Full-Hardware Architectures for Data-Dependent Superimposed Training Channel Estimation

Channel estimation based on superimposed training (ST) has been an active research topic around the world in recent years, because it offers similar performance when compared to methods based on pilot assisted transmissions (PAT), with the advantage of a better bandwidth utilization. However, physical implementations of such estimators are still under research, and only few approaches have been reported to date. This is due to the computational burden and complexity involved in the algorithms in conjunction with their relative novelty. In order to determine the suitability of the ST-based channel estimation for commercial applications, the performance and complexity analysis of the ST approaches is mandatory. This work proposes two full-hardware channel estimator architectures for a data-dependent superimposed training (DDST) receiver with perfect synchronization and nonexistent DC-offset. These architectures were described using Verilog HDL and targeted in Xilinx Virtex-5 XC5VLX110T FPGA. The synthesis results of such estimators showed a consumption of 3 % and 1 % of total slices available in the FPGA and frequencies operation over 160 MHz. They have also been implemented on a generic 90 nm CMOS process achieving clock frequencies of 187 MHz and 247 MHz while consuming 3.7 mW and 2.74 mW, respectively. In addition, for the first time, a novel architecture that includes channel estimation, training/block synchronization and DC-offset estimation is also proposed. Its fixed-point analysis has been carried out, allowing the design to produce practically equal performance to those achieved with the floating-point models. Finally, the high throughputs and reduced hardware consumptions of the implemented channel estimators, leads to the conclusion that ST/DDST can be utilized in practical communications systems.     

Doubly-Selective Channel Estimation Using Data-Dependent Superimposed Training and Exponential Basis Models

Channel estimation for single-user frequency- selective time-varying channels is considered using superimposed training. The time-varying channel is assumed to be well- approximated by a complex exponential basis expansion model (CE-BEM). A periodic (non-random) training sequence is arithmetically added (superimposed) at low power to the information sequence at the transmitter before modulation and transmission. In existing first-order statistics-based channel estimators, the information sequence acts as interference resulting in a poor signal-to-noise ratio (SNR). In this paper a data-dependent superimposed training sequence is used to cancel out the effects of the unknown information sequence at the receiver on channel estimation. A performance analysis is presented. We also consider the issue of superimposed training power allocation. Several illustrative computer simulation examples are presented.     

OFDM同步跟踪阶段的频偏估计算法

ＯＦＤＭ对栽频偏差是很敏感的，因此不仅在同步的捕获阶段，而且在同步的跟踪阶段，精确的频偏估计是很重要的。文献［３］提出了一种简化的相干判决反馈的迭代算法来估计同步跟踪阶段的载频偏差，对于１２８个子载波、ＱＰＳＫ调制的ＯＦＤＭ系统，在多径衰落信道下，当频偏小于子载波间隔的１５％时，频偏估计的标准方差小于１％，但是这个结果是在假设信道频率响应、定时偏差、载波相位等参数已知的条件下取得的，而当这些参数的估计存在误差时，由仿真结果可看出，频偏估计性能恶化了，因此，提出了采用差分判决反馈的频偏估计算法，虽然只能估计小于子载波间隔 ８％的频偏，但差分判决反馈算法不需要知道信道的参数，由于在同步跟踪阶段，频偏一般都较小，因此采用差分判决反馈算法可以很好地估计出同步跟踪阶段的频率偏差。     

Improved Carrier Frequency Offset Estimation in OFDM Systems

1　Introduction　OrthogonalFrequencyDivisionMultiplexing(OFDM )isaneffectivetransmissionschemetocombatmultipathfading[1 ] .Byinsertingaguardin tervalbetweensymbolblockscalledcyclicprefix ,theInterSymbolInterference (ISI)canbemitigat ed.OFDMwasadoptedasthemodulationschemeforaDigitalAudioBroadcasting(DAB)system[2 ]andADSL (AsymmetryDigitalSubscriberLoop) [3]andwasalsoproposedastheterrestrialHDTVtransportinEurope[4] .　OFDMsystemsareverysensitivetocarrierfre quencyoffset,andcarrie…     

