编码的多载波CDMA系统中Turbo时空多用户检测

联合MAP多用户检测和信道译码的迭代多用户检测技术可显著提高多载波CDMA系统的容量和性能,本文给出了结合智能天线和迭代MAP多用户检测的Turbo时空多用户检测算法,该方法进一步提高了系统的性能.Turbo时空多用户检测算法不仅极大减小了传统最优MAP多用户检测算法的运算量,而且,此算法性能在AWGN和频率选择性衰落信道中都能逼近单用户编码多载波CDMA系统多天线接收的性能.     

频选快衰落信道的Turbo均衡算法

针对频选快衰落信道,本文提出卡尔曼滤波信道跟踪、软输出判决反馈均衡及软输入软输出信道解码迭代处理的Turbo均衡算法以充分利用已获得的信息,实现信道估计、信道均衡与信道解码的迭代更新,并克服传统判决反馈均衡器误差传播的缺陷.仿真表明,本算法能有效地跟踪快衰落信道,经两次迭代就可获得较为满意的码间干扰消除效果.     

频选衰落MIMO信道的Turbo均衡

针对Turbo编码频选慢衰落MIMO信道,提出基于滑窗式概率数据辅助(Probabilistic Data Association)的软输出判决反馈均衡和软输入软输出Turbo信道解码器间迭代处理的Turbo均衡算法。充分利用已获得的信息,实现信道均衡与信道解码的迭代更新,克服传统判决反馈均衡器误差传播的缺陷。仿真表明,该系统经3次迭代就可获得较为满意的符号间干扰消除效果。     

Turbo MUD技术在TD-SCDMA系统中的应用

TD-SCDMA已成为第3代移动通信国际标准之一,它采用联合检测技术来抑制符号间干扰(ISI)和多址干扰(MAI)。介绍了Turbo多用户检测(MUD)技术在TD-SCDMA系统中的应用,该技术将Turbo迭代译码思想引入到联合检测,有机结合多用户检测和信道译码2种技术,通过在软MUD和软信道译码间多次进行迭代并及时交换软信息(如后验概率)来提高系统性能。研究表明,采用TurboMUD可使系统性能显著提高。     

MC-CDMA系统迭代检测中的一种信道估计算法

在DS—CDMA系统中，联合译码的迭代多用户检测是克服多址干扰增加系统容量的有效方法。本文将多用户检测和译码相结合的迭代检测技术应用于MC—CDMA系统，其中，多用户检测器由串行干扰消除和其后的MMSE滤波器组成。文中提出一种时域信道估计作为迭代初始值的频域信道估计算法，比单纯的频域信道估计方法节约导频符号数量，并且由于信道估计性能的改善，加快了迭代检测的收敛速度。     

DS/CDMA同步信道中的多用户联合检测和译码

将迭代(Turbo)处理的思想应用于DS/CDMA系统同步信道的多用户检测和译码中,接收机利用信道译码的先验信息进行多用户前端处理,而其输出又作为信道译码器软输入,从而使多用户检测和信道译码联合进行,通过迭代逐渐逼近单用户性能,减少多址干扰的影响。仿真结果给出了迭代处理方法在不同信噪比条件下的比特误码率性能。     

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。     

不完全信道状态信息条件下多用户Turbo-BLAST迭代检测算法

该文将空时多用户检测技术和Turbo-BLAST方案相结合,构造了基于CDMA技术的多用户Turbo- BLAST系统模型,提出了不完全信道状态信息条件下的解相关算法和迭代检测算法。在发送端将V-BLAST结构与CDMA技术相结合实现多路复用,在接收端利用空时多用户检测算法去除用户间干扰,得到期望用户的接收信号,然后采用考虑信道估计误差的软干扰抵消迭代检测算法,对期望用户的接收信号进行检测以去除天线间干扰。仿真结果说明,所提算法对于多用户Turbo-BLAST系统是有效的,可在不增加复杂度的条件下达到良好的迭代效果。     

