水声通信中基于软判决的块迭代判决反馈均衡器

在单载波频域均衡水声通信系统中,混合结构的时-频域判决反馈均衡器(H-DFE)计算复杂度高,不利于实时实现;而基于硬判决的块迭代判决反馈均衡器(HD-IBDFE)存在错误符号判决造成系统性能下降问题,同时需要估计判决符号和发射数据之间的互相关函数。该文对水声通信中基于软判决的块迭代判决反馈均衡(SD-IBDFE)接收机算法进行了研究,通过对均衡器输出信号进行软判决,并将符号软信息进行反馈,提高了系统性能,同时采用迭代信道估计方法来适应水声信道的时变性。通过仿真比较得出,该方法在水声信道条件下明显优于HD- IBDFE。对湖上试验数据处理结果表明,在浅水1.8 km通信距离下,单通道无编码QPSK调制可实现10-3的误码率并达到3000 bps的有效数据率。     

采用相位判决的低复杂度广义空间调制检测算法

针对广义空间调制(GSM)系统中信号检测复杂度过高的问题,提出了一种基于相位判决的低复杂度检测算法.首先根据一种排序准则对天线组合进行排序,然后将排序后的天线组合中的符号向量依次通过基于相位判决的迫零(ZF)均衡器进行检测,最终得到星座调制符号和激活天线组合.分析和仿真结果表明,该检测算法可以有效缩小接收端的搜索范围,在提供与最大似然(ML)检测算法相近的误比特率(BER)性能的同时,计算复杂度降低了98％.     

基于多用户反馈的判决反馈均衡器的研究

本文提出的一种新颖的基于多用户反馈的判决反馈均衡器,解决了在CDMA多用户检测中传统自适应判决反馈均衡器误码率高、系统容量小的缺点.它由具有误差反馈滤波器的判决反馈均衡器(Decision Feedback Equalizer with Error Feedback Filter,DFE-EFF)构成,并在判决后反馈多用户数据抵消多址干扰(多用户反馈干扰抵消).文中给出其结构图,分析各种判决反馈均衡算法.理论证明,具有误差反馈滤波器的多用户反馈干扰抵消判决反馈均衡器(多用户反馈干扰抵消DFE-EFF)较各种判决反馈均衡器为最优,它能同时有效处理ISI,MAI和噪声的干扰.仿真结果表明,在误码率性能和系统容量两方面,多用户反馈干扰抵消DFE-EFF比DFE、DFE-EFF均有较大改善.     

改进的SC-FDE块迭代判决反馈均衡器

在单载波频域传输(SC-FDE)系统中,块迭代判决反馈均衡器(IBDFE)明显提升了传统线性频域均衡器的性能.未知发送信号与迭代判决信号的相关因子估计是其关键技术,直接影响均衡器的性能.首先对IBDFE相关因子估计算法进行了改进,同时提出一种基于独特字(UW)帧结构的估计方法.该方法利用独特字的已知性和恒包络性进行判决,基于此判决方式使相关因子得到更精准的估计.实验结果表明,两种方法对IBDFE的性能有较为明显的提升.     

基于稀疏多径信道的均衡技术分析

为了解决宽带通信稀疏多径信道下均衡器结构复杂和收敛速度慢的问题,介绍了稀疏多径信道和基于伪随机序列的多径搜索。针对稀疏多径信道的特点,对判决反馈均衡器进行改进,提出了一种基于正交匹配追踪信道估计的完全判决反馈均衡器。利用正交匹配追踪估计结果在前馈均衡器前消除已判决码元对当前判决码元的码间串扰,降低了均衡器的复杂度,提高了收敛速度。通过仿真分析表明完全判决反馈均衡器能取得良好的性能。     

一种小数据量的通信信号符号速率估计方法

针对低信噪比条件下利用过零检测进行小数据量信号符号速率估计性能较差的问题,提出一种基于判决反馈的估计方法。该方法利用已知符号速率集,首先对基带信号进行判决,并根据判决结果生成方波作为匹配模板,与原始基带信号进行相关匹配,若相关值高于门限值则判定当前符号速率为估计结果。仿真试验表明,基于判决反馈的符号速率估计方法信噪比性能优于传统过零检测方法 6 d B以上。     