一种宽范围低复杂度的载波频偏估计算法

针对短突发通信系统存在的频偏估计相位模糊问题,本文提出了一种宽范围低复杂度的时域相关频偏估计算法——基于相位解模糊的部分互相关算法.该算法利用自相关算法思想和相关代数知识消除了其复乘运算,再利用基于蒙特卡罗仿真的解相位模糊算法解决了其相位模糊问题,从而适应大频偏下的短突发通信环境.最后仿真结果表明,与经典的M&M、AC和Giugno时域算法相比,在保证了较大估计范围的同时,该算法具有更高的估计精度和更低的复杂度,适用于低时延高可靠的短数据包传输.     

一种数据辅助的载波频差估值算法

在许多频率估值算法中,估值范围和估值精度是难以同时兼顾的一对矛盾。本文通过对这一问题进行分析,提出了一种具有高性能和低复杂度的估值算法。仿真结果表明,对于数据辅助的ＢＰＳＫ,在Ｅｂ／Ｎ０＞ ０ｄＢ时,本算法的频差估值范围为符号速率的±４０％ ,估值方差接近克拉美—劳界（ＣＲＢ）,与文献［２］提出的算法相比,在相同的性能下,其硬件实现代价减小了３～５ 倍     

CMMB接收机中的粗载波频偏估计

提出一种适合CMMB接收机的粗载波频偏估计算法,小数倍频偏在时域中估计,整数倍频偏在频域中估计,而频偏的纠正则是在时域中完成.     

OFDM Carrier Frequency Offset Estimation Methods With Improved Performance

Orthogonal frequency division multiplexing (OFDM) systems are highly sensitive to carrier frequency offset and symbol timing error. This paper deals with estimation method of integer frequency offset (IFO) without the aid of pilot symbols. The proposed IFO estimator exploits two consecutive identical OFDM data symbols with only change of phase. In order to improve the accuracy of the IFO estimator, receive diversity is adopted. To demonstrate the efficiency of the proposed IFO estimators, comparisons are made with other existing estimators in terms of error performance, estimation range, and complexity.     

非数据辅助的QAM信号载波频偏估计算法

研究了正交幅度调制（Quadrature Amplitude Modulated ,QAM）信号的非数据辅助载波频率偏移估计算法。针对一些算法主要适用于低阶QAM信号以及计算复杂度较高等问题,提出一种基于加权相位直方图的载波频偏估计算法。该算法通过分析零频偏下的相位概率密度函数与加权相位直方图的关系,采用多级估计方法,对该相位直方图二阶矩的峰值进行测量,从而得到频偏估计值。进一步地,本算法通过联合快速傅里叶变换（Fast Fourier Transform,FFT）算法实现多级估计过程,从而简化计算过程降低计算复杂度。仿真结果表明,信噪比较高时,该算法在无信噪比、星座图以及前导信息等辅助信息条件下同样具有较好的估计性能。      

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。     

Blind Estimation of Carrier Frequency Offset and DC Offset for OFDM Systems

In this letter, a blind joint carrier frequency offset and DC offset (DCO) estimator for OFDM systems is proposed. By exploiting the underlying subspace of the received OFDM signals after the time-domain-average based coarse DCO cancellation, the proposed estimator can achieve excellent performance, which is demonstrated by simulations.     

Carrier Frequency Offset Estimation for OFDM Systems with Null Subcarriers

An accurate estimation of carrier frequency offset (CFO) is a crucial task for orthogonal frequency-division multiplexing (OFDM) systems but should be performed with affordable computational complexity for practicality. In this paper, the authors derive two new estimation algorithms (one for the integer part and the other for the fractional part of CFO), each of which utilizes only one OFDM block with null subcarriers but offers improved accuracy and reduced complexity. The proposed estimator for fractional CFOs operates iteratively and is insensitive to the initial CFO. The other proposed estimator for integer CFOs employs a pseudonoise binary random sequence to assist in subcarrier arrangement and accurate estimation of the integer CFO. To demonstrate the efficiency of the proposed methods, numerical results are provided from computer simulation and analysis, and comparisons are made with other existing methods in the literature.     

