OFDM系统中抗非线性失真的迭代信道估计算法

针对OFDM系统中信号限幅滤波造成的信道估计性能下降,提出了一种基于梳状导频的迭代估计算法。该算法迭代估计信号中的非线性噪声,并据此补偿信号的非线性失真,提高信道再估计的性能。推导出了该算法在限幅预畸变系统中所能达到的理论均方误差下限,同时给出了初始信道估计的理论均方误差。仿真表明,该算法克服了由限幅滤波造成的性能瓶颈,且收敛速度快。与文献迭代信道估计算法相比,具有更强的抵抗峰均比抑制的能力。     

一种OFDM导频的信道估计算法的研究

提出了一种基于编码的OFDM系统的导频符号迭代辅助信道估计。利用信道解码器中的APP符号来形成虚拟的导频。与原有的信道估计算法相比,此种算法不仅在一般的信道条件下具有良好的性能,而且更加适合快变信道条件下的OFDM系统。仿真结果表明:提出的OFDM信道估计算法不仅可以给出精度较高的信道信息,而且近似达到EM信道估计的性能。     

基于信道估计的限幅OFDM信号检测性能分析

大峰均比是正交频分复用(OFDM)系统的主要缺陷之一，对时域OFDM信号限幅是通常采用的一种抑制发送信号峰值功率的方法，但是限幅产生的非线性干扰，使系统的信道估计和信号检测性能降低。本文分析了限幅干扰对信道估计以及基于估计信道信息的OFDM数据信号检测性能的影响，推导出了基于信道估计信号检测的信噪比与限幅参数之间的关系。利用信噪比和高斯信道的误符号率及误比特率公式，本文对频率选择性瑞利衰落信道环境限幅OFDM系统中信号的误符号率和误比特率进行估算。计算机仿真和估算的结果相吻合。     

OFDM系统中一种实用的干扰抑制信道估计算法

针对OFDM系统中IS信道估计在噪声消除和干扰抑制上的不足,提出一种干扰抑制信道估计算法.算法利用OFDM信号的时频二维特性,在LS信道估计基础上通过3次FFT/IFFT实现信道噪声消除和窄带干扰抑制,算法复杂度低,具有较好的工程可行性.算法仿真结果表明,这种干扰抑制的信道估计性能比传统LS信道估计在多径信道下的性能提升3 dB以上,在有窄带干扰的场景下系统性能损失在1.5 dB以内.     

PTS与限幅结合降低OFDM峰均比的改进算法

提出了一种基于部分传输序列(PTS)算法和限幅算法相结合的改进算法来降低正交频分复用(OFDM)系统的峰均功率比(PAPR).该算法先利用PTS算法对OFDM信号进行处理从而选择出限幅噪声最小的一路OFDM信号,所得OFDM信号再利用限幅法进行处理.因此可有效改善OFDM信号经过限幅引起的限幅噪声,减小限幅对OFDM系统的影响.数据仿真验证了所提方法的有效性.     

基于韦伯分布函数的低复杂度变步长符号算法

针对OFDM系统中传统信道估计算法在冲击噪声环境中性能急剧下降的问题,提出了一种基于韦伯分布函数的顽健型变步长符号算法进行信道估计。在深入研究冲击噪声特性及韦伯分布函数性质的基础上,提出了采用估计误差绝对值的韦伯分布函数控制步长的低复杂度变步长符号算法。该算法在利用传统符号算法顽健性的基础上,采用估计误差的韦伯分布函数动态地改变迭代符号算法的步长,从而能够以较低的复杂度提高变步长符号算法在冲击噪声环境中的收敛速度。算法复杂度分析及仿真结果表明,在冲击噪声环境下所提算法相较于传统自适应滤波信道估计算法能够以更低的复杂度、更快的收敛速度达到相同的信道估计均方误差。     

限幅OFDM系统中的判决辅助信道估计

在正交频分复用(OFDM)系统中，对基带时域信号限幅是通常采用的一种降低信号峰均比的方法，但是由限幅产生的非线性干扰使系统的信道估计和信号检测性能降低。本文针对OFDM系统的频域插值信道估计方案，分析了限幅对信道估计性能的影响，提出一种利用判决的信号辅助信道估计的方法，并分析了该方法为信道估计所能提供的最大信干比增益。理论分析和仿真结果表明这种方法能够提高信道估计的精度，从而提高信号检测的性能，降低接收机的误符号率。     

基于EM的联合信道参数估计和数据检测算法

为提高OFDM系统的传输效率，考虑正交频分复用（OFDM）系统的特殊结构，该文提出一种使用少量导频的EM（Expectation Maximization）迭代信道参数估计算法。在每次迭代中不但更新信道冲激响应而且更新噪声方差的估计值。为进一步提高算法的收敛速度，提出联合信道参数估计和数据检测算法。仿真结果表明，在插入较少导频时，基于EM的信道估计算法仍能收敛到给定参数的信道，联合信道参数估计和数据检测算法迭代次数明显减少，并且保持系统的误码率性能不变。     

MIMO-OFDM系统中一种新的联合迭代信道估计与符号检测算法

该文提出了一种MIMO-OFDM系统中基于MMSE准则的联合迭代信道估计和符号检测算法.联合迭代算法的性能取决于初始信道估计器的精度和迭代算法.首先提出了一种基于时频变换(TFT)的信道估计算法;其次提出了利用初始信道估计值与检测符号在MMSE准则下进行联合迭代信道估计和符号检测的算法.分析和仿真结果显示,在准静态和快时变信道条件下,新的联合迭代信道估计和符号检测算法有效地提高了系统性能.     

