Multichannel Estimation and Equalization Algorithm for Asynchronous Uplink DS/CDMA

This paper addresses the problem of channel estimation andequalization in asynchronous uplink DS/CDMA. We propose a completereceiver structure which contains a multichannel estimator suitablefor time-varying channels, a MMSE equalizer and a propagation delayestimator. The multichannel estimator is a stochastic gradientalgorithm which does not require any knowledge about the propagationdelays. It estimates a matrix which contains a linear combination ofthe impulse response of each channel and the propagation delays. Thisestimate is used to derive a MMSE equalizer. In the despreading stageknowledge on the integer part (chip period multiple) of thepropagation delays is needed. Two reduced complexity schemes forpropagation delay estimation are presented. The channel estimatorconvergence is studied in stationary conditions while the overallalgorithm performance is demonstrated by using simulations intime-varying channel conditions.     

Performance analysis of Godard-based blind channel identification

We analyze a blind channel impulse response identification scheme based on the cross correlation of blind symbol estimates with the received signal. The symbol estimates specified are those minimizing the Godard (1980) (or constant modulus) criterion, for which mean-squared symbol estimation error bounds have been derived. We derive upper bounds for the average squared parameter estimation error (ASPE) of the blind identification scheme that depend on the mean-squared error of the Wiener equalizer, the kurtoses of the desired and interfering sources, and the channel impulse response. The effects of finite data length and stochastic gradient equalizer design on ASPE are also investigated. All results are derived in a general multiuser vector-channel context     

一种基于回波数据的机载雷达通道均衡的方法

 提出了一种适用于机载雷达的基于回波数据的通道频率响应均衡的方法.该方法从参考通道和待均衡通道中选取一组高相关性的回波,分别作为期望信号和均衡器输入,借助维纳滤波方法估计均衡器系数;理论分析表明,在杂噪比足够高的情况下,该均衡器响应逼近于实际的通道失配误差.无须改装现有的雷达设备,该方法就可以对馈线和接收机的失配一并进行均衡.实测数据实验验证了该方法有效性.     

On the least-squares performance of a novel efficient center estimation method for clustering-based MLSE equalization

Recently, a novel maximum-likelihood sequence estimation (MLSE) equalizer was reported that avoids the explicit estimation of the channel impulse response. Instead, it is based on the fact that the (noise-free) channel outputs, needed by the Viterbi algorithm, coincide with the points around which the received (noisy) samples are clustered and can thus be estimated directly with the aid of a supervised clustering method. Moreover, this is achieved in a computationally efficient manner that exploits the channel linearity and the symmetries underlying the transmitted signal constellation. The resulting computational savings over the conventional MLSE equalization scheme are significant even in the case of relatively short channels where MLSE equalization is practically applicable. It was demonstrated, via simulations, that the performance of this algorithm is close to that using a least-squares (LS) channel estimator, although its computational complexity is even lower than that of the least-mean squares (LMS)-trained MLSE equalizer. This paper investigates the relationship of the center estimation (CE) part of the proposed equalizer with the LS method. It is proved that, when using LS with the training sequence employed by CE, the two methods lead to the same solution. However, when LS is trained with random data, it outperforms CE, with the performance difference being proportional to the channel length. A modified CE method, called MCE, is thus developed, that attains the performance of LS with perfectly random data, while still being much simpler computationally than classical LS estimation. Through the results of this paper, CE is confirmed as a methodology that combines high performance, simplicity, and low computational cost, as required in a practical equalization task. An alternative, algebraic viewpoint on the CE method is also provided.     

Blind channel estimation via combining autocorrelation and blind phase estimation

Symbol spaced blind channel estimation methods are presented which can essentially use the results of any existing blind equalization method to provide a blind channel estimate of the channel. Blind equalizer's task is reduced to only phase equalization (or identification) as the channel autocorrelation is used to obtain the amplitude response of the channel. Hence, when coupled with simple algorithms such as the constant modulus algorithm (CMA) these methods at baud rate processing provide alternatives to blind channel estimation algorithms that use explicit higher order statistics (HOS) or second-order statistics (subspace) based fractionally-spaced/multichannel algorithms. The proposed methods use finite impulse response (FIR) filter linear receiver equalizer or matched filter receiver based infinite impulse response+FIR linear cascade equalizer configurations to obtain blind channel estimates. It is shown that the utilization of channel autocorrelation information together with blind phase identification of the CMA is very effective to obtain blind channel estimation. The idea of combining estimated channel autocorrelation with blind phase estimation can further be extended to improve the HOS based blind channel estimators in a way that the quality of estimates are improved.     

