一种优化的OFDM符号定时与频偏估计算法及其FPGA实现

符号定时与频偏估计是OFDM系统中的关键技术之一.本文分析了符号定时偏差与载波频偏对OFDM系统性能的影响,提出了一种优化的最大似然同步算法,并给出了在FPGA中的硬件实现方案,得到其仿真结果.传统的循环前缀符号同步算法,仅仅利用一个OFDM符号的循环前缀及其相应部分的相关性,其相关峰值不明显,同步效果不理想.本文提出一种充分利用连续多个OFDM符号同时进行相关功率运算,在同样信噪比的情况下,相对于单个OFDM符号进行同步估计的系统,符号定时与频偏估计的精度更高,误差更小.     

DAB接收机中载波频偏估计

同步系统是 DAB 接收机的关键之一,针对其中的载波同步算法进行了分析。在理论分析载波频率偏差对 DAB 系统性能影响的基础上,介绍了2种分别用于载波粗频偏估计和细频偏估计的算法。粗频偏估计算法基于 DAB 信号所特有的相位参考符号(PRS),细频偏估计算法基于 OFDM 信号所特有的循环前缀(CP),对其它采用 OFDM 技术的系统具有很好的通用性。仿真结果表明这2种算法估计性能良好。     

基于循环前缀的MIMO-OFDM系统频率同步方法

从每一个MIMO-OFDM符号中循环前缀与数据部分的相关性出发,提出了一种实时调整的频率同步方法.该方法首先利用时域导频进行频率偏移估计,并对接收数据进行频偏调整.然后,再依据基于循环前缀的频率调整算法对已经进行了频偏校正的每一个符号进行进一步的精确调整.仿真结果表明,经过两个过程的调整,同步性能得到了改善.     

基于ESPRIT算法的子载波交织型OFDMA上行链路频偏估计

频率同步问题对于OFDMA系统来说至关重要。本文针对子载波交织分配的OFDMA系统上行链路，利用其接收信号周期性的结构特征，提出一种基于ESPRIT算法的多用户频偏估计算法，通过子空间旋转不变的特点估计各用户的载波频偏。仿真表明，利用该算法进行频偏估计具有良好的准确性。     

一种改进的基于训练符号的OFDM同步算法

根据一个OFDM符号前面的循环前缀是该符号最后一段数据的复制这一特性,结合Schmidl算法中特殊结构的训练序列,得出了一种改进的利用循环前缀来实现符号与频偏联合估计算法。先利用循环前缀的特性做粗符合同步,之后再利用Schmidl算法中的训练序列前后两部分良好的自相关性,来做细符号同步。仿真结果表明,新算法能够实现精确的符号定时,而且在AWGN和多径信道中均能较容易实现精确的频偏估计。     

高速移动环境下OFDM系统载波同步的混合结构算法

在分析载波频偏OFDM系统信号模型基础上，提出了基于前导符号循环前缀相关和前导符号相关的混合结构载波同步的算法，将基于循环前缀相关的方法和前导符号相关的方法融合，从链路级研究了易于实现的载波同步算法，在高速无线多径Rayleigh信道下，车速120km／h时，比较了两种不同的载波同步算法仿真结果。     

非合作通信中循环前缀线性调频信号的频率估计

针对非合作通信中循环前缀线性调频信号频率估计范围小的问题,提出了一种宽范围高精度的频率估计算法。该算法首先利用循环前缀的相关性确定符号周期起点,然后利用部分线性调频信号匹配相关确定接收信号的零频达到时刻,根据两者的时延差得到大范围频偏粗估计。最后,利用高精度单频估计算法估计匹配相关后波形的残余频偏,提高频率估计精度。理论分析和仿真结果表明,所提算法在保证估计精度的同时大大提高了频率估计范围,更适用于非合作接收环境。      

一种基于循环前缀的OFDM时频同步新算法

OFDM符号是由多个子载波信号叠加而成,为确保各子载波之间的正交性,就对载波间的同步有很严格的要求,否则将造成信道间干扰和符号间干扰,严重影响OFDM系统的性能。提出一种新的基于循环前缀的OFDM时频同步算法,通过仿真,将新算法和传统的ML算法及集相关算法相比较。仿真结果表明,新算法定时捕获更快,且能更准确地确定无IBI干扰的循环前缀采样部分,具有更好的频偏和定时估计性能。     

