Column-anchored zeroforcing blind equalization for multiuserwireless FIR channels

We propose a direct blind zeroforcing approach to cancel intersymbol interference (ISI) in multiple user finite impulse response (FIR) channels. By selectively anchoring columns of the channel convolution matrix, we present two column-anchored zeroforcing equalizers (CAZE), one without output delay and one with a chosen delay. Unlike many known blind identification algorithms, these equalizers do not need an accurate estimate of the channel orders. Exploiting second-order statistics (SOS) of the received signals, they can retain preselected d columns in the channel convolution matrix (d is the number of users) and force the remaining columns to zero. CAZE can effectively equalize single-input-multiple-output (SIMO) systems and can reduce dynamic multiple-input-multiple-output (MIMO) systems into a memoryless signal mixing system for source separation. Simulation results show that the CAZE is not only effective for blind equalization of linear quadrature amplitude modulation (QAM) systems, but it is also applicable to the nonlinear GMSK modulation in the popular wireless GSM systems when computational cost severely limits the use of nonlinear methods such as the Viterbi algorithm     

一种适用于高阶QAM系统Bussgang类盲均衡新方法

该文提出一种适用于高阶QAM系统的新Bussgang类多模盲均衡算法。将新的代价函数与星座匹配误差函数结合,给出一种瞬时双模切换混合算法,然后设计了一种基于判决圆的模式切换准则,从而达到进一步有效降低新算法稳态误差的效果。最后,仿真结果以高阶256QAM信号为例,验证了该算法对于高阶QAM信号的盲均衡能力和良好效果。     

基于二阶、四阶矩的QAM系统盲均衡准则

本文研究了QAM系统的盲均衡问题,提出了一个基于二阶、四阶矩的统计量匹配盲均衡准则,并由此导出了一种新的盲均衡算法,从而也加深了对盲均衡的理论认识。     

针对线性群时延畸变的加权多模盲均衡算法

群时延失真是影响卫星通信系统误码性能的重要因素之一。本文分析了高速卫星信道的线性群时延模型,依此模型提出了改进的加权多模盲均衡算法(MWMMA)。该算法引入Sigmoid函数的变形形式,构造了加权幂指数随迭代误差自适应变化的函数关系,在不需要通过大量仿真实验预先确定模式转变门限值的前提下,利用迭代误差的递减实现算法从MCMA模式通过多模自适应切换为DD模式。通过对多种算法的仿真比较,得到该算法不仅能使通过群时延信道的16QAM信号收敛集中,而且具有更小的稳态剩余码间干扰;同时,基于该算法对64QAM和256QAM传输信号的均衡仿真结果,验证了该算法对高阶QAM信号的均衡具有一定的适用性。      

复数Hopfield神经网络盲均衡QAM信号

为了解决复数多值信号的盲均衡问题,本文提出了基于复数Hopfield神经网络盲均衡多值信号的方法:将基于Hopfield神经网络的盲均衡算法从实数域推广到复数域.在复数域成功构造了复数Hopfield神经网络,重点针对16QAM信号进行盲均衡.并验证了此系统可以处理非统计量字符,即处理16QAM信号的Hopfield神...     

Turbo equalization for GMSK signaling over multipath channels basedon the Gibbs sampler

We consider the problem of Bayesian data restoration for Gaussian minimum shift keying (GMSK) signals over unknown multipath channels. As an alternative to the linear approximation method employed in the conventional finite impulse response (FIR) model, we develop a nonlinear signal model for this system. A Bayesian equalizer based on the Gibbs sampler, a Markov chain Monte Carlo (MCMC) procedure, is developed for estimating the a posteriori symbol probability in the GMSK system without explicit channel estimation. The basic idea of this technique 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. Being soft-input soft-output in nature, the proposed Bayesian equalization technique is well suited for iterative processing in a coded system, which allows the Bayesian equalizer to successively refine its processing based on the information from the decoding stage, and vice versa     

利用无约束函数的QAM信号自适应盲均衡方法

本文针对正交幅度调制(QAM)信号的盲均衡与载波相位恢复问题,首先在对现有的基于功率最大化盲均衡算法分析的基础上,依据向量范数间的关系,给出了一种QAM信号盲均衡与载波相位恢复的无约束代价函数;然后对代价函数的收敛性和解的唯一性进行严格论证,证明代价函数在取得最优解时能够同时实现盲均衡与载波相位恢复;之后将其转化为采用随机梯度法实现的自适应算法。相对CMA、MMA等其他自适应算法,新算法可获得更好的性能,通过对高阶QAM信号的均衡仿真,进一步验证了算法的有效性。      

