OFDM系统中线性插值信道估计器的性能研究

为了得到由线性插值信道估计器本身精度造成的插值误差与噪声所带来的误差间的定量关系,通过基于一阶线性插值的OFDM系统梳状导频信道估计器和块状导频信道估计器误差性能的分析,推导出了插值误差和高斯噪声对估计器性能影响的数学表示式,并得出了线性插值信道估计器导频间距的选择规范;最后,在IEEE802.11 a环境下进行了系统仿真,仿真结果表明,插值误差与插值带来的噪声降低二者存在折衷,并且在室内环境中具有相同导频间距的梳状导频估计器比块状导频信道估计器性能优越。     

LTE-A系统中基于小区参考信号的信道估计算法

增强型长期演进（LTE-A）系统中,通常利用插值算法估计出所有数据位置的信道频率响应值。针对传统的线性最小均方误差（LMMSE）算法需要预先获取信道统计特性,矩阵实时求逆运算量大的问题,提出了一种改进的频域LMMSE信道估计插值算法。首先通过导频插值来增加虚拟导频,以此提升算法性能;然后借助时域内的信道能量比较集中的优势,给出了自相关矩阵和信噪比的近似估计方法;最后采用滑动窗方法进一步简化算法复杂度,从而完成频域LMMSE插值。仿真结果表明,所提算法总体性能优于线性插值以及基于离散傅里叶变换（DFT）的插值方法,且与传统LMMSE插值算法具有相近的误码率（BER）和均方误差（MSE）;但与传统算法相比,运算次数降低了98.67%,实现了算法性能与复杂度的较好折中,适用于实际的工程应用。     

Channel estimation based on neural network in space time block coded MIMO–OFDM system

In this study, we propose feed-forward multilayered perceptron (MLP) neural network trained with the Levenberg–Marquardt algorithm to estimate channel parameters in MIMO–OFDM systems. Bit error rate (BER) and mean square error (MSE) performances of least square (LS) and least mean square error (LMS) algorithms are also compared to our proposed neural network to evaluate the performances. Neural network channel estimator has got much better performance than LS and LMS algorithms. Furthermore it doesn?t need channel statistics and sending pilot tones, contrary to classical algorithms.     

正交频分复用通信系统中的快变信道估计

信道的快速变化导致正交频分复用通信系统(OFDM)载波间的正交性遭到破坏,从而产生载波间的相互干扰(ICI),传统的信道估计方法(不可虑ICI影响)不再适用。为此,Choi等人提出了相应的快变信道估计方法,但该方法计算量较大,且需要信道的统计特性知识,而实际信道的统计特性往往无法精确得到。Linartz等人证明:在大多数应用条件下,信道在一个OFDM帧周期内的变化近似满足线性特性。对OFDM系统的ICI特性进行了时域和频域两方面分析,并利用信道变化的线性特性,提出了一种新的快变信道估计方法,该方法具有计算量小、且不需要信道的统计特性信息的优点。文章还得到如下结论:与慢变信道情形不同,在信道快速变化条件下,当OFDM系统中的训练序列应分成许多长度相同的组,且这些组在OFDM帧中等间隔分布时,信道估计误差最小。     

基于MAP算法的OFDM系统迭代信道估计

提出一种运用在OFDM系统中的迭代最大后验概率信道估计方法。译码器利用信道估计值形成译码模块的软信息,通过交织,反馈到信道估计模块中,使外信息在信道估计模块和译码模块之间循环迭代。信道估计模块中采用线性最小均方误差算法对信道参数进行估计。通过信道估计模块和译码器之间软信息的循环迭代,充分利用有效的外信息,降低误码率,提高OFDM系统的性能。     

