宽带MIMO-OFDM系统信道估计算法研究

本文提出了MIMO-OFDM系统中基于LS准则的参数化信道估计方法(LSPCE),推导出其MSE性能的下界并给出一种最优导频序列.为了降低复杂度,本文还提出了一种迭代的算法,它利用有限冲击响应信道的抽头之间的相关性从噪声中提取出信道信息并同时估计出多径时延.仿真和分析表明,相比传统的LS信道估计算法,这种基于参数化的信道估计算法可以大大提高信道估计的精度,接收端的检测性能接近理想信道估计的性能.     

Decision Feedback Channel and Symbol Estimation Methods for CDMA Systems in Indoor Wireless Communications

A dispersive finite impulse response (FIR) channel model is often considered for indoor wireless channels. For the FIR channel model in this paper, we consider the joint estimation of channel parameters and data symbols in indoor code division multiple access (CDMA) systems. The least squares formulation is constructed for the joint estimation incorporating the decision feedback technique. This formulation is suitable for indoor CDMA systems that usually have a small processing gain. The formulation is further modified to provide a recursive approach to estimate the channel vector.     

Improved Channel Estimation Based on Parametric Channel Approximation Modeling for OFDM Systems

Orthogonal frequency division multiplexing (OFDM) together with high order modulation scheme requires accurate channel estimation to perform coherent demodulation. In this paper, improved channel estimation methods based on a parametric channel approximation model are proposed for the OFDM system using pilot subcarriers. This channel model is called fraction taps channel approximation (FTCA) model, which is defined as a finite impulse response (FIR) on some definitive delay taps that have a fraction tap delay spacing relative to the sampling interval. Then, based on the FTCA channel model, the minimum mean square error (MMSE) and least square (LS) estimators are derived. Simulations over non-sample-spaced channels prove that the use of the FTCA channel model can effectively eliminate the problem of multi-path delay estimation and reduce the signal subspace dimension of the channel correlation matrix, where the full-rank estimators using pilot subcarriers can be adopted, and consequently, improve the channel estimation performance.     

Blind channel estimation via combining autocorrelation and blind phase estimation

Symbol spaced blind channel estimation methods are presented which can essentially use the results of any existing blind equalization method to provide a blind channel estimate of the channel. Blind equalizer's task is reduced to only phase equalization (or identification) as the channel autocorrelation is used to obtain the amplitude response of the channel. Hence, when coupled with simple algorithms such as the constant modulus algorithm (CMA) these methods at baud rate processing provide alternatives to blind channel estimation algorithms that use explicit higher order statistics (HOS) or second-order statistics (subspace) based fractionally-spaced/multichannel algorithms. The proposed methods use finite impulse response (FIR) filter linear receiver equalizer or matched filter receiver based infinite impulse response+FIR linear cascade equalizer configurations to obtain blind channel estimates. It is shown that the utilization of channel autocorrelation information together with blind phase identification of the CMA is very effective to obtain blind channel estimation. The idea of combining estimated channel autocorrelation with blind phase estimation can further be extended to improve the HOS based blind channel estimators in a way that the quality of estimates are improved.     

用滤波器组构成的传送多路复用器结构实现MMSE盲信道均衡

冗余滤波器组构成的传送多路复用器可以用来对FIR信道进行估计和均衡.本文提出一种在FIR滤波器组框架结构下,首先利用信号的相关矩阵对信道进行估计,然后在此基础上用MMSE准则下设计的FIR均衡器对数据进行均衡的盲算法.该均衡算法的性能要明显好于基于ZF准则的方法,并且在消除ISI的同时可以抑制噪声的影响,从而使系统的输出信噪比达到最优,而增加的复杂度很有限.文中最后在两种典型信道下对所提出的盲信道均衡算法进行了仿真,结果验证了上述性能.     

在脉冲噪声环境中用于快衰信道估计的改进型算法

该文分析了在存在噪声干扰的情况下,进行估计快衰信道的方法。在无线通信系统中,快衰信道可以采用AR(Auto-Regressive)模型进行预测,而LS (Least Square)算法和自适应Kalman滤波器可以分别对AR模型的参数和信道的冲激响应进行估计,但是这两种算法对噪声干扰非常敏感。该文提出改进型的RLM算法和Kalman 滤波器,并在存在噪声的情况下,使用它们并行对AR参数和信道的冲激响应进行联合估计。仿真结果显示:相比于传统的算法,改进后的算法在联合估计信道时,提高了抵抗大脉冲干扰的能力,加快了待估的参数的收敛速度。     

基于SVD的LC_CDMA通信系统信道估计研究

在LC-CDMA通信系统中，由于在多径衰落信道下使用了时变扩频码，使得信道估计非常困难，而对接收机的设计往往需要信道的先验知识。本文建立了长码条件下的CDMA通信系统模型和多径频率选择性衰落信道的FIR滤波器模型，利用子空间分解的方法，推导了长码条件下CDMA通信系统的信道估计算法，并仿真分析算法的性能。     

WRAN系统中基于自适应内插的信道估计算法

提出了一种基于自适应复系数内插的信道估计算法,改善了无线区域网络（WRAN）系统对抗动态多径时延的能力。WRAN是第一个采用认知无线电技术改善频谱效率的宽带接入标准,系统在下行链路中采用了正交频分复用（OFDM）调制技术,而信道估计技术对于采用相干解调的OFDM系统十分重要。传统的OFDM信道频域响应（CFR）估计算法通常采用实系数频域内插的方式,在对抗WRAN系统长多径时延信道时,不能有效地工作。该文在研究实系数FIR内插变换域响应的基础上,提出了一种复系数内插算法。为了同时适用于短时延信道,提出了一种低复杂度、自适应匹配信道最大多径时延的算法。通过仿真,验证了该算法能够对抗更大的多径时延,提高信道估计的精度,改善系统误码性能。      

叠加弱能量训练序列信道估计方法

本文提出了一种利用叠加弱能量的周期训练序列进行信道估计的线性最小均方误差(LMMSEE)算法.该方法不需要信道先验信息、不占用宝贵的带宽资源、计算量比常规LS方法更低.理论分析和计算机仿真表明:在训练序列周期比信道冲击响应长度大时,在较低的信噪比下,利用LMMSEE方法估计信道性能比LS方法更佳.     