基于预测的OFDM系统迭代联合信道估计与符号检测算法

该文在现有的OFDM系统联合迭代信道估计与符号检测算法的基础上,根据信道响应的时域相关性,将预测方法引入迭代信道估计,对其进行改进。提出一类基于对初始信道估计值进行预测的迭代信道估计算法。进而分别用两种预测方法进行仿真并与传统迭代算法进行比较。仿真结果表明:该方法与传统算法相比,加快了迭代收敛速度,降低了系统误码率。在复杂度增加不大的前提下,提高了系统性能。     

Clipping noise mitigation for channel estimation in OFDM systems

This letter provides a new technique to mitigate the clipping noise on pilot symbols in clipped and pilot-aided orthogonal frequency division multiplexing (OFDM) systems. The basic principle is to directly filter the clipping noise on the positions of pilots in the frequency domain before the insertion of pilots. Simulation results show that the new technique can effectively improve channel estimation and system performance.     

MIMO-OFDM系统中限幅噪声的降低

MIMO-OFDM技术已成目前第四代移动通信的核心技术,而当MIMO-OFDM系统应用于高速移动快衰落环境中时,由于限幅产生的限幅噪声将导致信道估计性能的严重下降,提出了在快速移动衰落环境下,减弱梳状导频位置处限幅噪声的一种新方法,其基本原理是插入导频前在频域内把导频位置的限幅噪声直接滤除。仿真结果表明这种新的方法能有效的改善信道估计和系统的性能。     

Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet

Due to the characteristics of the underwater acoustic channel especially the limited bandwidth, orthogonal frequency division multiplexing (OFDM) is widely used because of its high spectrum efficiency and ability in anti-multipath fading. However OFDM also has its drawbacks, one of which is the relatively high peak-to-average ratio (PAPR). The problem leads to saturation in the power amplifier and consequently distorts the signal which is not allowed in the underwater acoustic communication. Clipping as the most classic and convenience way is widely applied to address the high PAPR. However, it introduces additional noise that degrades the system performance. In this paper compressed sensing (CS) technique is proposed to mitigate the clipping noise. The scheme exploited pilot tones and data tones instead of reserved tones, which is different from the previous works and causes less loss of data rate. Also, in contrast with previous works, to minimizing the influence of underwater acoustic channel, compressed sensing in channel estimating is also adopted during mitigating the clipping noise, which can provide more accurate channel characteristics for estimating the clipping noise than traditional method such as LS or MMSE. The iterative CS technology proposed in this article can significantly improve the communication quality even in low SNR.     

Subspace-based blind and semi-blind channel estimation for OFDMsystems

This paper proposes a new blind channel estimation method for orthogonal frequency division multiplexing (OFDM) systems. The algorithm makes use of the redundancy introduced by the cyclic prefix to identify the channel based on a subspace approach. Thus, the proposed method does not require any modification of the transmitter and applies to most existing OFDM systems. Semi-blind procedures taking advantage of training data are also proposed. These can be training symbols or pilot tones, the latter being used for solving the intrinsic indetermination of blind channel estimation. Identifiability results are provided, showing that in the (theoretical) situation where channel zeros are located on subcarriers, the algorithm does not ensure uniqueness of the channel estimation, unless the full noise subspace is considered. Simulations comparing the proposed method with a decision-directed channel estimator finally illustrates the performance of the proposed algorithm     

Iterative decision‐directed estimation and compensation of nonlinear distortion effects for OFDM systems

Orthogonal frequency division multiplexing (OFDM) has been adopted for several wireless network standards due to its robustness against multipath fading. Main drawback of OFDM is its high peak‐to‐average power ratio (PAPR) that causes a signal degradation in a peak‐limiting (e.g., clipping) channel leading to a higher bit error rate (BER). At the receiver end, the effect of peak limitation can be removed to some extent to improve the system performance. In this paper, a joint iterative channel estimation/equalization and clipping noise reduction technique based on minimum mean square error (MMSE) criterion is presented. The equalization weight that minimizes the mean square error (MSE) between the signal after channel equalization and feedback signal after clipping noise reduction is derived assuming imperfect channel state information (CSI). The MSE performance of the proposed technique is theoretically evaluated. It is shown that the BER performance of OFDM with proposed technique can be significantly improved in a peak‐limited and doubly‐selective (i.e., time‐ and frequency‐selective) fading channel. Copyright © 2011 John Wiley & Sons, Ltd.     

Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems

The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.     

OFDM叠加导频联合信道估计和检测方法

针对现有正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)系统信道估计和迭代检测算法中频谱效率低和鲁棒性差等问题,提出了一种基于酉近似消息传递和叠加导频的信道估计与联合检测方法。首先,在软调制/解调中叠加导频对正交幅度调制的星座点进行预处理,检测时将叠加的导频作为频域符号的先验分布,利用置信传播算法进行调制和解调,实现检测模型的简化。然后,应用因子图-消息传递算法对OFDM传输系统和信道进行建模和全局优化,引入酉变换加强信道估计算法的鲁棒性。最后,建立OFDM仿真环境对现有方法进行仿真分析。仿真结果表明,相对于现有的独立导频类算法,所提算法能够以相同复杂度显著提升OFDM系统的频谱效率和鲁棒性。     

Joint channel and phase noise estimation in OFDM systems at very high speeds

In this paper, the problem of joint phase noise and channel estimation for OFDM systems over a fast time-varying frequency-selective channel is explored. Each channel tap time-variation within one OFDM symbol is approximated by a Basis Expansion Model (BEM). Joint estimation is performed on multiple OFDM symbols via the Extended Kalman Filtering in order to exploit the time-correlation of the parameters. The data symbols are estimated by means of an iterative pilot-based algorithm. It is shown that, with only 2 iterations, our algorithm outperforms the conventional one, and the performance approaches that of the ideal case for which the channel response and phase noise are known.