一种新的OFDM系统载波频偏估计算法

在正交频分复用(OFDM)系统中,频率偏移会破坏子载波间的正交性,降低整个系统的性能。在研究传统频偏估计算法的基础上,利用简单的实数训练序列,进行OFDM系统的载波频偏估计,只需要一个训练序列,就可以有效地在时域内同时对小数倍和整数倍的频率偏移进行估计。仿真结果表明,基于实数训练序列的载波频偏估计算法不仅方法简单,易于实现,而且可提高频偏估计精度。     

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.     

LOFDM系统大载波频偏的盲估计算法

该文研究了网格正交频分复用(LOFDM)系统中大载波频偏的盲估计.在低信噪比及虚子载波存在的假设下,基于最大似然准则(ML)推导出LOFDM系统大载波频偏盲估计算法.该算法利用了信号的时变自相关函数特性,频偏估计的范围为所有子载波宽度.计算机仿真表明,该算法也适用于高信噪比条件下的载波频偏估计.与基于信号二阶循环平稳特性(CS)的盲载波频偏估计算法相比,提出算法的均方根误差(RMSE)性能在加性高斯白噪声(AWGN)信道和广义平稳非相干散射信道(WSSUS)条件下均有很大程度的改善.     

Joint Blind Adaptive Carrier Frequency Offset Estimation and Channel Shortening

Multicarrier modulation has the advantage of robustness to multipath, so long as the delay spread of the multipath is less than the guard interval between successive transmitted blocks. However, it has the disadvantage of sensitivity to a carrier frequency offset (CFO), which disrupts the orthogonality of the subcarriers. If a CFO is present, it must be estimated and then corrected. In addition, if the channel delay spread exceeds the guard interval, this must be accounted for as well, usually by a channel shortening equalizer. Hitherto, CFO estimation and channel shortening have been addressed individually. However, this leads to a circular set of assumptions, since standard CFO estimators perform poorly when the channel is longer than the guard interval, and standard channel shorteners assume that CFO estimation has already been perfectly performed. In this paper, we investigate a blind, adaptive method for jointly performing CFO estimation and channel shortening.     

一种TD-SCDMA载波频偏与信道联合估计算法

通过分析时分同步码分多址(TD-SCDMA)系统的载波频偏和信道特性,提出一种频偏与信道联合估计算法。该算法通过对训练序列部分相关,然后做差分将频偏和信道特性解耦,并通过逐次迭代最终精确估计出频偏和信道参数。仿真结果表明,算法频偏估计性能接近Cramr-Rao界,准确度较高;全链路仿真误码率性能优越,信道估计准确。算法复杂度不高,实用性强,同样适用于其它的TDD模式的CDMA系统。     

一种有效的OFDM载波频率偏移的盲估计

导出了具有循环前缀（CP）和虚子载波的正交频分复用（OFDM）通信系统信号的薮学模型。提出了基于PM—ESPRIT算法的0FDM系统载波频率偏移（CFO）偏移不变性的估计算法。经过粗略估计,该算法可以同时获得频率偏移和包含信道信息的矩阵,它们均有利于接收信号的偏移补偿和解调。仿真结果说明了该方法是有效的。     

突发通信中数据辅助频偏估计算法研究

分析了基于最大似然准则的3种典型数据辅助（DA）开环频偏估计算法：Kay算法、Fitz算法和L＆R算法。利用MPSK信号对上述算法进行了计算机仿真验证,仿真结果表明：Kay算法的鉴频范围大,而Fitz算法和L＆R算法的估计性能好。