MIMO通信系统中一种新的自适应均衡方法

该文提出了时变频率选择性衰落环境下多输入多输出(MIMO)通信系统中一种新的基于递归最小二乘(RLS)的自适应干扰对消的判决反馈均衡方法(RLS-IC-DFE)。该方法将每个数据子流上的自适应判决反馈均衡器等效为一个加长的新的均衡器,并把已解出的子流数据作为新的输入参数,应用RLS算法自适应调整新的均衡器参数。仿真结果表明,该文提出的自适应干扰对消的判决反馈均衡器可以自适应跟踪信道变化,同时比已有的判决反馈均衡器(RLS-DFE)能提供更好的误符号率(SER)性能。     

基于双向逐幸存路径处理的空时格形码软判决自适应解码

本文提出一种针对TDMA下行链路的空时格形码自适应解码算法.为充分利用下行链路相邻时隙前导序列中的正交导引信号,该解码算法采用了双向逐幸存路径处理技术——正向处理利用基于当前时隙前导序列的自适应信道估计实现正向解码,并将软判决结果传递给反向处理模块;以正向软判决为先验知识,反向处理利用基于下一时隙前导序列的自适应信道估计实现反向解码,并将反向软判决作为最终结果输出.计算机仿真结果表明:在存在卷积外码的情况下,与基于最大似然序列检测的单向硬判决解码相比,基于所提出算法的软判决解码在多普勒频移小于60赫兹的时变信道中可提供1～2dB的增益.     

自适应均衡算法在信道均衡技术中的应用研究

文中描述了两种非线性均衡器分别为判决反馈均衡器(DFE)和最大似然序列估计(MLSE)均衡器.所用信道模型为加性白高斯噪声信道,在DFE和线性均衡器(LE)中都是使用递归最小二乘(RLS)算法和最小均方(LMS)算法对数据进行分块处理.MLSE均衡器中使用了维特比最佳译码算法.就误比特性能来做以比较,DFE远好于LE,MLSE均衡器又明显优于DFE,并且它能达到几乎最优的性能.     

一种用于TCM系统的均衡方法

本文介绍了一种适合于网格编码调制（ＴＣＭ）系统的均衡方法。这种方法基于预均衡结构,回避了网格译码不能提供判决反馈均衡（ＤＦＥ）所需的可靠的零时延判决的问题。本文从迫零判决反馈均衡器出发,利用网络编码市制的格形（Ｌａｔｔｉｃｅ）分割原理,推导出这种均衡器的结构。这种均衡器不但能够对带限符号间干扰信道进行均衡,而且当传输速度。较高时时,所采用的预均衡结构不影响预均衡器的输入序列的分布特性。因而可以支持     

Low complexity soft-input soft-output block decision feedback equalization

A low complexity soft-input soft-output (SISO) block decision feedback equalizer (BDFE) is presented for turbo equalization. The proposed method employs a sub-optimum sequence-based detection, where the soft-output of the equalizer is calculated by evaluating an approximation of the sequence-based a posteriori probability (APP) of the data symbol. The sequence-based APP approximation is enabled by the adoption of both soft a priori information and soft decision feedback, and it leads to better performance and faster convergence compared to symbol-based detection methods as used by most other low complexity equalizers. The performance and convergence property of the proposed algorithm is analyzed by using extrinsic information transfer (EXIT) chart. Both analytical and simulation results show that the new equalizer can achieve a performance similar to that of trellis-based equalization algorithms, with a complexity similar to linear SISO minimum mean square error equalizers.     