A GMSK modulator using a ΔΣ frequencydiscriminator-based synthesizer

This paper describes a new transmitter architecture suitable for wideband GMSK modulation. The technique uses direct modulation of ΔΣ frequency discriminator (ΔΣFD)-based synthesizer to produce the modulated RF signal without any up-conversion. Digital equalization is used to extend the modulation data rate far beyond the synthesizer closed-loop BW. A prototype 1.9-GHz GSM transmitter was constructed consisting of a ΔΣFD-based synthesizer and a digital transmit filter. The synthesizer consists of an 0.8-μm BiCMOS ΔΣFD chip, a digital signal processor FPGA, and an off-chip D/A converter, filter, and VCO. Measured results, using 271-kbit/s GSM modulation, demonstrate data rates well in excess of the 30-kHz synthesizer closed-loop BW are possible with digital equalization. Without modulation, the synthesizer exhibits a -76-dBc spurious noise level and a close-in phase noise of -74 dBc/Hz     

All-digital reverse modulation architecture based carrier recoveryimplementation for GMSK and compatible FQPSK

A carrier recovery circuit implementation with an all-digital reverse modulation approach for coherent detection in the GSM/GMSK system as well as the GMSK compatible improved efficiency cross-correlated FQPSK system is presented. The proposed carrier recovery implementation utilizes all-digital reverse modulation circuit in a feedback loop to remove the modulated signal from the received intermediate frequency (IF) signal and to estimate the phase error of this carrier signal using a phase-locked loop (PLL). The digital reverse modulation approach avoids the multipliers required in an analog reverse modulation design, so that it can be implemented in a single chip FPGA. Hardware implementation of the coherent detection demonstrates that cross-correlated FQPSK is completely compatible with GMSK in the system performance and the receiver structure for GSM. Experimental performance evaluations show that the proposed carrier recovery circuit provides a Bit Error Rate (BER) performance within 0.3 dB in a non-linearly amplified channel corrupted by additive white Gaussian noise (AWCN) as compared with the simulated performance of the GSM/GMSK system     

双线性反馈神经网络的复值盲均衡算法研究

将基于双线性反馈神经网络的盲均衡算法运用到了复数系统中,推导了复数系统中网络的权值迭代公式,运用QAM信号对算法进行仿真表明,算法对于QAM信号的均衡有着较快的收敛速度和较低的误码率。     

Dual-mode type algorithms for blind equalization

Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. The Godard algorithm and the generalized Sato algorithm are two widely referenced algorithms for blind equalization of a QAM system. These algorithms exhibit very slow convergence rates when compared to algorithms employed in conventional data-aided equalization schemes. In order to speed up the convergence process, these algorithms may be switched over to a decision-directed equalization scheme once the error level is reasonably low. The authors present a scheme which is capable of operating in two modes: blind equalization mode and a mode similar to the decision-directed equalization mode. In this proposed scheme, the dominant mode of operation changes from the blind equalization mode at higher error levels to the mode similar to the decision-directed equalization mode at lower error levels. Manual switch-over to the decision-directed mode from the blind equalization mode, or vice-versa, is not necessary since transitions between the two modes take place smoothly and automatically     

PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization

In some antenna array-based wireless communication systems the received signal is multidimensional and can be treated as a tensor (3D array) instead of a matrix (2D array). In this paper, we make use of a generalized tensor decomposition known as constrained Block-PARAFAC and propose a tensor (3D) model for the signal received by three types of wireless communication systems. The considered wireless communication systems are multiuser systems subject to frequency-selective multipath and employing multiple receiver antennas together with (i) oversampling or (ii) direct-sequence spreading or (iii) multicarrier modulation. The proposed modeling approach aims at unifying the received signal model of these systems into a single PARAFAC model. We show that the proposed model has a constrained structure, where model constraints and associated dimensions depend on each particular system. The proposed constrained Block-PARAFAC model is demonstrated by expanding the tensor using Kronecker products of canonical vectors. As an application of this model to tensor signal processing, a new tensor-based receiver is proposed for blind multiuser equalization, which combines PARAFAC-based modeling with a subspace method. Simulation results are presented to illustrate the performance of the proposed blind receiver.     

