基于叠加训练序列的低复杂度时变信道估计方案

与传统的时分/频分复用训练序列相比,采用叠加训练序列的传输方案可以有效地提高系统的频谱利用率。然而,叠加方案中训练序列与信息序列的相互干扰会造成系统性能的严重下降,如何有效消除信息干扰是提高信道估计性能的关键。该文针对时变衰落信道,首先提出一种新的基于一阶统计量信道估计算法。该算法利用基扩展模型(BEM)构建时变信道,通过时域分块平均的方法来抑制信息序列干扰。在此基础上,利用信息序列和训练序列经历相同信道衰落的特性,提出一种基于加权最小二乘(WLS)的迭代信道估计与检测方案。新方案利用 Kalman滤波检测器代替确定性最大似然(DML)检测器,将检测符号序列看作附加的“训练序列”用于信道估计,从而可以显著提高信道估计性能。仿真结果表明,新方案可以有效消除信息序列干扰,且性能和计算复杂度均优于现有的同类方案。     

突发通信中基于叠加训练的信道估计方案

针对无线突发通信中频带利用率低、信道参数获取困难等问题,提出了一种应用于突发通信的叠加训练信道估计与检测方案。该方案将信息和训练叠加发送,通过预失真发送信息符号使得训练与信息在频域正交,收端采用一阶统计信道估计和最大似然符号检测,并设计了抗直流干扰的信道估计方案。仿真表明,新方案在消除训练序列的频带开销的情况下获得了较好的信道估计和符号检测性能,与采用时分复用训练的方案相比,其有效吞吐率更优。     

基于低轨卫星PCMA信号的信道估计算法研究

【目的】随着天地一体化信息网络的发展,低轨卫星通信系统迎来发展热潮,成对载波多址（PCMA）技术凭借其节省带宽资源的优点也逐渐向低轨卫星通信发展。然而,传统PCMA技术多用于高轨卫星中,无法适应低轨卫星信道高动态的衰落信道特性,使得PCMA接收端误码性能大大下降,其中的瓶颈在于重叠信号的信道估计与均衡技术。【方法】针对低轨卫星信道特点,文章提出了一种联合训练序列估计与自回归（AR）模型预测的信道估计方案。借鉴叠加训练序列信道估计的思想,引入了适用于PCMA混合信号信道估计的迭代方法,通过迭代提升训练序列信道估计的精确度;并利用AR模型实时预测数据序列的信道状态信息（CSI）,同时也通过AR模型预测达到降低训练序列信道估计频次的目的,以适应低轨卫星信道的动态性。【结果】仿真结果表明,叠加训练序列信道估计的思路可以适用于PCMA信号中,经过迭代可以获得精确信道估计值。文章所提方法可以有效提高信道估计的精确性,且经过信号分离以及解调后,在信噪比>9 dB时误码率可以达到10-3量级。【结论】文章所提信道估计方案并入PCMA接收方案中后,误码率损失在可接受范围内,可以支持PCMA技术在低...     

菱形中继网络中基于叠加训练的信道估计技术研究

针对放大转发(Amplify-and-Forward, AF)模式下的菱形中继网络,为了高效获取级联和单跳链路信道状态信息(Channel State Information, CSI),本文提出基于叠加训练的信道估计方案,以消除多址接入干扰和训练间互干扰为目标,进行最优的多训练序列设计。新方案将中继训练叠加到源训练序列上,通过对中继识别符号以及中继训练组进行联合优化设计,设计了一种基于频域循环移位的正交扩展序列组生成算法。为了消除非高斯复合噪声对单跳信道估计造成的严重干扰,提出了一种中继噪声消除算法。通过两路中继链路获取的信息副本,能够在端节点实现分集合并,有效提高符号检测性能。仿真实验对比了同类型的信道估计方案,分析验证了方案的有效性。      