新的MIMO-OFDM 系统盲频偏估计算法

针对瑞利衰落信道,提出了一种新的基于加权循环前缀(CP,cyclic prefix)的MIMO-OFDM系统频偏估计算法及其简化实用算法。根据最大比合并原理,降低了MIMO-OFDM系统符号间干扰和高斯白噪声对频偏估计性能的影响。然后,利用无线信道统计信息,得到其简化算法。仿真结果表明,此算法在瑞利衰落信道中可以取得良好的频偏估计性能并优于其他同类算法。     

一种改进的适用于分组传输的OFDM频偏估计方法

提出了一种改进的基于训练符号的频偏估计方法.该方法通过综合利用训练符号和循环前缀的信息得到时域的细频偏估计,通过峰值检测得到频域的粗频偏估计.仿真结果表明,在多径衰落信道下,在频偏估计范围达到整个信号带宽的同时,本算法的估计精度也有了明显的提高,并且当信噪比达到12dB时,可以使剩余频偏限制在子载波间隔的2％以内.     

Multiple Invariance MUSIC-Based Blind Carrier Frequency Offset Estimation for OFDM System with Multi-Antenna Receiver

In this paper, we address the problem of carrier frequency offset (CFO) estimation for orthogonal frequency division multiplexing (OFDM) systems with multi-antenna receiver. The received signal can be reconstructed to form data model with multi-invariance property, and then a multi-invariance MUSIC algorithm for CFO estimation is proposed. This algorithm has better performance of CFO estimation than ESPRIT method, multi-invariance ESPRIT method and trilinear decomposition algorithm, and also qualifies the estimation for both integer CFO and fractional CFO. Simulation results illustrate validity of this algorithm.     

Blind Carrier Frequency Offset Estimation for OFDM System with Multiple Antennas using Multiple-invariance Properties

In this paper, we address the problem of carrier frequency offset (CFO) estimation for Orthogonal Frequency Division Multiplexing (OFDM) communications systems with multiple antennas. We reconstruct the received signal to form data model with multi-invariance property, and subsequently derive a multiple-invariance ESPRIT algorithm for CFO estimation. This algorithm has improved CFO estimation compared to ESPRIT method and maximum likelihood method. Simulation results illustrate performance of this algorithm.     

Compressed Sensing Trilinear Model-Based Blind Carrier Frequency Offset Estimation for OFDM System with Multiple Antennas

This paper addresses the problem of carrier frequency offset (CFO) estimation for orthogonal frequency division multiplexing (OFDM) systems with multiple antennas, and links CFO estimation problem in OFDM systems to the compressed sensing trilinear model. Exploiting this link, we derives a compressed sensing trilinear model-based CFO estimation algorithm. The signal model can be expressed as a trilinear model, and there exists three compressed matrices which can compress the trilinear model to be a lower dimensional one. After that, trilinear decomposition is performed for the compressed model to get the estimations of compressed data matrices, and then the CFO can be estimated through solving the sparse recovery problem via \(\ell _0\) -norm constraint. The proposed algorithm has much better CFO estimation performance than ESPRIT method, and performs very close to the trilinear decomposition-based approach which has heavier computational burden and requires much greater storage capacity. Furthermore, our proposed algorithm can even work in condition of no virtual carrier. We derive the Cramer-Rao bound of CFO estimation for multiple antenna OFDM system. Simulation results illustrate performance of our algorithm.     

OFDM盲载波间干扰抑制与同步算法研究

针对载波频偏引起的子载波间干扰问题,提出一种基于独立分量分析的OFDM载波频率同步算法。本算法直接实现载波频率同步,可以避免基于导频机制的频偏估计和由频偏估计误差带来的频谱效率降低与性能损失。首先建立含频偏OFDM独立分量分析模型,然后从最大似然原则得到分离的代价函数,结合自然梯度优化得到OFDM源信号实现载波频率同步。理论分析表明,提出的算法不仅具有基于最大似然的频偏补偿性能而且提高了系统的输出信噪比。最后,仿真分析证明了算法的有效性。      

Novel Blind Carrier Frequency Offset Estimation Algorithm for OFDM System Via Generalized Precoding

In this letter, we develop a blind carrier frequency offset (CFO) algorithm for orthogonal frequency division multiplexing (OFDM) systems by utilizing a generalized precoding. Generalized precoding is employed to obtain multiple covariance matrices, and then a CFO estimation algorithm for OFDM system using joint diagonalization is proposed. Comparing to estimation of signal parameters via rotational invariance techniques (ESPRIT) method, the algorithm that we presented has improved CFO estimation performance. Furthermore, our algorithm even works well without virtual carrier. Simulation results illustrate performance of this algorithm.     