Blind decision feedback equalization for terrestrial televisionreceivers

In December 1996 the Federal Communications Commission (FCC) adopted the Grand Alliance (GA) system as the digital television broadcasting standard for the United States ending a seven-year-long search for a fully digital television standard. MPEG-2 was chosen as the video compression standard, and trellis-coded 8-vestigial sideband (VSB) with a training sequence was chosen as the transmission standard. The laboratory tests that were performed on the final two competing systems, 8-VSB with training sequence and 32-quadrature amplitude modulation (QAM) with blind equalization, showed a need for blind equalization in dynamic channels that could not be adequately handled by an equalizer training on the training sequence alone. Hence, the final GA system recommended the use of blind equalization in the receiver. In this paper, we describe the U.S. digital television transmission standard as it pertains to the equalization problem, typical transmission channel characteristics and the need for blind equalization in terrestrial television receivers     

Deterministic approaches for blind equalization of time-varyingchannels with antenna arrays

In this paper, we study the blind equalization problem of time-varying (TV) systems where the channel variations are too rapid to be tracked with conventional adaptive equalizers. We show that using a finite Fourier basis expansion, a TV antenna array system can be cast into a time-invariant multi-input, multi-output (MIMO) framework. The multiple inputs are related through the bases, thereby allowing blind equalization to be accomplished without the use of higher order statistics. Two deterministic blind equalization approaches are presented: one determines the channels first and then the equalizers, whereas the other estimates the equalizers directly. Related issues such as order determination are addressed briefly. The proposed algorithms are illustrated using simulations     

Autocorrelation properties of channel encoded sequences-applicability to blind equalization

Many blind channel equalization/identification algorithms are derived assuming the transmitted information sequence to be white. In practical communication systems, redundancy is added to the source sequence in order to detect and correct symbol errors in the receiver. It is not obvious how channel encoding will affect the assumption of whiteness. The autocorrelation function of some commonly used channel codes is analyzed in order to study the validity of assumptions used in blind equalization. The codes are presented in terms of a Markov model for which the autocorrelation is analytically expressed. The various encoded sequences are used in a prediction error based blind equalizer, and the performance is empirically compared with the case of unencoded data. A blind equalization example using a practical GSM speech encoder combined with a convolutional channel encoder is also given.     

Performance analysis of M‐APSK generalised spatial modulation with constellation reassignment

Generalised spatial modulation (GSM) is a recently developed multiple‐input multiple‐output (MIMO) technique aimed at improving data rates over conventional spatial modulation (SM) systems. However, for identical antenna array size and configurations (AASC), the bit error rate (BER) of GSM systems in comparison with SM systems is degraded. Recently, a GSM system with constellation reassignment (GSM‐CR) was proposed in order to improve the BER of traditional GSM systems. However, this study focused on M‐ary quadrature amplitude modulation (M‐QAM) schemes. The focus of this paper is the application of a circular constellations scheme, in particular, amplitude phase shift keying (APSK) modulation, to GSM and GSM‐CR systems. An analytical bound for the average BER of the proposed M‐APSK GSM and M‐APSK GSM‐CR systems over fading channels is derived. The accuracy of this bound is verified using Monte Carlo simulation results. A 4 × 4 16‐APSK GSM‐CR system achieves a gain of 2.5 dB at BER of 10^?5 over the traditional 16‐APSK GSM system with similar AASC. Similarly, a 6 × 4 32‐APSK GSM‐CR system achieves a gain of 2 dB at BER of 10^?5 over equivalent 32‐APSK GSM system.     

基于星座图的QAM信号调制方式识别

给出了利用信号星座图的QAM信号调制方式识别技术。在对QAM信号进行分析的基础上。重点讨论了信号载频、码元速率盲估计方法以及信道盲均衡方法。仿真结果表明，利用这种方法，可以精确地估计QAM信号的载频和码元速率，成功地将信号星座图恢复出来，并通过信号星座图完成信号的识别。     

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％.     

一种改进的加权多模盲均衡算法

数字有线电视主要采用QAM调制形式。针对QAM调制信号的特点,在加权多模盲均衡算法的基础上,引入Sigmoid函数的变形,提出了一种加权值随均方误差自适应变化的新算法。新算法不需要设定模式转变的门限值,使算法模式从MCMA随均衡输出自适应转化为DD模式。通过仿真表明该算法与多模盲均衡算法(WMMA)相比降低了仿真复杂度,具有更稳定的收敛性能,适应于高阶QAM信号。     

应用粒子滤波器实现混沌通信系统的盲信道均衡

粒子滤波器(Particle filter,PF)是一种结合重要性权重抽样的序贯蒙特卡罗方法,能够应用到任意状态空间模型,并且能较好地估计经过非线性变化后的随机变量的统计特性.本文应用粒子滤波器和信号建模技术研究混沌通信系统的盲信道均衡问题,发展基于混沌的通信系统的盲均衡技术.仿真结果证实了,当Logistic映射作为混沌发生器和通信场景为固定参数与时变衰落信道时,该盲信道均衡器与基于扩展卡尔曼滤波算法的盲均衡器和基于无先导变换的自适应盲均衡器相比,有较好的均衡实现.此外,利用本文的盲均衡算法,实现了一种混沌调制通信系统的解调.