协作多小区正交频分复用系统联合信道估计扩展算法

多小区联合信道估计(MC-JCE)是多小区协作联合处理技术实用化的基础,然而现有MC-JCE算法需满足各小区信道功率延迟谱(PDP)相同且已知的条件。针对这一不足基于协作多小区正交频分复(OFDM)系统框架首先探讨在多小区信道PDP存在差异但已知条件下多小区联合信道估计的扩展算法(MC-eJCE),进而提出未知该信息条件下多小区联合信道估计的修正算法(MC-mJCE),同时为降低算法运算复杂度并获得信道估计最小的均方误差(MSE)。采用梳状导频最优导频设计,推导了以上MC-JCE算法的克拉美罗界(CRB)。仿真显示在多小区信道PDP存在差异条件下所提MC-eJCE和MC-mJCE算法都具有良好MSE性能,而基于以上算法信道估计的空频块码(SFBC)协作联合传输也具有良好误码率(BER)性能。     

基于小波去噪与离散余弦变换相结合的正交频分复用系统信道估计算法

针对传统的基于离散余弦变换(DCT)信道估计算法没有处理循环前缀之内噪声的问题,提出了一种基于小波去噪与DCT插值相结合的正交频分复用(OFDM)系统信道估计方法。首先,采用最小二乘(LS)法对接收到的导频信号进行信道初步估计;然后,对LS法估计出的结果进行离散小波阈值去噪处理;最后,利用DCT插值对循环前缀内的噪声再次处理,以进一步减小噪声的影响。在Matlab 2012平台上仿真,与传统的基于DCT信道估计算法相比较,误码率相同的条件下,所提算法的信噪比(SNR)性能提升了1 dB左右;均方误差相同的条件下,所提算法的SNR性能提升2 dB左右。仿真实验结果表明,该算法能够较好地减小加性高斯白噪声(AWGN)的影响,并有效提高信道估计的准确度,其总体性能较基于DCT的信道估计算法更优。     

联合子载波抑制-机会网络编码的OFDM数据广播方法

正交频分复用(Orthogonal freqency division multiplexing,OFDM)技术通过采用多个子载波在不同的子带上传输信息来有效对抗频率选择性衰落。但不同子载波信道质量不同,其中信道质量较差的子载波会产生较大的误码率,从而导致整个系统性能下降。将信道质量较差的子载波抑制不用即可解决该问题。本文提出了一种适用于OFDM数据广播系统的联合子载波抑制-机会网络编码方法（Joint subcarriers suppression and opportunistic network coding, JSSONC）,即将子载波抑制技术与网络编码（Network coding,NC)技术联合使用。基站抑制信道质量较差的子载波,仅采用信道质量较好的子载波进行数据包的广播与重传。在此基础上,结合机会网络编码,进一步减少重传数据包数量。仿真结果表明,与传统OFDM广播系统相比,本文提出的JSSONC方法降低了每一个数据包平均传输次数（Average transmission times of every data package,ATT-E）,从而大大提高了系统传输效率。     

一种新颖的OFDM信号子载波数估计方法

针对低信噪比多径信道下传统的正交频分复用(OFDM)信号子载波数估计方法存在估计性能不高,计算复杂度高等问题,提出了一种新颖的OFDM信号子载波数估计方法。首先计算接收信号的自相关矩阵,然后对接收信号的自相关矩阵进行特征分解,提取分解后的特征值,最后根据特征值的分布特性实现子载波数目的估计。仿真实验结果验证了我们的方法在高斯白噪声信道和多径信道条件下对OFDM信号子载波数估计的有效性与可靠性。     

基于正则总体最小二乘准则的OFDM系统信道估计算法

基于导频的最小二乘(LS)估计方法的优点是结构简单,容易实现,但对噪声和干扰敏感。通过对OFDM系统中由于信道的时变性产生的载波间干扰进行了分析,在此基础上提出正则总体最小二乘(TLS)信道估计算法。根据Tikhonov正则化原理,导出了总体最小二乘正则化解法的计算公式。与一般的LS信道估计相比,TLS方法同时考虑了信道噪声和信道时变特性,所以该算法不仅在一般的信道条件下具有良好的性能而且也适合快变信道条件下的OFDM系统。仿真结果表明,该算法具有很好的均方误差和误比特率性能。     