宇宙通信、星际通信、卫星通信与多址通信

Y98-61483-6 9907938采用迭代译码和软干扰对消的多载频 CDMA=Multi-carrier CDMA with iterative decoding and soft-interfer-ence cancellation[会,英]/Kaiser,S.& Hagenauer,J.//1997 IEEE GLOBECOM,Vol.1.—6～10(MaV)本文提出并研究了在多载频码分多址(CDMA)系统中采用迭代软干扰对消的一种新颖的多用户检测方案。介绍了多载频 CDMA(MC-CDMA)系统模型及所提出的采用软干扰对消的迭代检测和译码方案的基本原理。对于衰落信道验证了所提出方案的性能,并且与采用 MMSE(最小均方误差)均衡的单用户检测及采用 MLSE(最大似然序列估计)的多用户检测进行了性能比较。参12     

Turbo编码STBC系统中削弱误差传播的迭代多用户检测技术

空时编码(STC)技术将天线阵列信号处理和信道编码技术联合起来实现无线信道容量的有效增加。为了抑制空时分组编码(STBC)系统的共道用户干扰,对低复杂度的多用户检测算法进行研究,该文提出了一种STBC系统的迭代(turbo)多用户接收机。该接收机由一个软入软出(SISO)基于均值的软判决多用户检测器(Soft Decision Multi-User Detector, SDMUD)和一组SISO Turbo信道解码器构成。两者之间通过迭代交换外信息,精确地估计用户信号。仿真结果表明这种接收技术经3次迭代后性能改善约2dB,并且系统性能会随着接收天线的增多而得到明显提高,从而大大增加系统容量。     

Transmit antennae space-time block coding for generalized OFDM inthe presence of unknown multipath

Transmit antenna diversity has been exploited to develop high-performance space-time coders and simple maximum-likelihood decoders for transmissions over flat fading channels. Relying on block precoding, this paper develops generalized space-time coded multicarrier transceivers appropriate for wireless propagation over frequency-selective multipath channels. Multicarrier precoding maps the frequency-selective channel into a set of flat fading subchannels, whereas space-time encoding/decoding facilitates equalization and achieves performance gains by exploiting the diversity available with multiple transmit antennas. When channel state information is unknown at the receiver, it is acquired blindly based on a deterministic variant of the constant-modulus algorithm that exploits the structure of space-time block codes. To benchmark performance, the Cramer-Rao bound of the channel estimates is also derived. System performance is evaluated both analytically and with simulations     

Blind turbo multiuser detection for long-code multipath CDMA

We consider the problem of demodulating and decoding multiuser information symbols in an uplink asynchronous coded code-division multiple-access (CDMA) system employing long (aperiodic) spreading sequences, in the presence of unknown multipath channels, out-cell multiple-access interference (OMAI), and narrow-band interference (NBI). A blind turbo multiuser receiver, consisting of a novel blind Bayesian multiuser detector and a bank of MAP decoders, is developed for such a system. The effect of OMAI and NBI is modeled as colored Gaussian noise with some unknown covariance matrix. The main contribution of this paper is to develop blind Bayesian multiuser detectors for long-code multipath CDMA systems under both white and colored Gaussian noise. Such detectors are based on the Bayesian inference of all unknown quantities. The Gibbs sampler, a Markov chain Monte Carlo procedure, is then used to calculate the Bayesian estimates of the unknowns. The blind Bayesian multiuser detector computes the a posteriori probabilities of the channel coded symbols, which are differentially encoded before being sent to the channel. Being soft-input soft-output in nature, the proposed blind Bayesian multiuser detectors and the MAP decoders can iteratively exchange the extrinsic information to successively refine the performance, leading to the so-called blind turbo multiuser receiver     

Space-time turbo equalization in frequency-selective MIMO channels

A computationally efficient space-time turbo equalization algorithm is derived for frequency-selective multiple-input-multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang (see Signal Processing, vol.81, no.5, p.989-995, 2001) for frequency-selective fading channels and of iterative multiuser detection for code-division multiple-access (CDMA) systems by Wang and Poor (see IEEE Trans. Commun., vol.47, p.1046-1061, 1999). The proposed algorithm is implemented as a MIMO detector consisting of a soft-input-soft-output (SISO) linear MMSE detector followed by SISO channel decoders for the multiple users. The detector first forms a soft replica of each composite interfering signal using the log likelihood ratio (LLR), fed back from the SISO channel decoders, of the transmitted coded symbols and subtracts it from the received signal vector. Linear adaptive filtering then takes place to suppress the interference residuals: filter taps are adjusted based on the minimum mean square error (MMSE) criterion. The LLR is then calculated for adaptive filter output. This process is repeated in an iterative fashion to enhance signal-detection performance. This paper also discusses the performance sensitivity of the proposed algorithm to channel-estimation error. A channel-estimation scheme is introduced that works with the iterative MIMO equalization process to reduce estimation errors.     