基于叠加训练序列和低复杂度频域Turbo均衡的时变水声信道估计和均衡

针对时变水声信道估计和均衡问题,该文提出基于叠加训练序列(ST)和低复杂度频域Turbo均衡(LTE)的时变水声信道估计和均衡(ST-LTE)算法。基于叠加训练序列方案,将训练序列和符号线性叠加,使得训练序列和符号信道信息一致;基于最小二乘算法,进行信道估计。基于频域训练序列干扰消除技术,在频域消除训练序列对符号的干扰;基于频域线性最小均方误差(LMMSE)均衡算法,通过先验、后验、外均值和方差的计算,实现低复杂度信道均衡(符号估计);基于Turbo均衡算法,软重构叠加训练序列和更新信道估计,进行均衡器和译码器的信息交换,利用编码冗余信息,大幅度提升信道均衡性能。进行仿真、水池静态通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率4.8 ksym/s,训练序列和符号的功率比为0.25:1)和胶州湾运动通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率3 ksym/s,训练序列和符号的功率比为0.25:1),仿真和试验结果验证了所提算法的有效性。     

基于叠加训练序列的MIMO-OFDM信道估计

为能够估计出MIMO-OFDM系统的信道状态信息(CSI)又能充分利用系统频谱资源,提出了一种基于叠加训练序列的信道估计算法。该算法即将非随机训练序列叠加于信息序列之上,利用训练序列与信息序列的不相关特性,在没有带宽损失的情况下估计出信道参数。并对估计的均方误差性能进行了分析,讨论了训练序列的优化方案。仿真结果证明了该方法的有效性。     

基于叠加训练序列和低复杂度频域Turbo均衡的时变水声信道估计和均衡

针对时变水声信道估计和均衡问题,该文提出基于叠加训练序列(ST)和低复杂度频域Turbo均衡(LTE)的时变水声信道估计和均衡(ST-LTE)算法.基于叠加训练序列方案,将训练序列和符号线性叠加,使得训练序列和符号信道信息一致;基于最小二乘算法,进行信道估计.基于频域训练序列干扰消除技术,在频域消除训练序列对符号的干扰;基于频域线性最小均方误差(LMMSE)均衡算法,通过先验、后验、外均值和方差的计算,实现低复杂度信道均衡(符号估计);基于Turbo均衡算法,软重构叠加训练序列和更新信道估计,进行均衡器和译码器的信息交换,利用编码冗余信息,大幅度提升信道均衡性能.进行仿真、水池静态通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率4.8 ksym/s,训练序列和符号的功率比为0.25:1)和胶州湾运动通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率3 ksym/s,训练序列和符号的功率比为0.25:1),仿真和试验结果验证了所提算法的有效性.     

基于训练序列的MIMO信道估计

提出了一种基于隐训练序列的多输入多输出通信系统的信道估计方法,利用训练序列与信息序列的不相关特性,在没有带宽损失的情况下估计出信道参数。给出了信道估计算法,并对估计的均方误差性能进行了分析,讨论了隐训练序列的优化方案。与以往的隐训练序列估计方法比较,本算法不受接收端直流偏移的限制,且有更低的估计均方误差。计算机仿真结果表明了该估计方法的有效性。     

叠加训练序列设计及其高效传输技术研究

采用训练序列与信息数据叠加的传输方案由于消除训练序列占用的频带开销而受到广泛关注。然而,如何高效的分离叠加信号是实现高效信道估计和可靠检测的基础。通过叠加周期训练序列,研究了基于数据依赖的叠加训练(DDST)方案的高效信道估计和检测方案。并结合信道编码技术,研究了编码条件下DDST方案与传统时分复用(TDM)方案的性能。仿真结果表明,在消除训练带宽开销的情况下,获得DDST方案与TDM的误码率基本保持一致。     

叠加训练序列的判决指导信道估计方法

针对实际应用中信道先验信息未知时无法求解信道相关矩阵的问题,提出了一种改 进的叠加训练序列的判决指导信道估计方法。该方法利用每次迭代的信道估计值求解信道相 关矩阵。推导了该方法中信道相关矩阵的求解公式。仿真结果表明,在未知信道先验信息的 情况下,与利用信道先验信息的叠加训练序列的信道估计方法相比,改进方法取得了与之几 乎一样的性能,因此改进方法更适用于实际应用。     

基于Turbo原理的迭代UWB信道估计方法

针对UWB系统室内密集离散多径信道,提出一种基于Turbo原理的无训练比特的迭代信道估计方法和接收机结构.在迭代信道估计过程中,译码器输出的软信息反馈给信道估计模块,作为信道估计的先验信息使用.以有效提高信道利用率和接收机的性能.仿真结果表明,该信道估计方法能够有效估计信道参数,并且对于信道变化具有较强的跟踪估计能力.     