Doubly selective fading channel estimation in MIMO OFDM systems

Recent researches in the information theory have demonstrated that MIMO commu nication systems have the potential to provide the linear increase in the channel capacity and frequency spectral efficiencies compared with single-input single-output (SISO communication systems. MIMO is one of the major development aspects in the new generation mobile communication technology, in which plenty spatio-temporal signa processing problems need to be resolved. Especially when MIMO channels are time…     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Blind synchronization scheme using the conjugate characters of the OFDM BPSK-modulated symbol

Previously, Beek?s scheme for timing and frequency offset estimation in the OFDM system employs cyclic prefix (CP) has been proposed under the assumption of independent identified distributed (i.i.d.) OFDM symbols. Actually, the real data in the OFDM modulated symbol, transferred by the inverse fast Fourier transform (IFFT), has the characters of complex symmetry. With these characters, more information in the whole OFDM symbol could be used for the timing and frequency offset estimation. In this paper, two conjugate symmetry characters of the OFDM BPSK-modulated symbol are used to achieve blind timing estimation algorithm in the OFDM systems. One is symbol-based symmetry and the other is CP-based symmetry. With these two conjugate characters applied to the proposed algorithm, the timing of the OFDM BPSK-modulated symbol could be derived. Under an AWGN channel, based on the performance of lose symbol timing rate and estimator mean square error, the proposed algorithm is with a tremendous improvement compared with Beek?s estimation method. Under a multipath fading channel, the results show that performance including lose symbol timing rate and estimator MSE with the proposed algorithm is better than those algorithms with Beek?s estimation method. In practical OFDM applied system, the OFDM BPSK-modulated symbol could be used to replace the preamble or training sequences in the standard to obtain an accurate timing and frequency offset estimation and to avoid the data rate decreasing with the proposed algorithm.     

DVB-C2数字接收机的信道均衡方法

DVB-C2系统采用了4096-QAM调制,并结合OFDM技术在同轴电缆上获得接近12 （bit/s）/Hz的频谱利用率。然而相对于低阶调制,高阶QAM密集的星座点分布更容易受到信道估计误差的影响。分析了高阶QAM调制对OFDM信道估计精度的要求,针对同轴电缆信道的慢时变特性,提出了一种噪声抑制的信道均衡方法。计算机仿真结果表明,与传统的信道均衡方法相比,在高信噪比时,提出方法的误比特率性能优于传统方法约3 dB。     

Optimisation of the pilot-to-data power ratio in the wireless MIMO-OFDM system with low-complexity MMSE channel estimation

Multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) communication systems are currently being viewed as a main candidate for the next generation broadband wireless access interfaces providing high throughput. However, a considerable potential gain in spectral efficiency is challenged by the receiver’s ability of accurate data symbol identification at the output of the radio channel. Performance of the MIMO detectors strongly depends on both the received signal-to-noise power ratio (SNR) and the retrieved channel state information (CSI), which can be obtained using the channel estimation techniques relying on pilot symbol transmission on the dedicated subcarriers. Necessity to improve channel estimation and detection performance concurrently leads to the dilemma of the optimal power assignment to the data and pilot subcarriers as these are the conflicting requirements under the total transmit power constraint. We derive an analytical solution of the described problem in the form of weak and tight upper bounds on the pilot-to-data power ratio (PDR) given the system design parameters (number of subcarriers, number of pilots, number of transmit antennas, model order of the channel response, SNR). The resultant PDR equations can be applied to OFDM systems with arbitrary arrangement of the pilot subcarriers operating in an arbitrary multipath channel, not just limited to the equispaced optimal pilot pattern and the channel with the uniform sample-spaced power-delay profile as studied in the previous works.In an adaptive system, which is capable to adjust transmit signal configuration (e.g., block length, number of pilot subcarriers or antennas) according to the established channel conditions, an optimal parameter tuning is desirable for each operational mode. The closed-form PDR expressions and their analysis presented in this work are designated to alleviate the challenging task of the on-the-fly system optimisation as they represent relatively simple functional relationships.     