基于概率软切换的两级双模盲均衡器

文中提出一种基于概率软切换的两级双模盲均衡器。它实时统计两级盲均衡器输出硬判决值相同的概率,并利用它切换盲均衡算法。该均衡器结合了级联两级均衡结构和双模算法的优点。仿真表明,它能够纠正相位偏移,相对于波特间隔（BSE）的并发常模＋判决导引（CMA＋DD）盲均衡器,以非常小的计算复杂度代价,获得稳态均方误差（MSE）性能和误比特率（BER）性能的较大提高。     

Joint Frequency-Domain Multiuser Turbo Equalization with Successive Interference Cancellation for Doubly-Selective Fading Channels

A novel multiuser separation and equalization scheme is proposed for single carrier wireless communication systems integrating frequency-domain (FD) multiuser turbo equalization (MUTE) and successive interference cancellation (SIC). The proposed iterative structure consists of multiple layers of detection, and at each layer the user with strongest power is processed by a frequency-domain multiuser equalizer to yield the soft extrinsic information on the coded bits of that user, which is delivered to a channel decoder after deinterleaving. The extrinsic information gleaned by the decoder is fed back to both the current and previous multiuser equalizers for the next iteration as a-priori information. The soft symbols of the current user are evaluated by the a-posteriori information of coded bits provided by the multiuser equalizer, and the interference reconstructed by the current user’s soft symbols is canceled out from the received signals in frequency domain. The interference-canceled signals are fed forward to subsequent layers for detection of other users. The proposed scheme effectively mitigates multiple access interference and intersymbol interference by an iterative (turbo) detection method. Numerical simulation examples demonstrate that the proposed FD MUTE with SIC outperforms the traditional MMSE multiuser equalizer over the severely doubly-selective channels, and the bit-error-rate performance tends to be better with the increase of iterations.     

Doubly iterative receiver for block transmissions with EM-based channel estimation

Cyclic-prefix code division multiple access (CP-CDMA), multicarrier CDMA (MC-CDMA) and single carrier cyclic-prefix (SCCP) transmission are some schemes that could support the increasing demand of future high data rate applications. The linear and nonlinear equalizers used to detect the transmitted signal are always far from the Maximum-Likelihood (ML) detection bound. The block iterative generalized decision feedback equalizer (BI-GDFE) is an iterative and effective interference cancelation scheme which could provide near-ML performance yet with very low complexity. In order to deploy this scheme, the channel state information (CSI) must be available at the receiver. In practice, this information has to be estimated by using pilot and data symbols. This paper investigates the problem of channel estimation using the Expectation Maximization (EM) algorithm. The BI-GDFE provides the soft information of the transmitted signals to the EM-based algorithm in the form a combination of hard decision and a coefficient so-called the input-decision correlation (IDC). The resultant receiver becomes a doubly iterative scheme. To evaluate the performance of the proposed estimation algorithm, the Cramér-Rao Lower Bound (CRLB) is also derived. Computer simulations show that the bit error rate (BER) performance of the proposed receiver for joint channel estimation and signal detection can reach the performance of the BI-GDFE with perfect CSI.     

MIMO OFDM系统中的Turbo子载波均衡

在MIMO OFDM系统中,为了对抗同天线干扰及由于保护间隔不足而引起的码间干扰和载波间干扰,该文给出了一种基于MMSE的Turbo子载波均衡器。在该算法中,软输入软输出(SISO)的子载波均衡器与软输入软输出(SISO)解码器通过迭代进行软信息交换。仿真结果表明,与非迭代的子载波均衡器相比,该文给出的Turbo子载波均衡器能够有效利用时间和空间分集,使系统性能得到了改善。     

Space–Time Turbo Equalization With Successive Interference Cancellation for Frequency-Selective MIMO Channels

This paper addresses the issue of iterative space–time equalization for multiple-input–multiple-output (MIMO) frequency-selective fading channels. A new soft equalization concept based on successive interference cancellation (SIC) is introduced for a space–time bit-interleaved coded modulation (STBICM) transmission. The proposed equalizer allows us to separate intersymbol interference (ISI) and multiantenna interference (MAI) functions. Soft ISI is successively suppressed using a low-complexity suboptimum minimum mean square error (MMSE) criterion. The decoupling of ISI and MAI offers more flexibility in the design of the whole space–time equalizer. Different multiantenna detection criteria can be considered, ranging from simple detectors to the optimal maximum a posteriori (MAP) criterion. In particular, we introduce two soft equalizers, which are called SIC/SIC and SIC/MAP, and we show that they can provide a good performance-to-complexity tradeoff for many system configurations, as compared with other turbo equalization schemes. This paper also introduces an MMSE-based iterative channel state information (CSI) estimation algorithm and shows that attractive performance can be achieved when the proposed soft SIC space–time equalizer iterates with the MMSE-based CSI estimator.      

