一种改进的OFDM盲信道估计算法研究

信道估计在无线OFDM系统中至关重要,现有的盲信道估计算法中存在计算复杂度高、精度低的缺点。研究了一种改进的适用于SISO-OFDM系统的非冗余预编码的盲信道估计算法。在改进的算法中,由于采用幂法获得主特征值取代了原有采用特征值分解,使复杂度大大降低。仿真结果表明,改进的算法性能优于原有的基于预编码的盲信道估计算法。     

MIMO-OFDM中基于系统分解的VC子空间盲信道估计快速算法

研究MIMO-OFDM系统中的盲信道估计问题。将OFDM系统中的子空间盲信道估计方法引入到MIMO-OFDM系统中,建立了带有虚拟载波的系统数据传输模型。针对MIMO-OFDM系统VC子空间盲信道估计算法复杂度高的特点,提出了一种该算法下基于系统分解的快速方法。仿真实验结果表明,算法在RMSE性能上稍差于原算法,但却显著降低了信道估计算法的复杂度,对快速信道估计应用方面具有一定的指导意义。     

一种基于期望最大化的OFDM半盲信道估计算法

提出了一种OFDM半盲信道估计算法。传统的OFDM系统信道估计是依赖于训练序列，但是在无线通信系统中，运用半盲信道估计的性能和灵活性更好。在无线局域网的5GHz频宽的OFDM背景下，利用EM算法仿真，结果表明该算法的SNR与传统训练序列信道估计比较提高了2dB。     

强单音干扰下短波OFDM信道估计算法

文章针对接收端存在强单音干扰的场景,基于短波Watterson信道模型,对所提出的具有干扰抑制能力的短波OFDM系统信道估计算法进行了仿真评估,比较了在不同干扰强度下算法的系统误码性能。仿真表明：这种基于干扰抑制消除的信道估计算法有效降低了系统误码率,提高了系统性能。     

基于OFDM信号周期平稳特性的盲信道估计算法

该文提出一种基于信号周期平稳特性的盲信道估计算法,用于频率选择性衰落环境下的正交频分复用(OFDM)系统。该算法利用OFDM信号本身具有的周期平稳特性以及其周期自相关函数值的能量分布规律,确定信道阶数,并通过确定信道零点的方法间接获得信道冲激响应。理论和仿真结果表明,与其它的盲信道估计算法相比,该算法不仅可以较准确地获得信道阶数,而且降低了信道估计的均方误差。     

射频干扰环境下OFDM系统的盲信号干扰噪声比估计

基于OFDM信号的循环平稳特性,提出一种在射频干扰环境下OFDM系统的盲信号干扰噪声比估计方法。通过分析发送信号,射频干扰信号以及高斯白噪声的周期自相关函数能量分布规律,选取合适的延时变量和循环频率在功率谱域能有效分离信号功率和干扰加噪声功率分量,从而估计出信号干扰噪声比值。计算机仿真结果表明,和经典的二阶四阶矩(M2M4, second-order and fourth-order moments)盲信号干扰噪声比估计方法相比,新方法不仅能够有效估计射频干扰环境下OFDM系统的信号干扰噪声比值,而且无论是估计性能还是复杂度都优于M2M4方法;同时在快衰落Rayleigh信道下,新方法也能有效的估计出信号干扰噪声比值。进一步,所提方法具有对射频干扰信号密度不敏感的优点。     

OFDM系统中基于恒模的盲信道估计算法

该文提出了一种适用于采用PSK调制方式的正交频分复用(OFDM)系统的准盲信道估计算法。该算法首先利用系统信号的恒模特性得到有限个可能的信道,然后利用信号的有限字符特性从可能信道中寻找出最佳信道,因而具有较低的计算复杂度。与现有的盲信道估计算法不同,该算法利用二阶统计量而不是高阶统计量估计信道,获得了较好的估计性能。仿真结果表明,该算法的性能优于基于有限字符特性的盲信道估计算法。     

一种基于ML算法及盲信道识别的DWPM系统

该文提出了一种基于ML算法及盲信道估计的离散小波包调制(Discrete Wavelet Packet Modulation,DWPM)系统.本文通过基于导频信号的盲信道识别方法,获得信道的状态信息,并且利用基于ZF(Zero Forcing)算法的H矩阵消除码间干扰,最后,利用ML(Maximum Likelihood)算法检测解调后的码元,并且通过仿真分析了该系统在多径衰落信道下的性能.仿真结果表明,该系统的性能要比传统的OFDM系统的性能好.     