Performance analysis of a single-user MISO ultra-wideband time reversal system with DFE

This paper presents an analysis of the performance of a baseband multiple-input single-output (MISO) time reversal ultra-wideband system (TR-UWB) incorporating a symbol spaced decision feedback equalizer (DFE). A semi-analytical performance analysis based on a Gaussian approach is considered, which matched well with simulation results, even for the DFE case. The channel model adopted is based on the IEEE 802.15.3a model, considering correlated shadowing across antenna elements. In order to provide a more realistic analysis, channel estimation errors are considered for the design of the TR filter. A guideline for the choice of equalizer length is provided. The results show that the system’s performance improves with an increase in the number of transmit antennas and when a symbol spaced equalizer is used with a relatively small number of taps compared to the number of resolvable paths in the channel impulse response. Moreover, it is possible to conclude that due to the time reversal scheme, the error propagation in the DFE does not play a role in the system’s performance.     

信息管理中UWB系统信道估计与均衡算法及实现

通过介绍UWB技术的发展现状,着重阐述了MB-OFDM UWB通信系统的物理层帧结构和信道模型。在分析最小二乘(LS)信道估计算法和基于快速傅里叶变换(FFT)信道估计算法的基础上,针对MB-OFDM UWB信号帧结构特征提出了一种基于FFT变换和Hannan-Quinn(HQ)准则的改进算法,即FFT-HQ信道估计算法。该文也提出了一种基于信道估计的自适应均衡算法,利用仿真可以看出此均衡算法在性能上优于传统的基于LS算法调整均衡器系数的方法。     

Modeling of non-line-of-sight ultraviolet scattering channels for communication

A stochastic non-line-of-sight (NLOS) ultraviolet (UV) communication channel model is developed using a Monte Carlo simulation method based on photon tracing. The expected channel impulse response is obtained by computing photon arrival probabilities and associated propagation delay at the receiver. This method captures the multiple scattering effects of UV signal propagation in the atmosphere, and relaxes the assumptions of single scattering theory. The proposed model has a clear advantage in reliable prediction of NLOS path loss, as validated by outdoor experiments at small to medium elevation angles. A Gamma function is shown to agree well with the predicted impulse response, and this provides a simple means to determine the channel bandwidth. The developed model is employed to study the characteristics of NLOS UV scattering channels, including path loss and channel bandwidth, for a variety of scattering conditions, source wavelength, transmitter and receiver optical pointing geometries, and range.     

Adaptive equalization of CPM signals transmitted over fast Rayleighflat-fading channels

A new algorithm for adapting the coefficients of an equalizer for continuous phase modulated data signals in a flat-fading environment is presented. The cost function to optimize is based on the maximum likelihood sequence estimation index for such signals and channel conditions. It is shown that this equalizer algorithm, called the maximum likelihood equalizer, involves the iterative computation of one of the eigenvectors of a matrix. An implementation is proposed, which combines iterative estimation procedures for QR decomposition, matrix eigenvalue tracking and channel prediction error. Simulation results are presented that demonstrate the ability of the algorithm to equalize the channel filtering effects in a fast fading environment, without requiring phase coherent carrier recovery     

隐含训练序列信道估计中的功率分配

与传统时分发送训练序列的信道估计算法相比,隐含训练序列信道估计算法将训练序列与信息序列直接相加后通过天线发送,从而节约了信道带宽。然而,在天线发送总功率一定时,训练序列的功率越大,信息序列的功率便越小,从而导致信道均衡器的信噪比减小。本文研究了基于MIMO系统的隐含训练序列信道估计算法,分析了信道均衡器信噪比与训练序列功率的关系,并根据均衡器信噪比最大原则推导出训练序列与信息序列的最佳功率分配。分析和仿真结果表明：在训练序列的最佳功率点上,信道均衡器的信噪比最高;随着接收天线信噪比的增加,训练序列的最佳功率增大。     

