基于小波的频率选择性瑞利衰落信道估计

频率选择性快衰落信道的精确估计对接收机性能的提高起着重要作用。本文采用小波基表示频率选择性快衰落信道，并由此提出两种估计时变信道的算法，瑞利快速衰落信道下的仿真结果表明，信道估计精度较之传统的LMS和RLS算法有明显提高。     

空间相关莱斯衰落信道下基于部分信道信息的多用户预编码与调度算法

在空间相关的莱斯衰落信道模型下,针对多用户MIMO(Multiple-Input Multiple-Output)系统潜在的多用户分集增益和空间分集增益,该文提出了一种基于部分信道信息的多用户预编码与调度算法。结合部分瞬时信道信息和统计信息,利用约束最大似然估计对各用户信道矢量进行估计,然后利用估计的各用户信道调度多个用户进行预编码。仿真结果表明,该方案以较少的反馈开销,获得了较大的性能增益。     

MIMO-OFDM系统的信道估计算法

基于训练序列的信道估计方法在慢衰落信道中呈现出较好的性能，但是这种方法不适用于快衰落环境，为了能够及时跟踪信道的变化，通常采用基于导频符号的信道估计方法。将针对采用连续传输方式的MIMO—OFDM系统，讨论基于导频符号的信道估计方法并进行了计算机仿真。     

STTC—OFDM系统中的导频辅助半盲信道估计

在快衰落信道情况下，基于判决指导信道估计（DDCE）法不能够很好的跟踪信道参数的变化，使得系统性能产生很大的恶化。在这篇论文中，为了防止在快衰落信道中由于信道估计误差带来STTC-OFDM系统性能恶化，我们在每帧除训练符号外的OFDM符号引入导频辅助半盲（APSB）信道估计技术。同时，为了简化系统，我们仅在每帧最后一个符号使用APSB信道估计技术。在本文的最后我们给出了一些结论。     

未知衰落信道中MPSK信号的非数据辅助载波频率估计方法

未知衰落信道中的MPSK信号的非数据辅助载波频率估计是通信参数估计中的复杂问题,目前尚缺乏有效的针对性研究成果.针对该问题,提出采用先补偿信道影响,再去调制,然后进行非衰落信道单频信号频率估计的方法.该方法比进行频率和信道冲激响应联合估计的方法简洁和高效,而且解决了联合估计中难以有效去调制的问题.通过和非衰落信道的频率...     

叠加训练序列OFDM系统的一种迭代信道估计方法

在瑞利多径衰落信道中，针对叠加训练序列正交频分复用系统的迭代接收机，提出了一种迭代信道估计方法．在迭代译码开始前，利用与数据符号同时发送的训序列得到信道估计初始值，并在每次迭代后利用更新的码字比特先验信息估计接收信号中的数据符号，计算更准确的信道估计值．理论分析给出了每次迭代后的信道估计值的均方误差性能．在多径衰落信道中，通过计算机仿真验证了该迭代信道估计方法的有效性和可靠性。     

WLAN OFDM系统信道估计技术

介绍了802．11a系统的信道估计技术，包括LS(最小平方)信道估计技术，维纳滤波器方法，以及它们的基本原理和主要算法．在802．11a系统的仿真平台上用LS和维纳滤波器方法分别对信道进行估计．仿真结果表明，对瑞利衰落信道，在相同的传输速率下，Wiener-Filter的信道估计比LS信道估计都有一定的性能提高。     

Nakagami衰落信道的信噪比估计及其在Turbo译码中的应用

在Turbo译码中，需要精确的信噪比信息来计算译码器生成的外信息，而在无线衰落信道中，Nakagami衰落信道具有通用性，文中对Summer信噪比估计算法进行了改进，使之能够应用于Nakagami衰落信道。最后，对应用了改进Summer信噪比约Turbo译码进行了性能仿真，从结果可以看出，改进的Summer信噪比估计算法能够成功应用到Turbo译码中，使得Turbo译码获得良好的性能。     

平衰落信道下ML和MAP信道估计与导频符号长度的关系性能比较

信道估计是无线通信系统必须加以解决的关键技术之一，采用导频符号辅助的方法进行信道估计是目前各类无线通信系统常用的方法。本文针对平衰落信道提出了最大似然(ML)算法和最大后验概率(MAP)估计算法，给出了ML估计和MAP估计之间的关系，仿真了MAP估计和ML估计的方差与导频符号长度的关系，提出当导频符号长度的取值超过20个符号长度时，MAP信道估计明显优于ML信道估计。     