Nonlinear equalization of multipath fading channels withnoncoherent demodulation

A nonlinear decision-based adaptive equalizer compatible with differentially coherent phase shift keying (PSK) is proposed for frequency-selective fading channels. This equalization scheme is appropriate whenever conventional equalizers are not capable of tracking phase variations in selective fading channels. The received signal is first converted to a baseband signal and then sent through a differential detector. A nonlinear processor before the equalizer generates the needed nonlinear terms that are weighted and summed in the equalizer. Nonlinear intersymbol interference at the output of the differential detector is dealt with by minimizing an error signal between the output of the equalizer and the detected data. The adaptation algorithm can be any algorithm currently used for conventional equalizers. Our simulation results confirm that for channels with spectral nulls, equalization is achieved successfully with the proposed scheme, whereas, linear equalizers, either with coherent or noncoherent detection, fail     

A new adaptive equalizer with channel estimator for mobile radiocommunication

For unknown mobile radio channels with severe intersymbol interference (ISI), a maximum likelihood sequence estimator, such as a decision feedback equalizer (DFE) having both feedforward and feedback filters, needs to handle both precursors and postcursors. Consequently, such an equalizer is too complex to be practical. This paper presents a new reduced-state, soft decision feedback Viterbi equalizer (RSSDFVE) with a channel estimator and predictor. The RSSDFVE uses maximum likelihood sequence estimation (MLSE) to handle the precursors and truncates the overall postcursors with the soft decision of the MLSE to reduce the implementation complexity. A multiray fading channel model with a Doppler frequency shift is used in the simulation. For fast convergence, a channel estimator with fast start-up is proposed. The channel estimator obtains the sampled channel impulse response (CIR) from the training sequence and updates the RSSDFVE during the bursts in order to track changes of the fading channel. Simulation results show the RSSDFVE has nearly the same performance as the MLSE for time-invariant multipath fading channels and better performance than the DFE for time-variant multipath fading channels with less implementation complexity than the MLSE. The fast start-up (FS) channel estimator gives faster convergence than a Kalman channel estimator. The proposed RSSDFVE retains the MLSE structure to obtain good performance and only uses soft decisions to subtract the postcursor interference. It provides the best tradeoff between complexity and performance of any Viterbi equalizers     

Turbo equalization via constrained-delay APP estimation with decision feedback

We consider turbo equalization for intersymbol interference (ISI) channels, wherein soft symbol decisions generated by the channel detector are iteratively exchanged with the outer error-correction decoder based on the turbo principle. Our work is based on low-complexity suboptimal soft-output channel detection using a constrained-delay (CD) a posteriori probability (APP) algorithm. Central to the proposed idea is the incorporation of effective decision-feedback schemes, which significantly reduce complexity while providing immunity against error propagation that typically plagues decision-feedback schemes. We observe that the effect of decision feedback is quite different on turbo equalization versus traditional, hard-decision-generating and noniterative equalization. In particular, we demonstrate that when the feedback scheme applied is inadequate for the given equalizer parameters and ISI condition, the extrinsic information generated by the equalizer becomes distinctly non-Gaussian, and the quality of soft information, as monitored by the trajectory of mutual information, fails to improve in the iterative process. We identify parameters of feedback-based CD-APP schemes that offer favorable complexity/performance tradeoffs, compared with existing turbo-equalization techniques.     

Trellis-based soft-output adaptive equalization techniques for TDMAcellular systems

The concatenation of an equalizer and a Viterbi (1967) decoder is a powerful means for improving receiver performance in wireless communication systems. A soft-output equalizer increases the impact of this combination by enabling the use of soft-decision Viterbi decoding. It is well known that the maximum a posteriori (MAP) algorithm provides optimal reliability information, but at the cost of substantial complexity. This paper contains the results of an investigation into the design and performance of soft-output adaptive equalization techniques based on suboptimum trellis-based soft-output decoding algorithms. It is shown that the performance improvement relative to hard output equalizers is substantial, while the cost in terms of complexity is modest. A time-division multiple-access (TDMA) cellular system is used as the basis for comparisons. Simulation results and a complexity analysis are presented