Low-complexity turbo equalization and multiuser decoding for TD-CDMA

The authors propose a low complexity multiuser joint parallel interference cancellation (PIC) decoder and turbo decision feedback equalizer for code division multiple access (CDMA). In their scheme, an estimate of the interference signal (both multiple-access interference and intersymbol interference) is formed by weighting the hard decisions produced by conventional (i.e., hard-output) Viterbi decoders. The estimated interference is subtracted from the received signal in order to improve decoding in the next iteration. By using asymptotic performance analysis of random-spreading CDMA, they optimize the feedback weights at each iteration. Then, they consider two (mutually related) performance limitation factors: the bias of residual interference and the ping-pong effect. The authors show that the performance of the proposed algorithm can be improved by compensating for the bias in the weight calculation, and they propose a modification of the basic PIC algorithm, which prevents the ping-pong effect and allows higher channel load and/or faster convergence to the single-user performance. The proposed algorithm is validated through computer simulation in an environment fully compliant with the specifications of the time-division duplex mode of third-generation systems, contemplating a combination of time-division multiple access and CDMA and including frequency-selective fading channels, user asynchronism, and power control. The main conclusion of this work is that, for such application, soft-input soft-output decoders (e.g., implemented by the forward-backward BCJR algorithm) are not needed to attain very high spectral efficiency, and simple conventional Viterbi decoding suffices for most practical settings.     

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.     

Space-time turbo multiuser detection for coded MC-CDMA

The system capacity and performance of multicarrier code-division multiple-access (MC-CDMA) communication systems can be significantly enhanced by jointly employing MAP-based multiuser detection (MUD) and channel decoding techniques. In this paper, a group-oriented soft iterative MUD based on the combination of smart antennas and iterative MAP-based MUD is presented. The proposed method is featured as a novel technique for further increasing the system capacity and performance. In this method, all the users are first grouped into several groups according to their impinging direction of arrivals (DOAs). All users with similar DOAs are classified into the same group and then low-complexity MAP-based iterative MUD is employed in each group. Because spatial filtering cannot suppress all the interference between the groups, interference cancellation among the groups is used prior to MUD within each group. It is shown that the proposed group-oriented soft iterative MUD algorithm can significantly reduce the computational complexity compared with the conventional optimal MAP-based MUD schemes. It is also demonstrated that the performance of the proposed algorithm can approach that of a single-user coded MC-CDMA system with an antenna array in additive white Gaussian noise and frequency selective fading channels.     

Sampling-based soft equalization for frequency-selective MIMO channels

We consider the problem of channel equalization in broadband wireless multiple-input multiple-output (MIMO) systems over frequency-selective fading channels, based on the sequential Monte Carlo (SMC) sampling techniques for Bayesian inference. Built on the technique of importance sampling, the stochastic sampler generates weighted random MIMO symbol samples and uses resampling to rejuvenate the sample streams; whereas the deterministic sampler, a heuristic modification of the stochastic counterpart, recursively performs exploration and selection steps in a greedy manner in both space and time domains. Such a space-time sampling scheme is very effective in combating both intersymbol interference and cochannel interference caused by frequency-selective channel and multiple transmit and receiver antennas. The proposed sampling-based MIMO equalizers significantly outperform the decision-feedback MIMO equalizers with comparable computational complexity. More importantly, being soft-input soft-output in nature, these sampling-based MIMO equalizers can be employed as the first-stage soft demodulator in a turbo receiver for coded broadband MIMO systems. Such a turbo receiver successively improves the receiver performance through iterative equalization, channel re-estimation, and channel decoding. Finally, computer simulation results are provided to demonstrate the performance of the proposed sampling-based soft MIMO equalizers in both uncoded and turbo coded systems.     

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 (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