WCDMA系统中结合导频与信息码的信道估计方法

研究了快衰落环境中第三代移动通信空中接口WCDMA(FDD),基于时分复用的导频信号辅助衰落信道下的信道估计。提出了同时根据导频信号及数据信号估计信道参数的信道估计方法,该方法将信道估计分为根据导频信号和数据信号两部分进行并由其加权合并完成。计算了最小均方误差下的合并系数。仿真结果表明该方法能快速跟踪信道的衰落,有效地估计出各时隙中数据段的信道参数。利用该算法,尤其在高速运动情况下,接收机的性能可得到显著的改善。     

Analysis of LMS-adaptive MLSE equalization on multipath fadingchannels

We consider a practical maximum-likelihood sequence estimation (MLSE) equalizer on multipath fading channels in conjunction with an adaptive channel estimator consisting of a least mean square (LMS) estimator and a linear channel predictor, instead of assuming perfect channel estimates. A new LMS estimator model is proposed which can accurately characterize the statistical behavior of the LMS estimator over multipath fading channels. Based on this model, a new upper-bound on block error rate is derived under the consideration of imperfect channel estimates. Computer simulations verify that our analytical results can correctly predict the real system performance and are applicable over a wide range of the step size parameter of the LMS estimator     

Channel estimation and long-range prediction of fast fading channels for adaptive OFDM system

This correspondence presents the channel estimation and long-range prediction technique for adaptive-orthogonal-frequency-division-multiplexing (AOFDM) system. The efficient channel loading is accomplished by feeding the accurately predicted channel-state-information (CSI) back to transmitter. The frequency-selective wireless fading channel is modelled as a tapped-delay-line-filter governed by a first-order autoregressive (AR1) process; and an adaptive channel estimator based on the generalised-variable-step-size least-mean-square (GVSS-LMS) algorithm tracks AR1 correlation coefficient. To compensate for the signal fading due to channel state variations, a modified-Kalman-filter (MKF)-based channel estimator is utilised. In addition, channel tracking is also performed for predicting future CSI at receiver, based on the numeric-variable-forgetting-factor recursive-least-squares (NVFF-RLS) algorithm. Subsequently, adaptive bit allocation for AOFDM system is employed by using predicted CSI at transmitter. Here, the proposed combination of GVSS-LMS and MKF algorithms for robust channel estimation and the NVFF-RLS algorithm for efficient channel prediction is incorporated. The performance validation of presented method is carried out by using different channel realisations through simulation, and also by comparing it with fixed step-size LMS, MKF and fixed forgetting-factor RLS algorithm based conventional techniques. Eventually, the reliable performance of underlying AOFDM system can be achieved in terms of the lower mean squared estimation/prediction errors and alleviated symbol error rate.     

在脉冲噪声环境中用于快衰信道估计的改进型算法

该文分析了在存在噪声干扰的情况下,进行估计快衰信道的方法。在无线通信系统中,快衰信道可以采用AR(Auto-Regressive)模型进行预测,而LS (Least Square)算法和自适应Kalman滤波器可以分别对AR模型的参数和信道的冲激响应进行估计,但是这两种算法对噪声干扰非常敏感。该文提出改进型的RLM算法和Kalman 滤波器,并在存在噪声的情况下,使用它们并行对AR参数和信道的冲激响应进行联合估计。仿真结果显示:相比于传统的算法,改进后的算法在联合估计信道时,提高了抵抗大脉冲干扰的能力,加快了待估的参数的收敛速度。     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

Performance of adaptive MC-CDMA detectors in rapidly fading Rayleigh channels

Multicarrier code-division multiple access (MC-CDMA) combines multicarrier transmission with direct sequence spread spectrum. Different approaches have been adopted which do not assume a perfectly known channel. We examine the forward-link performance of decision-directed adaptive detection schemes, with and without explicit channel estimation, for MC-CDMA systems operating in fast fading channels. We analyze theoretically the impact of channel estimation errors by first considering a simpler system employing a threshold orthogonality restoring combining (TORC) detector with a Kalman channel estimator. We show that the performance deteriorates significantly as the channel fading rate increases and that the fading rate affects the selection of system parameters. We examine the performance of more realistic schemes based on the minimum mean square error (MMSE) criterion using least mean square (LMS) and recursive least square (RLS) adaptation. We present a discussion which compares the decision-directed and pilot-aided approaches and explores the tradeoffs between channel estimation overhead and performance. We find that there is a fading rate range where each method provides a good tradeoff between performance and overhead. We conclude that the MMSE per carrier decision-directed detector with RLS estimation combines good performance in low to moderate fading rates, robustness in parameter variations, and relatively low complexity and overhead. For higher fading rates, however, only pilot-symbol-aided detectors are appropriate.     

