation for decorrelatingdecision-feedback CDMA multiuser detection using learning-typestochastic approximations

This paper investigates the application of linear reinforcement learning stochastic approximation to the blind adaptive energy estimation for a decorrelating decision-feedback (DDF) multiuser detector over synchronous code-division multiple-access (CDMA) radio channels in the presence of multiple-access interference (MAI) and additive Gaussian noise. The decision-feedback incorporated into the structure of a linear decorrelating detector is able to significantly improve the weaker users' performance by cancelling the MAI from the stronger users. However, the DDF receiver requires the knowledge of the received energies. In this paper, a new novel blind estimation mechanism is proposed to estimate all the users' energies using a stochastic approximation algorithm without training data. In order to increase the convergence speed of the energy estimation, a linear reinforcement learning technique is conducted to accelerate the stochastic approximation algorithms. Results show that our blind adaptation mechanism is able to accurately estimate all the users' energies even if the users of the DDF detector are not ranked properly. After performing the blind energy estimation and then reordering the users in a nonincreasing order, numerical simulations show that the DDF detector for the weakest user performs closely to the maximum likelihood detector, whose complexity grows exponentially with the number of users     

BAD: bidirectional arbitrated decision-feedback equalization

The bidirectional arbitrated decision-feedback equalizer (BAD), which has bit-error rate performance between a decision-feedback equalizer (DFE) and maximum a posteriori (MAP) detection, is presented. The computational complexity of the BAD algorithm is linear in the channel length, which is the same as that of the DFE, and significantly lower than the exponential complexity of the MAP detector. While the relative performance of BAD to those of the DFE and the MAP detector depends on the specific channel model, for an error probability of 10/sup -2/, the performance of BAD is typically 1-2 dB better than that of the DFE, and within 1 dB of the performance of MAP detection.     

Noise-predictive decision-feedback detection for multiple-input multiple-output channels

The decision-feedback (DF) detector is a nonlinear detection strategy for multiple-input multiple-output (MIMO) channels that can significantly outperform a linear detector, especially when the order in which the inputs are detected is optimized according to the so-called Bell Labs Layered Space-Time (BLAST) ordering. The DF detector may be implemented as the cascade of a linear detector, which mitigates interference at the expense of correlating the noise, followed by a noise predictor, which exploits the correlation in the noise to reduce its variance. With this architecture, existing linear detectors can be easily upgraded to DF detectors. We propose a low-complexity algorithm for determining the BLAST ordering that is facilitated by the noise-predictive architecture. The resulting ordered noise-predictive DF detector requires fewer computations than previously reported ordered-DF algorithms. We also propose and derive the ordered noise-predictive minimum-mean-squared-error DF detector and show how to determine its BLAST ordering with low complexity.     

An information-theoretic framework for deriving canonical decision-feedback receivers in Gaussian channels

A framework is presented that allows a number of known results relating feedback equalization, linear prediction, and mutual information to be easily understood. A lossless, additive decomposition of mutual information in a general class of Gaussian channels is introduced and shown to produce an information-preserving canonical decision-feedback receiver. The approach is applied to intersymbol interference (ISI) channels to derive the well-known minimum mean-square error (MMSE) decision-feedback equalizer (DFE). When applied to the synchronous code-division multiple-access (CDMA) channel, the result is the MMSE (or signal-to-interference ratio (SIR) maximizing) decision-feedback detector, which is shown to achieve the channel sum-capacity at the vertices of the capacity region. Finally, in the case of the asynchronous CDMA channel we are able to give new connections between information theory, decision-feedback receivers, and structured factorizations of multivariate spectra.     

Channel equalization for block transmission systems

In a block transmission system the information symbols are arranged in the form of blocks separated by known symbols. Such a system is suitable for communication over time-dispersive channels subject to fast time-variations, e,g., the HF channel. The known reliable receiver for this system is the nonlinear data-directed estimator (NDDE). This paper presents appropriate equalization methods for this system. A nonstationary innovations representation based on Cholesky factorization is used in order to define a noise whitener and a maximum-likelihood block detector. Also block linear equalizers and block decision-feedback equalizers are derived. For each type we give the zero-forcing and the minimum-mean-squared-error versions. Performance evaluations and comparisons are given. We show that they perform better than conventional equalizers. As compared to the NDDE, the derived block decision-feedback equalizers perform better and are much less complex. Whereas the NDDE uses the Levinson algorithm to solve M/2 Toeplitz systems of decreasing order (where M is the number of symbols per block), the derived equalizers need to process only one Toeplitz system. Moreover, the Schur algorithm, proposed for Cholesky factorization allows us to further reduce the complexity     

A Soft-Input Soft-Output Decorrelating Block Decision-Feedback Multiuser Detector for Turbo-Coded DS-CDMA Systems

Previously, a decorrelating decision-feedback multiuser detector for direct-sequence code-division multiple-access (DS-CDMA) systems normally produces only hard-decision outputs of users' data. In turbo-coded DS-CDMA systems, such a multiuser detector does not match well with the soft-input soft-output nature of a turbo-decoding algorithm, thereby resulting in some extent of performance loss. In this paper, a soft-input soft-output decorrelating block decision-feedback multiuser detector is proposed to perform joint multiuser detection and turbo decoding in an iterative manner. This multiuser detector partitions the received users' data into a number of blocks appropriately and then detects the users' data on a block-by-block basis, where the soft-decision outputs are generated based on the maximum a posteriori criterion and the decision outputs of a stronger block (with a higher energy) are fed back for use in making decisions of those weaker ones. Computer simulation results show that the proposed iterative multiuser detector with turbo decoding significantly improves the bit error rate performance of a DS-CDMA receiver.     

