基于ML和ESPRIT方法的OFDMA上行链路频偏估计算法

由于载波频偏会给正交频分多址接入OFDMA系统带来子载波之间干扰,从而造成多用户之间的干扰,导致系统性能下降。该文提出一种基于ESPRIT和ML方法联合估计的频偏估计算法。该算法首先使用ESPRIT方法估计出多个可能的频偏构成的子集,然后使用最大似然估计方法在这个有限子集合中搜索出估计的频偏。该算法解决了使用似然估计进行多维搜索的问题,大大降低了算法的复杂度,同时解决了多个频偏估计的问题。     

两根分布式接收天线载波频偏的联合估计

该文在平坦瑞利衰落信道下,针对一根发射天线、两根分布式接收天线场景,提出了一种缩小频率搜索范围的最大似然准则载波频偏联合估计方法。该方法利用载波频率、收发天线晶振精度和移动台最大运动速度的先验信息,确定了两个载波频偏之差的取值区间;联合各接收天线的相关值滑动此取值区间进行搜索,相比已有方法缩小了搜索范围。仿真结果表明,在信噪比为5 dB,载波频率为2 GHz,发射天线晶振精度为10 ppm,接收天线晶振精度为1 ppm,移动台最大运动速度为120 km/h的条件下,载波频偏联合估计的均方误差性能高出已有方法一个数量级。     

基于正交训练序列的MIMO系统联合最大似然时频同步和信道估计

该文推导了多输入多输出(MIMO)系统中的符号定时、频偏和信道参数的联合最大似然(ML)估计。针对联合ML估计没有闭合的表达式、数值计算复杂度高的问题,该文提出了一种基于重复结构的正交训练序列的简化估计算法。该估计算法形式简单、复杂度低,且仍为最大似然估计。最后仿真分析了最大似然参数估计的均方误差与接收信噪比和天线数目的关系,并与Cramer-Rao界作了比较,表明了该算法的有效性。     

BICM-OFDM系统中基于ML算法的迭代频偏估计

正交频分复用(OFDM)联合比特交织编码调制(BICM),是一种能够有效地抗频率选择性衰落的技术.由于载波频偏的存在会引起载波间干扰,导致系统性能的严莺下降.针对BICM-OFDM系统提出了一种基于最大似然(ML)估计的迭代频偏估计算法.该算法充分利用了译码信息,分两步进行.首先,利用最大似然估计进行初始频偏估计,然后再利用BICM译码的硬判决反馈信息进行残留频偏估计.通过BICM迭代译码,更新译码反馈信息,提高频偏估计精度.在短波宽带信道下的仿真结果表明,在频偏为0～0.2的范围内,提出的算法经过3次迭代可有效地进行频偏估计.与传统最大似然估计算法相比,本文提出的算法提高了低信噪比下的频偏估计精度,并且提高了频偏估计范围.     

分布式MIMO中的最大似然频偏估计

在考虑分布式多入多出(MIMO)系统中各收发天线对之间的频偏均可能不同的一般情况下,推导出了平坦衰落MIMO信道模型下的最大似然频偏估计.针对收端是否采用分布式天线的两种不同情况,分别提出了一种只涉及一维最大化问题的较低复杂度频偏估计方法.仿真结果表明,所提频偏估计方法在平坦衰落MIMO信道下可以获得令人满意的估计性能;而在收端仍采用集中式天线这一特殊情况下,利用所有接收天线上的接收信号进行联合估计,可以进一步提高估计性能.     

引入蝙蝠算法的最大似然DOA估计

DOA估计理论的传统算法中,最大似然DOA估计方法能准确地估计出目标方向角度,性能优良,并且具有很好的稳定性。与MUSIC及其他的子空间分解类算法相比,在信噪比较低、小快拍信号时,最大似然DOA估计算法优势更为突出。但是由于其自身算法复杂度较高的缺陷而碍于工程上的应用。针对这一问题,将蝙蝠算法与最大似然算法相结合,应用于信号的DOA估计,利用蝙蝠搜索算法搜索路径优、寻优能力强的优点,快速搜索到似然函数的全局最优值,优化多维非线性的估计谱函数。仿真结果表明,蝙蝠搜索算法有效地克服最大似然DOA估计中存在的运算量大,计算复杂度高等问题,通过与其他经典的仿生智能优化算法相比较,该方法体现出更好的收敛性。     