DFT-S-OFDM系统中基于DFT的软迭代信道估计

在基于傅里叶变换扩展的正交频分复用（DFT-S-OFDM）系统中,为了消除由多径传播和多普勒效应导致的信道间干扰（ICI）,提出了一种基于离散傅里叶变换（DFT）的软迭代信道估计算法。该算法将传统DFT信道估计技术与Turbo均衡技术相结合,利用Turbo均衡器反馈的软信息来更新初始信道估计响应,进而消除噪声和ICI。Matlab仿真结果表明,在多径信道下,经过2次以上的迭代后,该算法的误码率（BER）性能得到了显著的改善。     

正交频分复用信道估计的隐藏导频法

正交频分复用系统具有简单的单抽头频域均衡，在均衡之前需要完成信道估计。本文提出一种基于隐藏导频序列的信道估计方法，只要利用接收信号一阶统计信息就可估计出信道信息。这种半盲的信道估计方法具有简单的信道估计和均衡，而且不占用频谱资源。仿真结果表明本方法能有效进行信道估计，并得到了隐藏序列的最佳能量值。     

A channel estimation using sliding window approach and tuningalgorithm for MLSE

A simultaneous sliding window channel estimation and timing adjustment method is proposed for adaptive maximum-likelihood sequence equalizer (MLSE) in the global system for mobile communication (GSM) system, and also a tuning scheme based on least mean squared (LMS) algorithm is presented in order to improve the performance of equalizer. Simulation results show that the proposed channel estimation technique is effective for channel estimation of the adaptive equalizer     

MUI-free receiver for a synchronous DS-CDMA system based on blockspreading in the presence of frequency-selective fading

We discuss a synchronous direct-sequence code division multiple-access (DS-CDMA) system based on block spreading in the presence of frequency-selective fading. Note that block spreading, which is also known as chip interleaving, refers to a spreading of a data block sequence, which is obtained by dividing a data symbol sequence into consecutive blocks. For such a system, we develop a simple new receiver that completely removes the multiuser interference (MUI) without using any channel information. The MUI-free operation is obtained by the use of a shift-orthogonal set of code sequences on which this receiver is based. Within the framework of the MUI-free receiver, we further present a subspace deterministic blind single-user channel estimation algorithm. As a benchmark for the MUI-free receiver and the corresponding subspace deterministic blind single-user channel estimation algorithm, we consider the linear multiuser equalizer and the corresponding subspace deterministic blind multiuser channel estimation algorithm developed by Liu and Xu (1996) for a standard synchronous DS-CDMA system in the presence of frequency-selective fading. We show that the complexity of the MUI-free receiver using the corresponding subspace deterministic blind single-user channel estimation algorithm is much smaller than the complexity of the linear multiuser equalizer using the corresponding subspace deterministic blind multiuser channel estimation algorithm. We further show that the performance of the MUI-free receiver is comparable with the performance of the linear multiuser equalizer. This is for the case in which the channels are known as well as for the case in which the channels are estimated with the corresponding subspace deterministic blind channel estimation algorithm     

A novel expression for the achievable MSE performance obtained by blind adaptive equalizers

In this paper, I propose for the noisy, real, and two independent quadrature carrier case, an approximated closed-form expression for the achievable minimum mean square error (MSE) performance obtained by blind equalizers where the error that is fed into the adaptive mechanism which updates the equalizer’s taps can be expressed as a polynomial function of the equalized output of order three like in Godard’s algorithm. The proposed closed-form expression for the achievable MSE is based on the step-size parameter, on the equalizer’s tap length, on the channel power, on the signal to noise ratio (SNR), on the nature of the chosen equalizer, and on the input signal statistics. Since the channel power is measurable or can be calculated if the channel coefficients are given, there is no need anymore to carry out any simulation with various step-size parameters, different values for the signal to noise ratio (SNR) and equalizer’s tap length for a given equalization method, and input signal statistics in order to find the MSE performance in the convergence state.     