地空信道下基于OFDM/OQAM系统的信道估计研究*

针对地空信道时变快,正交频分复用/偏移正交幅度调制(OFDM/OQAM)系统存在固有干扰的问题,提出一种信道估计算法。该信道估计算法包含一种新型的梳状导频结构和一种改进的线性插值算法。提出的新型梳状导频通过将导频周围数据置零来消除系统的固有干扰和减小子载波间干扰对信道估计的影响,且导频分布在整个时间轴上,因而可以较好的跟踪信道状态;改进的线性插值算法通过在时域插零,来减小信道噪声和系统干扰对信道估计的影响。仿真结果表明,提出的梳状导频相比于传统梳状导频具有较好的优势,可有效提高系统的抗误码性能;改进的线性插值算法相比于传统插值算法可有效提高系统的可靠性。     

基于五次hermite插值的OFDM信道估计

导频辅助信道估计方法是OFDM系统中的主要信道估计方法,可以使用LS(最小均方估计)估计导频点处的信道响应,然后通过插值算法来估计数据点的信道响应。该文提出五次hermite插值信道估计算法,目的是利用该插值算法在不同信噪比的环境下,降低误码率(BER)。通过仿真实验说明,该算法相对于传统的信道估计算法具有较良好的性能。相对于线性插值和三次样条插值,在不同的信噪比环境下具有较低的BER的优点。     

OFDM系统中一种低复杂度的信道估计算法

提出一种适用于正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统的低复杂度信道时域响应估计算法.在发送端,算法基于最小均方误差(Mean-square error,MSE)准则以及给定的导频分布对导频功率及相位进行设计;在接收端,算法直接对接收到的导频符号进行求和,通过对求和结果进行简单加权后得到信道时域响应的估计.由于该算法在估计信道时只需进行很少量的复数乘法运算,因此接收端的计算复杂度非常低.理论分析与仿真结果表明,当信道时不变或慢时变时,该算法具有较小的估计均方误差.     

基于压缩感知的协同OFDM稀疏信道估计方法

针对频率选择性衰落信道下的放大转发协同正交频率复用(OFDM)通信系统,提出一种基于压缩感知理论的稀疏信道估计方法。首先,构造协同OFDM系统模型,利用循环矩阵理论,将该系统模型变换成类似于传统的点对点系统模型,该模型由一个协同卷积信道矢量和等效的观测矩阵组成;然后,通过压缩感知理论证明,该等效矩阵以很高的概率满足严格等距特性(RIP);最后,利用压缩感知算法重构卷积信道脉冲响应。与传统的线性信道估计方法相比较,所提方法能够利用较少的训练序列达到稳健的信道估计,有效地提高频谱资源利用率,且具备计算复杂度低的特点。仿真结果验证了该方法的有效性。     

基于正交频分复用调制的物理层并行插值加密算法

针对传统链路层安全机制不能从根本上保护无线通信系统信息传输安全的问题,提出了一种基于正交频分复用（OFDM）系统并行调制特性和物理层安全的并行插值加密算法。首先,根据OFDM系统调制的子载波数目确定插入符号个数,并通过密钥控制生成插入符号位置;然后,取出对应插入位置前后的原OFDM符号,并计算其平均值作为插入符号;最后,在反快速傅里叶变换（IFFT）后完成伪随机插值。与传统链路层安全机制相比,所提算法能实现调制符号整体加密,保证了信令、标志及数据信息的安全,并有效降低了算法实现复杂度。仿真实验结果表明,该算法能有效抵抗各种窃听攻击,对通信系统固有性能影响小,能较好地适应高斯信道和多径信道,且表现出一定的抗多径衰落能力。