基于隐训练序列的信道估计与跟踪

提出了新的基于隐训练序列的频率选择性信道估计方法,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。文中对所提方法给予了证明,给出了信道估计算法,并提出了改进的自适应形式,可以用于跟踪时变信道。与以往的隐训练序列估计方法比较,文章中的算法具有更低的估计均方误差,不受接收端直流偏移的限制,且适用于时变信道。计算机仿真结果表明了该估计方法的有效性。     

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。     

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。     

Channel estimation using aperiodic binary sequences

Estimating a channel impulse response using a known aperiodic sequence is considered. The problem can be reduced to minimizing the trace of the inverse of a Toeplitz matrix. An efficient algorithm for computing this trace is developed and optimal binary sequences up to length 32 are found and tabulated. The use of complementary sequences in this context is also investigated. It is shown that the eigenvalues of the autocorrelation matrices of a pair of complementary sequences sum to a known constant     

基于叠加训练序列快速信道辨识方法

信道状态信息(CSI)对于无线通信来说至关重要,而叠加训练序列的信道估计方法由于不占用额外的信号带宽和具有较高的估计精度而受到人们的注意.本文从算法的复杂度入手,分析了不同的训练序列对算法复杂度的影响,并且在训练序列为PN序列下,利用循环Toeplitz矩阵的特性,得到了信道估计的快速算法.仿真实验的结果表明,这种算法不需要矩阵求逆、计算量小,估计精度高,有很大的实际应用前景.     

Channel estimation using pilot tones in OFDM systems

Channel estimation techniques using pilot tones in OFDM systems are investigated. Two time-domain channel estimation methods are proposed. Based on theoretical analysis and computer simulation, for a channel with multipath distortion and AWGN, the proposed time-domain channel estimation schemes perform better than the conventional frequency-domain channel estimation techniques     

Channel estimation for AF relaying using ML and MAP

Channel state information is very important in cooperative communication for performance improvement or signal demodulation. Previous works on channel state information estimation mainly focus on least squares and minimum mean squared error estimators. In this work, several new maximum likelihood and maximum a posteriori estimators for the cooperative network are proposed. Two of them estimate the individual channel powers of different links using all pilots from the source node, while two of them estimate the individual channel gains of different links using pilots from the source node as well as the relay node. Numerical results show that the estimation error decreases when the signal-to-noise ratio increases or when the number of pilots increases. The estimators for the individual channel gains have normalized mean squared errors of less than 0.001 when the signal-to-noise ratio is 30 dB, and their bit error rate performances are very close to the perfect case. Importantly, channel estimation is performed at the destination only such that there is no extra complexity at the relay node.

     

多中继协同通信系统中基于循环正交训练序列的信道估计算法

提出了一种实用的基于循环正交序列的信道估计算法。源节点发送循环正交的信道训练序列,各个中继节点对接收到的信道训练序列进行不同间隔的循环移位后向目的节点转发。尽管各个中继转发的序列在时间上是叠加的,但序列之间不存在相关性。由此可以推导出相应的最小二乘信道估计和线性最小均方误差信道估计。仿真结果证明该算法具有较高的估计精度和效率,同时运算复杂度较低。     

利用训练序列进行无线局域网信道估计

研究了基于训练序列的无线局域网信道估计的几种方法，通过Matlab算法仿真分析，总结出适用IEEE802．1la的信道估计方法。并指出了各种算法的优缺点及适用条件，有利于无线局域网信道估计与均衡的硬件实现。     

Channel parameter estimation in mobile radio environments using theSAGE algorithm

This study investigates the application potential of the SAGE (space-alternating generalized expectation-maximization) algorithm to jointly estimate the relative delay, incidence azimuth, Doppler frequency, and complex amplitude of impinging waves in mobile radio environments. The performance, i.e., high-resolution ability, accuracy, and convergence rate of the scheme, is assessed in synthetic and real macro- and pico-cellular channels. The results indicate that the scheme overcomes the resolution limitation inherent to classical techniques like the Fourier or beam-forming methods. In particular, it is shown that waves which exhibit an arbitrarily small difference in azimuth can be easily separated as long as their delays or Doppler frequencies differ by a fraction of the intrinsic resolution of the measurement equipment. Two waves are claimed to be separated when the mean-squared estimation errors (MSEEs) of the estimates of their parameters are close to the corresponding Cramer-Rao lower bounds (CRLBs) derived in a scenario where only a single wave is impinging. The adverb easily means that the MSEEs rapidly approach the CLRBs, i.e., within less than 20 iteration cycles. Convergence of the log-likelihood sequence is achieved after approximately ten iteration cycles when the scheme is applied in real channels. In this use, the estimated dominant waves can be related to a scatterer/reflector in the propagation environment. The investigations demonstrate that the SAGE algorithm is a powerful high-resolution tool that can be successfully applied for parameter extraction from extensive channel measurement data, especially for the purpose of channel modeling     

On channel estimation using superimposed training and first-order statistics

Channel estimation for single-input multiple-output (SIMO) time-invariant channels is considered using only the first-order statistics of the data. A periodic (nonrandom) training sequence is added (superimposed) at a low power to the information sequence at the transmitter before modulation and transmission. Recently superimposed training has been used for channel estimation assuming no mean-value uncertainty at the receiver and using periodically inserted pilot symbols. We propose a different method that allows more general training sequences and explicitly exploits the underlying cyclostationary nature of the periodic training sequences. We also allow mean-value uncertainty at the receiver. Illustrative computer simulation examples are presented.     