Reduced complexity in-phase/quadrature-phase M-QAM turbo equalization using iterative channel estimation

A reduced complexity trellis-based turbo equalizer known as the in-phase (I)/quadrature-phase (Q) turbo equalizer (TEQ-IQ) invoking iterative channel impulse response (CIR) estimation is proposed. The underlying principle of TEQ-IQ is based on equalizing the I and Q component of the transmitted signal independently. This requires the equalization of a reduced set of separate I and Q signal components in comparison to all of the possible I/Q phasor combinations considered by the conventional trellis-based equalizer. It was observed that the TEQ-IQ operating in conjunction with iterative CIR estimation was capable of achieving the same performance as the full-complexity conventional turbo equalizer (TEQ-CT) benefiting from perfect CIR information for both 4- and 16-quadrature amplitude modulation (QAM) transmissions, while attaining a complexity reduction factor of 1.1 and 12.2, respectively. For 64-QAM, the TEQ-CT receiver was too complex to be investigated by simulation. However, by assuming that only two turbo equalization iterations were required, which is the lowest possible number of iterations, the complexity of the TEQ-IQ was estimated to be a factor of 51.5 lower than that of the TEQ-CT. Furthermore, at BER = 10/sup -3/ the performance of the TEQ-IQ 64-QAM receiver using iterative CIR estimation was only 1.5 dB away from the associated decoding performance curve of the nondispersive Gaussian channel.     

MLSE and soft-output equalization for trellis-coded continuousphase modulation

This paper presents two equalizer structures for trellis-coded continuous phase modulation (TC-CPM) on multipath fading intersymbol interference (ISI) channels. An equivalent discrete-time (DT) model is developed by combining the tapped-delay-line (TDL) model of the frequency-selective channel and by oversampling at the receiver. The (noninterleaved) fractionally spaced maximum-likelihood sequence estimation (MLSE) equalizer performs continuous phase modulation (CPM) demodulation, trellis-coded modulation (TCM) decoding, and channel equalization by exploiting the finite state nature of the ISI-corrupted TC-CPM signal. Both simulation and analytical results show diversity-like improvement when performing joint MLSE decoding and equalization. For the interleaved soft-output equalizer, the soft symbol metric is delivered to the TCM decoder by using a forward and backward recursion algorithm. Three variants of the soft-output equalizer are examined. We conclude that the backward recursion is essential to partial response CPM schemes, and with moderate complexity, the soft-output equalizer can have a substantial advantage over a noninterleaved MLSE equalizer     

基于粒子滤波的OFDM载波频偏和信道联合估计

一种基于粒子滤波(PF)的正交频分复用(OFDM)系统在慢衰落瑞利信道下联合信道估计和载波恢复的新方法被提出。该算法适用于多径时变信道模型以及等效离散时间信道模型。算法引入了在非线性系统参数估计和跟踪领域上十分有效的PF方法,将Kaman滤波与序贯蒙特卡罗采样(SMCS)相结合来估计信道衰落系数以及载波频偏(CFO)的后验概率密度,从而通过计算得到信道的响应函数,并在此基础上,利用MMSE均衡器消除码间串扰(ICI),进行码元估计。仿真结果表明了算法的有效性和优越性。     

一种水声通信中的多阵元Turbo均衡算法

Turbo均衡应用在水声通信中的问题主要在于水声信道时间扩展长,多接收阵元处理复杂度较高。该文研究了将时间反转与马尔可夫链蒙特卡罗(MCMC)均衡联合优化算法用于实现Turbo均衡。首先进行时间反转实现多接收阵元较长多径时延的压缩,再利用白化滤波器解决时间反转造成的噪声模型失配问题,最后利用复杂度较低的MCMC均衡器结合软迭代信道估计对时间反转合并后得到的信号进行均衡。结合真实实验信道条件对信道响应估计的误差建立模型,通过仿真比较得出, 该算法在相同条件下相对于多阵元直接自适应Turbo均衡算法复杂度降低67%,且有1.6 dB的误码率性能增益。通过对湖上试验数据进行处理,进一步验证了该算法的优势。