Asymptotic multiuser efficiencies for decision-directed multiuserdetectors

The asymptotic multiuser efficiencies (AMEs) are derived for various classes of decision-directed multiuser detectors, including multistage detectors, and decision-feedback detectors. Novel classes of soft-decision multistage detectors are proposed and analyzed. Each class is specified in part by a soft-decision nonlinearity, such as a symmetric quantizer or a linear clipper. Closed-form expressions for two-user AMEs are derived for soft-decision two-stage detectors and can be used as a design criterion to optimize the soft-decision nonlinearities. For a special case of two synchronous users, the soft-decision two-stage detector using an optimized linear clipper with either conventional or decorrelated tentative decisions is shown to achieve optimum AME. Upper and lower bounds on the AME are obtained for decision-feedback detectors using either conventional or decorrelated tentative decisions. It is demonstrated that decision-directed multiuser detectors with conventional tentative decisions have low near-far resistance compared to those with decorrelated tentative decisions     

一种新的基于噪声预测的部分判决反馈MIMO接收算法

传统垂直-贝尔实验室分层空时结构(V-BLAST)系统采用全排序判决反馈(ODF)算法,能提高线性接收机性能,但也增加系统复杂度。该文在分段检测理论基础上,提出一种改进的采用噪声预测技术的部分判决反馈(PDF)接收算法。它基于MMSE准则,将接收到信号分为两段,只进行一次判决反馈操作,与传统重复排序判决反馈算法相比,大大降低了接收机计算复杂度。仿真结果表明SUI-3信道中天线数为2发4收,误码率为10-4量级的情况下,其性能与V-BLAST相比只下降了0.6 dB左右,但要明显好于线性接收机以及其他改进型MMSE算法,有2~3dB左右的增益。     

A New Multiuser Detector for Synchronous DS/CDMA System

1IntroductionInaCode-DivisionMultiple-Access(CDMA)system,severalindependentusersaccesssimulboeouslyacommonchannelbymodulatingpreassignedsignatUrewaveforms.Inthemobileradiochannels,MultipleAccessinterference(MAI)arises.Therefore,muchattelltionhasbeend...     

Efficient Detection Algorithms for MIMO Communication Systems

In this paper, two new efficient detection algorithms, Type 1 (T1) with better complexity-performance tradeoff and Type 2 (T2) with lower complexity, are derived from one generalized framework for multiple-input multiple-output (MIMO) communication systems. The proposed generalized detection framework constructed by parallel interference cancellation (PIC), group, and iteration techniques provides three parameters and three sub-algorithms to generate two efficient detection algorithms and conventional BLAST-ordered decision feedback (BODF), grouped, iterative, and B-Chase detection algorithms. Since the group interference suppression (GIS) technique is applied to the proposed detection algorithms, the complexities of the preprocessing (PP) and tree search (TS) can be reduced. In (8,8) system with uncoded 16-QAM inputs, one example of the T1 algorithm can save complexity by 21.2% at the penalty of 0.6 dB loss compared with the B-Chase detector. The T2 algorithm not only reduces complexity by 21.9% but also outperforms the BODF algorithm by 3.1 dB.     

CDMA移动通信中的判决反馈多用户信号检测器

本文推导了一种具有线性计算复杂度的同步ＤＳ—ＣＤＭＡ系统多用户检测算法，由此形成的判决反馈检测器在性能上优于解相关检测器，与两级多用户检测器的性能相当，而实现起来则更为简单。数值结果表明，当接收到的干扰信号能量比有用信号能量高４ｄＢ以上时，判决反馈检测器的性能将接近单用户系统的性能，因而该检测器可有效地克服ＣＤＭＡ移动通信中的远近影响。     

Decision-feedback blind adaptive multiuser detector for synchronousCDMA system

We develop a blind adaptive multiuser detector for synchronous code-division multiple access (CDMA) with a noise-whitening filter. The triangular structure of the noise-whitened model ensures complete resolution of detection ambiguities. To further improve the symbol error probability performance, we introduce decision feedback in our detector similar to the decorrelating derision-feedback detector (DDFD), thus forming the decision-feedback blind adaptive multiuser detector (DFBD). Simulations indicate that the performance of the DFBD is very close to that of the DDFD in additive white Gaussian noise (AWGN) channels. In Rician fading channels, the DFBD can track the slowly varying channels well and has a symbol error probability performance approaching that of the DDFD, which requires the knowledge of users' energies. The blind adaptive and decision-feedback blind adaptive multiuser detectors proposed here do not, however, require that knowledge     

SPREAD SPECTRUM WATERMARK DETECTION IN DRT-DOMAIN

The traditional correlation-based detector is optimal only for Gaussian data, but the Laplacian Probability Density Function (PDF) is more appropriate to model the coefficients in the Discrete Ridgelet Transform (DRT) domain. An additive maximum-likelihood detector based on the Laplacian PDF is analyzed and the theoretical result of its performance is given. The experiments show that the error of the Laplacian model for the DRT coefficients of many images is smaller than that of the Gaussian model. The experiments also prove that the Laplacian detector is superior to the tradi- tional correlation-based detector.     