一种新的多用户OFDM系统的频偏估计算法

由于载波频偏会给多用户正交频分复用（Orthogonal Frequency—Division Multiplexing，OFDM）系统带来子载波之间干扰，从而造成多用户之间的干扰，导致系统性能下降．本文研究了多用户OFDM上行链路的频偏估计问题，通过使用多用户检测中的干扰抵消方法提出一种迭代参数估计算法用于估计多用户OFDM上行链路的频偏，该算法解决了使用似然估计（Maximum Likelihood，ML）进行多维搜索的问题，降低了ML估计器的复杂度，同时解决了多个频偏估计的问题。     

基于最大似然估计的16APSK载波捕获算法研究

针对在低信噪比情况下16APSK信号频偏捕获困难的问题,讨论了一种结合Kalman滤波和最大似然估计的非数据辅助频偏估计算法。该算法对包含载波频偏信息的相位序列进行最大似然频偏估计,通过Kalman滤波,降低了噪声对估计精度的影响。对结合Kalman滤波和最大似然估计的16APSK频偏估计算法进行了仿真。仿真结果表明,在低信噪比条件下,结合Kalman滤波的最大似然频偏估计算法可获得良好的性能。     

一种基于自相关函数的载波频偏估计方法

为解决前向载波频偏估计中捕获范围和估计精度矛盾的问题,在最大似然准则的基础上,利用相位折叠现象使得自相关函数的频偏具有周期化规律,提出了一种利用最大似然估计中的自相关函数进行频偏估计的算法,该算法估计范围广,精度高且复杂度低,适于突发通信的频偏估计。最后进行了MATLAB仿真实验,仿真结果表明了该算法估计精度高、捕获范围广和计算复杂度低的性能。     

基于DML-ESPRIT算法的多维参数快速联合估计

将确定性最大似然估计准则的多维参数估计能力与ESPRIT算法的高时效性有机结合,提出了一种二维DOA-功率-频率快速联合估计方法--DML-ESPRIT算法。利用双L阵列的空间特性,通过引入空间锥角,将多维空间搜索问题转换为一维角度估计,并基于确定性最大似然估计准则推导得到了多信源的空间锥角、功率和频率联合估计的数学模型;然后在对子阵进行扩展的基础上,利用TLS-ESPRIT算法对模型进行求解,避免了谱峰搜索问题,实现了多维参数的快速联合估计。实验结果表明,DML-ESPRIT算法在保持高估计精度的同时运行耗时约35 ms,具有较好的工程应用前景。     

Joint estimation of symbol timing and carrier frequency offset of OFDM signals over fast time-varying multipath channels

In this paper, we present a novel joint algorithm to estimate the symbol timing and carrier frequency offsets of wireless orthogonal frequency division multiplexing (OFDM) signals. To jointly estimate synchronization parameters using the maximum likelihood (ML) criterion, researchers have derived conventional models only from additive white Gaussian noise (AWGN) or single-path fading channels. We develop a general ML estimation algorithm that can accurately calculate symbol timing and carrier frequency offsets over a fast time-varying multipath channel. To reduce overall estimation complexity, the proposed scheme consists of two estimation stages: coarse and fine synchronizations. A low complexity coarse synchronization based on the least-squares (LS) method can rapidly estimate the rough symbol timing and carrier frequency offsets over a fast time-varying multipath channel. The subsequent ML fine synchronization can then obtain accurate final results based on the previous coarse synchronization. Simulations demonstrate that the coarse-to-fine method provides a good tradeoff between estimation accuracy and computational complexity.     