Data Aided Iterative Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

This work pertains to the use of superimposed training for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. An iterative time domain Least Squares based channel estimator is proposed. The estimator is generalized to provide scope for exploiting the coherence time and the coherence bandwidth of the channel. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance without any change in the structure of the channel estimator. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and also its impact on the bit error rate is shown. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.     

Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.     

一种改进的LTE下行系统信道估计算法

基于3GPP长期演进（LTE）下行链路系统,在比较了现有几种不同信道估计算法的基础上,提出了一种适用于LTE下行系统的时频二维联合维纳迭代滤波信道估计算法。具体步骤如下：首先,采用基于奇异值分解（SVD）的线性最小均方误差（LMMSE）算法在频域进行维纳迭代滤波;然后,再利用频域估计出来的值在时域进行一次维纳迭代滤波。仿真结果表明,该算法能够有效地改善信道估计的误比特率（BER）性能,与传统的方法相比,性能更加接近于理想信道估计,同时也没有显著增加算法的运算复杂度。     

A robust timing and frequency synchronization for OFDM systems

A robust symbol-timing and carrier-frequency synchronization scheme applicable to orthogonal frequency-division-multiplexing systems is presented. The proposed method is based on a training symbol specifically designed to have a steep rolloff timing metric. The proposed timing metric also provides a robust sync detection capability. Both time domain training and frequency domain (FD) training are investigated. For FD training, maintaining a low peak-to-average power ratio of the training symbol was taken into consideration. The channel estimation scheme based on the designed training symbol was also incorporated in the system in order to give both fine-timing and frequency-offset estimates. For fine frequency estimation, two approaches are presented. The first one is based on the suppression of the interference introduced in the frequency estimation process by the training symbol pattern in the context of multipath dispersive channels. The second one is based on the maximum likelihood principle and does not suffer from any interference. A new performance measure is introduced for timing estimation, which is based on the plot of signal to timing-error-induced average interference power ratio against the timing estimate shift. A simple approach for finding the optimal setting of the timing estimator is presented. Finally, the sync detection, timing estimation, frequency estimation, and bit-error-rate performance of the proposed method are presented in a multipath Rayleigh fading channel.     

MC-CDMA系统迭代检测中的一种信道估计算法

在DS—CDMA系统中，联合译码的迭代多用户检测是克服多址干扰增加系统容量的有效方法。本文将多用户检测和译码相结合的迭代检测技术应用于MC—CDMA系统，其中，多用户检测器由串行干扰消除和其后的MMSE滤波器组成。文中提出一种时域信道估计作为迭代初始值的频域信道估计算法，比单纯的频域信道估计方法节约导频符号数量，并且由于信道估计性能的改善，加快了迭代检测的收敛速度。     

Multiuser channel estimation and tracking for long-code CDMA systems

Channel estimation techniques for code-division multiple access (CDMA) systems need to combat multiple access interference (MAI) effectively. Most existing estimation techniques are designed for CDMA systems with short repetitive spreading codes. However, current and next-generation wireless systems use long spreading codes whose periods are much larger than the symbol duration. We derive the maximum-likelihood channel estimate for long-code CDMA systems over multipath channels using training sequences and approximate it using an iterative algorithm to reduce the computational complexity in each symbol duration. The iterative channel estimate is also shown to be asymptotically unbiased. The effectiveness of the iterative channel estimator is demonstrated in terms of squared error in estimation as well as the bit error rate performance of a multistage detector based on the channel estimates. The effect of error in decision feedback from the multistage detector (used in the absence of training sequences) is also shown to be negligible for reasonable feedback error rates using simulations. The proposed iterative channel estimation technique is also extended to track slowly varying multipath fading channels using decision feedback. Thus, an MAI-resistant multiuser channel estimation and tracking scheme with reasonable computational complexity is derived for long-code CDMA systems over multipath fading channels.