Joint low‐complexity equalization and CFO estimation and compensation for UWA‐OFDM communication systems

Frequency synchronization has a great importance in preserving the performance of the underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems. The carrier frequency offset (CFO) estimation can be blind or data‐aided. In this paper, the Zadoff‐Chu (ZC) sequences are used for OFDM synchronization in UWA communications, and they are compared with different data‐aided algorithms. We propose a low‐complexity algorithm for CFO estimation based on ZC sequences. Also, a joint equalization and CFO compensation scheme for UWA‐OFDM communication systems is presented. Simulation results demonstrate that the proposed CFO estimation algorithm allows estimation of the CFO accurately with a simple implementation in comparison with the traditional schemes. Also, the performance of the UWA‐OFDM system can be preserved in the presence of frequency offsets.     

Cyclostationarity-Based Frequency Synchronization for OFDM Systems Over Doubly-Selective Fading Channels

Orthogonal frequency division multiplexing (OFDM) systems are highly sensitive to carrier frequency offset (CFO), especially in doubly-selective fading environment. Cyclostationarity-based blind synchronization methods are appealing in high-data-rate applications and low signal-to-noise regions. However, the cyclostationarity has not been exploited for frequency synchronization of OFDM systems under doubly-selective fading channels. In this paper, we derive the close-form second order cyclic statistics of the received OFDM signal in presence of CFO, by modeling the doubly-selective fading channel with basis expansion model. Both transmitter-induced cyclostationarity and doubly-selective channel information are contained in the derived cyclic moments, and they are efficiently utilized for CFO estimation. Simulation results demonstrate that the proposed estimator provides significant improvements on frequency synchronization performance.     

OFDM信号定时同步参数的盲估计算法

该算法通过联合多个正交频分复用（OFDM）符号对定时同步参数进行估计。该算法不需要额外的数据辅助,主要利用接收信号循环前缀的相关性,通过计算接收信号的联合相关函数,并利用搜索其峰值来实现OFDM信号的定时同步。该算法分为定时粗估计和定时细估计,利用定时细估计能精确进行OFDM信号的定时同步。仿真结果表明该算法在低信噪情况下估计精度较高,适合实际信号的应用。     

Non-data-aided carrier-frequency offset estimation for pulse-shaping OFDM/OQAM systems

In this paper we consider the problem of blind carrier-frequency offset (CFO) estimation for pulse-shaping orthogonal frequency-division multiplexing (OFDM) systems based on offset quadrature amplitude modulation (OQAM). In particular, under the assumption of low signal-to-noise ratio, three maximum-likelihood (ML) CFO estimators for non-dispersive channels are derived. Due to their significant computational complexity a more feasible closed-form CFO synchronization algorithm is considered. The performance of the derived blind estimators is assessed via computer simulations and compared with that of a blind CFO estimator previously proposed in the literature, exploiting the second-order cyclostationarity property of the OFDM/OQAM signal.     

电力无线专网中一种OFDM载波同步算法

电力无线专网在1.8 GHz频段建设4G TD-LTE网络,正交频分复用(OFDM)是其关键技术之一,OFDM系统对信道产生的载波频率偏移(CFO)很敏感,频率偏移会造成系统性能的严重下降。因此,需要对OFDM系统中的频率载波偏移精确估计并补偿,以保证系统的性能。本文提出了一种用于OFDM系统中基于局部搜索的多重信号分类(MUSIC)盲CFO估计的算法,该算法利用频率偏移矩阵列矢量与噪声子空间的正交性和CFO的单峰特性,构造一个改进空间谱函数,然后通过局部谱峰搜索得到频偏估计值。该算法的CFO估计性能优于传统CFO估计算法,且能够克服传统MUSIC算法低信噪比下谱峰缺失的问题。仿真结果证明了该算法的有效性。