Joint Semi-Blind Channel Estimation and Data Sequence Detection of OFDM Systems

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A hybrid joint ML technique for CFO,timing offset,and channel estimations in an OFDMA uplink

In this paper, we propose a novel hybrid joint maximum‐likelihood estimator for carrier frequency offset (CFO), timing offset, and channel response of all users in the uplink of an orthogonal frequency division multiple access (OFDMA) system. The proposed estimation method significantly reduces complexity of this multiparameter, multidimensional optimization problem, using the concept of separation of the different user signals by means of newly defined projection operators. This projection technique is combined with the alternating projection method available in the literature to arrive at a new hybrid algorithm that offers significant performance advantages in terms of computational complexity and estimator performance. The joint estimation of the CFOs, timing offsets, and channel coefficients for all active users together at the base station of the OFDMA uplink is a rarely addressed task. The proposed method also offers the flexibility of application to any subcarrier assignment scheme used in OFDMA systems. Extensive simulation studies corroborate the advantages of the new hybrid method for all three estimation requirements in the multiuser OFDMA uplink. Copyright © 2012 John Wiley & Sons, Ltd.     

MIMO OFDM系统中同步和信道的联合估计

提出了一种MIMO OFDM系统的定时恢复、频率同步和信道估计的联合算法。为了减少算法的复杂度，算法分两步完成：首先利用接收信号的自相关函数进行粗同步和信道估计，得到时延和频偏的粗估计，然后在粗估计基础上采用最大似然准则进行精确的同步和信道估计。仿真结果表明，该算法能够达到很好的效果，系统误码率接近已知信道响应时的情况。     

Turbo Estimation and Equalization for Asynchronous Uplink MC-CDMA

In this contribution, we propose a new code-aided synchronization and channel estimation algorithm for uplink MC-CDMA. The space alternating generalized expectation- maximization (SAGE) algorithm is used to estimate the channel impulse responses, propagation delays and carrier frequency offsets of the different users. The estimator, multi-user detector, equalizer, demapper and channel decoder exchange soft information in an iterative way. The performance of the proposed algorithm is evaluated through Monte Carlo simulations. Impressive performance gains are visible as compared to a conventional data-aided estimation scheme.     

一种改进的OFDM盲同步算法

研究了OFDM系统中的最大似然估计(ML)算法,并使用数据循环移位以及多符号联合估计等技术对ML算法进行了改进,随后提出了一个综合性的新方案。仿真结果显示,在AWGN和瑞利多径衰落信道中,该方案可以有效提高符号定时偏差(STO)和载波频率偏移(CFO)的估计性能。     

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO–OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO–OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator.     

Analysis and design of joint CFO/channel estimate techniques for a cooperative STBC‐OFDM system

This paper studies the joint estimation technique of carrier frequency offset (CFO) and channel information for a distributed decode‐and‐forward (DF) cooperative space‐time block‐coded (STBC) orthogonal frequency division multiplexing (OFDM) system. For the considered relay system, we provide theoretical analysis of the effects upon the output signal‐to‐noise ratio (SNR), which is caused by the CFO/channel estimation error. Based on the provided analytical results, a joint CFO/channel estimation scheme is then developed, where the CFO estimate is achieved by a multiple‐dimensional linear search algorithm. Furthermore, we propose an alternative estimation solution with iteration approach being designed for the CFO estimation prior to the channel estimation. In contrast to the former estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. The conducted computer simulation results verify the effectiveness of the proposed schemes.     

Joint Frequency and Symbol Synchronization Schemes for an OFDM System

This paper proposes two multi-stage joint symbol timing and carrier frequency synchronization schemes for an orthogonal frequency division multiplex (OFDM) system. Simultaneous estimation of symbol timing and frequency offset is derived from the maximum likelihood (ML) principle, assuming a cyclic prefix (guard interval) is inserted in each OFDM symbol. One of the proposed algorithms derives an initial frequency estimate in the first stage that reduces the frequency uncertainty to only two or three sub-carrier spacings. The timing information and a finer frequency estimate that has a resolution of a sub-carrier spacing are obtained in the second stage. The third stage provides an estimation for the residual fractional frequency error. The other algorithm bypasses the first stage for one can use the second stage alone to search for the timing and frequency offsets. However, the computing complexity of the second stage is higher than that of the first stage, thus the three-stage algorithm is a preferred choice unless the frequency uncertainty is small. Simulation results show that both algorithms yield excellent performance not only in white Gaussian channels but also in multipath fading channels.