Parameter Estimation for Correlated MIMO Channels with Frequency-Selective Fading

In this paper, we address the problem of frequency offset and channel gain estimation for frequency-selective multi-input multi-output (MIMO) correlated fading channels. A maximum-likelihood (ML) frequency offset (FO) estimator is proposed by using the Bayesian approach. We show that the proposed FO estimator is efficient and asymptotically optimal. Based on the FO estimate, we derive the linear minimum mean square error (LMMSE) channel estimator and analytically investigate the effect of frequency offset estimation error on the mean square error (MSE) performance of the channel estimator. Finally, the performances of the FO and channel estimation are evaluated by simulation results.     

OFDM分集接收系统上行链路信道估计研究

对采用时频块组帧的OFDM(正交频分复用)上行链路信道估计进行了研究,给出了基于二维DFT(离散傅里叶变换)的信道估计算法,针对传统二维信道估计方法的边缘效应提出了一种改进办法,即采用分块拟合的方法对信道曲面边缘部分进行补偿估计。仿真表明,改进的二维DFT信道估计方法可以有效地消减边缘效应,从而获得更好的系统性能。     

Robust channel estimation for OFDM systems with rapid dispersivefading channels

Orthogonal frequency-division multiplexing (OFDM) modulation is a promising technique for achieving the high bit rates required for a wireless multimedia service. Without channel estimation and tracking, OFDM systems have to use differential phase-shift keying (DPSK), which has a 3-dB signal-to-noise ratio (SNR) loss compared with coherent phase-shift keying (PSK). To improve the performance of OFDM systems by using coherent PSK, we investigate robust channel estimation for OFDM systems. We derive a minimum mean-square-error (MMSE) channel estimator, which makes full use of the time- and frequency-domain correlations of the frequency response of time-varying dispersive fading channels. Since the channel statistics are usually unknown, we also analyze the mismatch of the estimator-to-channel statistics and propose a robust channel estimator that is insensitive to the channel statistics. The robust channel estimator can significantly improve the performance of OFDM systems in a rapid dispersive fading channel     

Parallel Interference Cancellation in Multiuser CDMA Channel Estimation

Parallel interference cancellation (PIC) based channel parameter estimators for frequency selective fading channels are proposed for the uplink in code-division multiple-access (CDMA) mobile communication systems. The performance of PIC based algorithms depends heavily on the quality of the multiple-access interference estimates, which can be improved by using adaptive channel estimation filters. The performance of two adaptive complex channel coefficient estimation filters has been verified in a fading channel by computer simulations. According to the results, the PIC based adaptive channel estimators outperform clearly conventional, successive interference cancellation, and decorrelation based adaptive channel estimators. The PIC method is also used in delay tracking. By using the principles of sample-correlate-choose-largest (SCCL) delay trackers, a robust algorithm for multiuser delay tracking in fading channels is obtained.     

Soft Decoding Assisted SNR Estimation Under Block Fading Channels for Orthogonal Modulations

The performance of the coded orthogonal modulation (OM) system under slow fading channels heavily depends on the estimation of the signal-to-noise ratio (SNR), including the fading amplitude and the noise spectral density. However, a relatively long packet of pilot symbols is often required to guarantee the accuracy of the SNR estimation, which makes it impractical in some situations. To address this problem, this paper proposes an iterative SNR estimation algorithm using the soft decoding information based on the expectation-maximization algorithm. In the proposed method, a joint iterative loop between the SNR estimator and decoder is performed, where the extrinsic information generated by the soft decoder is employed to enhance the estimation accuracy and the SNR estimated by the estimator is used to generate the soft information to the decoder. Also, no pilot symbols are needed to estimate the SNR in the proposed estimator. The Cramer–Rao lower bound (CRLB) of fully data-aided (FDA) estimation is derived to works as the final benchmark. The performance of the proposed algorithm is evaluated in terms of the normalized mean square errors (NMSEs) and the bit error rates (BERs) under block fading channels. Simulation results indicate that the NMSE of the proposed estimator reaches the CRLB of the FDA estimator and outperforms that of the approximate ML (ML-A) estimator proposed by Hassan et al. by 4.1 dB. The BER performance of coded OM system with the proposed estimation algorithm is close to the ideal case where the channel fading and the noise spectral density are known at the receiver.