MIMO-OFDM系统中的信道估计算法

本文对MIMO—OFDM系统中的信道估计技术进行了介绍,根据是否使用训练序列,信道估计可以分为导频辅助信道估计、盲信道估计及半盲信道估计,本文分别对已有的信道估计算法进行了综述,并对一种已有的基于m序列的时域信道估计方法进行了改进。     

一种新的MIMO—OFDM系统的盲信道估计算法

深入分析了基于二阶统计特性的子空间盲信道估计算法,在分析得出MIMO—OFDM系统中的子空间盲信道估计方法不能用在发射天线数大于接收天线数这种情况下,引出了基于非冗余线性预编码的子空间盲估计算法。仿真结果表明,只要尸的取值合适,该算法就会有着很好的估计性能,并且通过分析发现,该算法的计算复杂度较小。     

MIMO-OFDM系统中信道盲估计与检测

针对MIMO-OFDM系统,提出了一种基于子空间的盲信道估计与检测方案,该算法将阵列信号处理的思想应用到MIMO-OFDM系统中,通过发送端信号的冗余编码,利用一种类ESPRIT算法进行盲信号检测和信道估计。仿真结果表明该算法的有效性及其信道盲估计方法的性能。     

OFDM系统中的盲信道估计

本文从OFDM信号的矩阵表示出发,分析比较了OFDM系统中现有的各种盲信道估计方法。OFDM盲信道估计方法分为两类,一类是统计型方法,它利用了发送信号和接收信号的统计特性;另一类是确定型方法,它利用了发送调制信号的固有特性。一般而言,统计型方法的计算量较小,但是估计精度不高且估计的实时性不好;而确定型方法的估计精度较高,实时性较好,但是其计算量较大。计算机仿真表明,这些盲信道估计方法的性能受信道参数尤其是多普勒频率影响很大,盲信道估计的实用化有待进一步研究。     

Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction

Aiming at the problem that in the current electromagnetic environment,the modulation method is complicated,the frequency-consuming equipment increases,the spectrum is congested,and the electromagnetic environment interference increases,the algorithm of OFDM signal detection and subcarrier identification in the background of non-cooperative communication were deeply studied.Using the different distribution states of OFDM signals and single carrier signals in the time domain,a joint characteristic parameter was proposed to solve the existence problem of OFDM in the received signal.For the phase shift and frequency offset problems caused by the channel transmission to the signal,by using the periodic stability the blind parameter estimation was performed to obtain the signal prior information.On the basis of the obtained signal prior information,a multi-level classification and recognition method for non-cooperative OFDM signal sub-carrier signals was proposed.Therefore,a model based on non-cooperative communication system OFDM signal detection and subcarrier modulation identification was designed,and finally modulation identification of unknown signals was completed.Simulation experiments show that in non-cooperative communication systems,OFDM signals and single-carrier signals can be accurately identified,and ideal modulation recognition effects can be achieved on empty subcarriers,QPSK,and 16QAM in the receiver OFDM signal subcarriers,overcoming the channel transmission band The problems of phase shift and frequency offset have improved the accuracy of modulation mode identification.     

认知无线电中OFDM信号信噪比盲估计

针对认知正交频分复用(OFDM,orthogonal frequency division multiplexing)系统中低信噪比多径信道下传统的OFDM信号信噪比盲估计算法的估计性能差,计算复杂度高的问题,提出一种新的OFDM信号信噪比盲估计方法,该方法首先利用自相关函数的特性粗略估计出信道阶数,确定循环前缀部分中不受符号间干扰的数据区间,然后根据选定区间的数据的自相关函数值估计接收信号的信号功率,最后利用循环前缀数据为部分有用数据的复制这一特性估计出噪声功率,从而估计出接收信号的信噪比。仿真实验结果表明,提出的方法无需任何先验信息,在低信噪比多径信道下具有良好的估计性能,且计算复杂度低,更适合于认知OFDM系统。     