基于叠加训练的非合作多用户/MIMO信道估计

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的“训练序列”来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。     

Channel estimation using complementary sequence pairs for UWB/OFDM systems

It is well known that time domain channel estimation can achieve better performance than frequency domain channel estimation with a time-multiplexed preamble in common OFDM systems. When it is applied to UWB/OFDM systems, however, its high complexity becomes the main obstacle because of the large number of resolvable paths. To solve this problem, a low-complexity channel estimation scheme is presented by exploiting a special construction of complementary sequence pairs.     

Channel estimation for multicarrier modulation systems using a time-frequency polynomial model

Channel estimation is a crucial aspect in the design of multicarrier modulation systems. We propose a channel estimation scheme based on polynomial approximation of the channel responses in both the time and frequency domains. The proposed estimator is more robust to the variations of channel statistics. Our simulation shows that it has more than a 5-dB improvement over the existing methods under practical channel conditions     

Channel estimation for OFDM systems using adaptive radial basis function networks

We propose a new scheme for pilot-symbol-aided channel estimation in orthogonal frequency-division multiplexing (OFDM) systems in multipath fading channels, that does not require knowledge of the channel statistics (e.g., Doppler or power spectrum). It is based on using the radial basis function (RBF) network to model the dynamics of the fading process. Both one-dimensional and two-dimensional RBF networks are proposed to exploit the channel correlation in the time domain and in the time-frequency domain. The proposed RBF networks are essentially nonlinear interpolators of the pilot channels. Compared with the existing OFDM channel estimation methods based on linear filtering, the proposed new techniques offer both robustness to fading rate, and a better performance especially in relatively fast fading channels.     

Joint I/Q imbalances estimation using data-dependent superimposed training

In this paper, we address the joint estimation of the channel impulse response and frequency-dependent in-phase and quadrature-phase (I/Q) imbalances using data-dependent superimposed training (DDST). The analysis developed shows that it is possible to use the first-order statistics of the received process to achieve synchronization and identify the resulting widely linear system that encompasses the radio frequency impairments considered. Furthermore, it is also verified that for the joint estimation of the transmitter and the receiver I/Q imbalances, additional constraints than those required for strictly linear systems should be imposed on the training sequences employed. The results of numerical simulations show that DDST has comparable performance with methods reported in the literature.     

Channel and capacity estimation errors

Systems with multiple element transmitter and receiver arrays have been shown to achieve very high spectral efficiencies. The theoretically achievable Shannon capacity is a function of the channel between the transmitters and the receivers. On the simulation level, one assumes certain statistical characteristics for the channel, but on a practical level, the actual channel is measured. We show that the accuracy of the measurements affects the accuracy of the capacity estimation when using the Shannon formula. We study analytically how the channel estimation error appears in the capacity formula, and we derive mathematical expressions for the first- and second-order approximations of the error. We also present simulation results that show the effect of the system size, the measurement accuracy, the system signal-to-noise ratio and the nature of the channel itself on the accuracy of the estimation of the channel capacity.     

Channel estimation by symmetrical clustering

A new blind channel estimation algorithm is presented. This algorithm comes from the well-known maximum likelihood estimation approach. However, we intentionally "smooth" the joint probability density function (PDF) of a finite set of observations in order to reduce the computational burden. As a result, we obtain an online clustering algorithm whose main characteristic is the constraint of symmetry among cluster centers. Computational simulations are used to evaluate this algorithm     

Channel estimation for ultra-wideband communications

This paper deals with channel estimation in ultra-wideband communications operating in a multipath environment and in the presence of multiaccess interference. The channel parameters are the attenuations and delays incurred by the signal echoes along the propagation paths. Time-hopping modulation with binary symbols is assumed. The estimation method is based on the maximum-likelihood criterion and is applied to two different scenarios: either with known symbols (DA estimation) or with unknown symbols (NDA estimation). The effects of the estimation errors on the performance of a RAKE receiver are assessed by simulation by comparing the receiver bit-error rate with either perfect channel estimates or imperfect estimates as obtained from the proposed algorithms. The results show that the degradations are tolerable as long as the number of users is limited. They also show that the DA method has an edge over the NDA in that it can handle a larger number of users for a fixed degradation. The number of users that can be accommodated in practice is found for some values of the system parameters.     

基于SC-FDMA的信道估计研究

介绍了SC-FDMA系统的基本原理和四种不同的信道估计方法:LS,LMMSE,DCT,DFT。在16QAM和QPSK调制情况下对四种信道估计方法进行比较分析,得出了不同信道估计算法下误符号率的性能曲线。仿真结果表明LMMSE性能最佳,LS性能最差,DCT性能优于DFT性能。