Truncation for Low-Complexity MIMO Signal Detection

Joint maximum-likelihood (JML) detector may be used in memoryless multiple-input multiple-output (MIMO) systems to obtain optimal detection performance. However, JML detector performs an exhaustive search and has prohibitively large decoding complexity. To reduce the complexity of MIMO signal detection, minimum mean-square-error (mmse) linear detector (LD), decision-feedback detector (DFD), group detector, and sphere detector (SD) may be used. In this correspondence, we propose a truncation based detector for low-complexity MIMO signal detection, and give theoretical insight into the design and performance of such a detector. We study bitruncation in detail and present two bitruncation approaches. These approaches have low-complexity, and computer simulation results show that they outperform mmse-LD and mmse-DFD     

Performance analysis of linear multiuser detectors for randomlyspread CDMA using Gaussian approximation

The performance of a linear decorrelating detector (LDD) and a minimum mean square error (MMSE) detector is analyzed for random spreading waveforms. The performance of the LDD and MMSE detectors is expressed in terms of the so-called near-far resistance, defined by a reciprocal of a diagonal component of inverse matrix. For random code division multiple access, which employs random spreading waveforms, the near-far resistance can be regarded as a random variable. Many papers have dealt with the analysis of multiuser detectors for random spreading sequences. In most cases, however, these analyses derived only the expectations or bounds for the near-far resistance. In this paper, we directly derive the approximate probability density function (PDF) of the near-far resistance and corresponding bit error rate expression for random spreading sequences. It is based on Gaussian approximation of the cross correlation between any two randomly generated spreading codes. The resulting PDF turned out to be a reversed-and-scaled version of chi-square distribution. The approximate expressions, both the PDF and the corresponding bit error rate expression, were verified via Monte Carlo simulations. The results showed that the approximation is quite close to the simulation results when the number of users is less than half the processing gain     

Local ML detection for multicarrier DS-CDMA downlink systems with grouped linear precoding

Abstract-A multicarrier direct-sequence code-division multiple-access (MC-DS-CDMA) downlink system with linear precoding over a group of subcarriers is considered. This scheme preserves user orthogonality independently of the underlying frequency-selective channel, collects the channel diversity and enables low-complexity decoding. In this context, we examine a local maximum-likelihood (LML) detection technique that searches for the maximum-likelihood (ML) solution in the neighborhood of the output provided by the minimum mean-squared error (MMSE) detector. By exploiting the soft information of the MMSE detector output and the precoder structure, we introduce useful criteria to reduce the computational complexity of the LML search. Simulations illustrate that the LML-MMSE detector with minimum neighborhood size yields considerable BER improvement with respect to MMSE, and outperforms a block decision-feedback equalization (DFE) approach at comparable complexity.     

On adaptive decision-feedback equalization of intersymbolinterference channels in coded modulation systems

Recently, Eyuboglu (1988) has shown that adaptive noise-predictive decision-feedback equalization (DFE) can be combined with coded modulation to achieve high-speed data transmission by periodic interleaving. In this paper, we present a new method of adaptive DFE with periodic interleaving for coded modulation systems. The method is an improved version of that proposed by Eyuboglu, where the deinterleaving operation is performed on a vector-by-vector basis, instead of a sample-by-sample basis. Unlike the original system in which the linear equalizer's coefficients can be adjusted only with hard decisions from the threshold detector, the improved structure updates the coefficients of both the linear equalizer and the noise predictor based on soft decisions from the most likely path in the soft decoder. The improved system achieves better error-rate performance than the original with a little increase in hardware complexity. As compared to another improved design reported by Zhou et al. (1990), the new structure also gains advantages in error-rate performance, hardware complexity, and throughput delay     

Decision-feedback equalization using multiple-hyperplanepartitioning for detecting ISI-corrupted M-ary PAM signals

A decision-feedback equalizer scheme is derived based on multiple-hyperplane partitioning of signal space for detecting M-ary pulse amplitude modulation symbols transmitted through a noisy intersymbol interference channel. The proposed scheme is based on the fact that the optimal Bayesian decision boundary separating two neighboring signal classes is asymptotically piecewise linear and consists of several hyperplanes, when the signal-to-noise ratio tends to infinity. An algorithm is developed to determine these hyperplanes, which are then used to partition the observation signal space. The resulting detector can closely approximate the optimal Bayesian detector, at an advantage of considerably reduced detector complexity