OFDM系统中盲、半盲以及非盲信道估计方法的Cramér-Rao界

从OFDM信号系统的矩阵表示出发，推导了OFDM系统中盲、半盲以及非盲信道估计方法的CRB，其中，半盲信道估计的CRB是一般的表达式，经过外推可以得到盲信道估计和非盲信道估计的CRB。在推导盲信道估计的CRB时，证明了线性约束和二次约束两种情况下的CRB是一致的。针对OFDM系统的两种不同方案CP-OFDM和ZP-OFDM，分别进行了信道估计的性能仿真，验证了所推导CRB的正确性，并且利用CRB对一些信道估计方法进行了性能评价。     

OFDM系统中盲、半盲以及非盲信道估计方法的Cramér-Rao界

从OFDM信号系统的矩阵表示出发,推导了OFDM系统中盲、半盲以及非盲信道估计方法的CRB,其中,半盲信道估计的CRB是一般的表达式,经过外推可以得到盲信道估计和非盲信道估计的CRB。在推导盲信道估计的CRB时,证明了线性约束和二次约束两种情况下的CRB是一致的。针对OFDM系统的两种不同方案CP-OFDM和ZP-OFDM,分别进行了信道估计的性能仿真,验证了所推导CRB的正确性,并且利用CRB对一些信道估计方法进行了性能评价。     

Linear precoding assisted blind channel estimation for OFDM systems

We propose a novel precoding approach for single transmit/receiver antenna orthogonal frequency-division multiplexing (OFDM) systems that enables blind channel estimation. A nonredundant nonunitary linear precoder is applied on each pair of blocks before they enter the OFDM system. The structure induced to the transmitted blocks allows for blind channel estimation at the receiver based on simple cross-correlation operations. At the same time, the multipath diversity of the system is increased. An optimal precoding scheme is pursued that, for quadrature phase-shift keying signals results in minimum channel error and asymptotically minimum bit error rate. Analytic performance evaluation of the proposed approach, and Cramer-Rao bound for the proposed channel estimate, are presented.     

MIMO—OFDM系统基于子空间的盲信道估计技术

MIMO-OFDM系统能在宽带无线信道中达到很高的速率。文章建立了MIMO-OFDM信道识别的条件并实现了基于子空间方法的盲信道估计技术。该方法将现存的在SISO-OFDM系统中的基于子空间的盲信道估计进行统一，并且推广到MIMO-OFDM系统中。特别是该方法可以获得信道的精确估计，且能快速收敛。仿真实验的结果显示了该方法的均方误差性能。     

Fast blind channel estimation for space–time block coded MIMO–OFDM systems

Fast blind subspace channel estimation using circular property of the channel matrix is investigated for space–time block coded (STBC) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO–OFDM) systems in this paper. The noise subspace computed from the correlation matrix of received signals requires a large number of symbols to converge in the subspace channel estimation. Using the circular property of the channel matrix, we propose both the cyclic repetition method (CRM) and the forward–backward method (FBM) to generate N times of equivalent signals for each STBC–OFDM symbol, respectively, where N is the size of FFT operation. With these equivalent symbols, the proposed CRM, FBM and CRM–FBM (CFBM) channel estimations can perform very well within a few OFDM symbols. The CRM, FBM and CFBM schemes are applicable to the CP-OFDM, ZP-OFDM and VC-OFDM systems, respectively. The identifiability of the subspace channel estimation is investigated that the channel matrix is determined up to two ambiguity matrices. Computer simulations demonstrate that the CRM-based, FBM-based and CFBM-based channel estimations have better performances than the conventional ones.     

Blind estimation of a fractionally sampled FIR channel for OFDM transmission using residue polynomials

This paper introduces blind-channel estimation methods using residue polynomials for orthogonal-frequency-division-multiplexing (OFDM) transmission under the assumption that the channel is finite-impulse response (FIR). In terms of z transform, if the received signal is multiplied by the inverse of the transmitted signal, the resulting z transform renders the channel transfer function when additive noise is absent in the channel. For an FIR channel, samples of the recovered impulse response must be zero in the region of zeros of the channel impulse response. Based on this observation, the blind estimation problem is formulated as a solution of linear equations, treating the transmitted symbols as unknown variables. Polynomial residue arithmetic turns out to be very useful for deriving the linear equations. The proposed method is computationally more efficient than subspace methods that are applied for OFDM transmission systems. In addition, unlike subspace methods, the proposed method is deterministic and does not require estimation of the autocorrelation matrix of received signals, which is required in subspace methods.