Interpolated narrowband lowpass FIR filters

The article describes a class of digital filters, called interpolated finite impulse response (IFIR) filters that can implement narrowband lowpass FIR filter designs with a significantly reduced computational workload relative to traditional FIR filters. Topics discussed include: optimum expansion factor choice, number of FIR filter taps estimation, IFIR filter performance modeling, passband ripple considerations, implementation, and filter design.     

适合频率选择性MIMO信道的FIR预编码器

改善频率选择性多输入多输出(MIMO)系统的信道容量,具有重要的理论和现实意义。基于最大信道容量准则,提出一种适合MIMO频率选择性衰落信道的预编码新方法。该方法将预编码器建模为一个有限冲击响应(FIR)滤波器,利用秩松弛将原非凸优化问题转换成为半定规划(SDP)问题,并结合特征值分解设计预编码器。仿真实验结果和分析表明,相对于扩展均匀信道分解(EUCD)等其它现有算法,该算法仅需较少的滤波器阶数即可显著提升系统的信道容量,具有较低的实现复杂度。     

Pilot-Aided OFDM Channel Estimation in the Presence of the Guard Band

In this letter, pilot design and channel estimation are discussed for orthogonal frequency-division multiplexing (OFDM) systems with guard subcarriers. First, we investigate the effects of guard band on channel estimation errors. From this, we propose pilot placement having a maximum distance between adjacent pilots except for the guard band, and show that it achieves minimum channel estimation errors among partially equispaced pilots using equivalence of the Toeplitz and circulant matrices. Also, an efficient channel estimator is developed by introducing an extended channel and its finite impulse response (FIR) approximation to overcome high numerical complexity caused by the presence of guard subcarriers and the use of a large number of subcarriers. Simulation results are presented for OFDM and orthogonal frequency division multiple access (OFDMA) systems consistent with IEEE 802.16a standards.     

基于均衡代价函数的信道阶数盲估计算法

针对信道阶数估计问题,利用单输入多输出(Single-Input Multiple-Output,SIMO)有限冲激响应(Finite Impulse Response,FIR)信道的结构特点和输入/输出信号的统计特征,提出了一种基于均衡代价函数的信道阶数盲估计算法.首先计算了归一化最小二乘均衡(Normalized Least Squares Equalization,NLSE)代价函数在理想条件下的理论渐近值,并指出其拐点与信道阶数之间的对应关系.然后分析了NLSE代价函数在实际条件下的近似值.最后引入了拐点优化因子,提出了一种基于NLSE代价函数拐点检测的信道阶数估计算法.理论分析和仿真结果表明,在信噪比(Signal-to-Noise Ratio,SNR)较低和信道首尾系数较小的情况下,该算法比现有其它方法具有更强的鲁棒性,可以获得更小的接收信号均衡误差.     

Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels

In various signal-channel-estimation problems, the channel being estimated may be well approximated by a discrete finite impulse response (FIR) model with sparsely separated active or nonzero taps. A common approach to estimating such channels involves a discrete normalized least-mean-square (NLMS) adaptive FIR filter, every tap of which is adapted at each sample interval. Such an approach suffers from slow convergence rates and poor tracking when the required FIR filter is "long." Recently, NLMS-based algorithms have been proposed that employ least-squares-based structural detection techniques to exploit possible sparse channel structure and subsequently provide improved estimation performance. However, these algorithms perform poorly when there is a large dynamic range amongst the active taps. In this paper, we propose two modifications to the previous algorithms, which essentially remove this limitation. The modifications also significantly improve the applicability of the detection technique to structurally time varying channels. Importantly, for sparse channels, the computational cost of the newly proposed detection-guided NLMS estimator is only marginally greater than that of the standard NLMS estimator. Simulations demonstrate the favourable performance of the newly proposed algorithm.     

Blind MMSE Equalization of FIR/IIR Channels Using Oversampling and Multichannel Linear Prediction

A linear‐prediction‐based blind equalization algorithm for single‐input single‐output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second‐order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single‐input multiple‐output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum‐mean‐square‐error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.     

基于失配序列的OFDM信道估计

本文提出了一种利用失配序列进行OFDM信道估计的新方法。在发端将失配序列加入到OFDM信号中作为训练序列,接收端将收到的去掉循环前缀的失配序列与失配滤波器系数的循环移位序列做相关运算,利用失配序列的优良自相关特性,估计出信道的冲击响应,进而得到子载波处信道的频率响应。理论分析和仿真结果表明,该方法计算复杂度低,估计速度快、精度高,系统的BER性能好。      

基于变论域模糊控制光伏MPPT算法的仿真研究

通常采用模糊控制算法设计的控制器对实现光伏系统MPPT控制具有针对性,在光伏系统或控制器参数改变时,会出现跟踪速度慢、稳定性差、甚至跟踪失效等问题。针对此问题,文中采用一种基于变论域模糊控制的MPPT算法,利用电导增量法的跟踪原理设计控制器的模糊规则来提高控制器的普适性。该算法引入伸缩因子实现变论域的设计以降低控制器参数改变对跟踪效果的影响。在MATLAB/Simulink中的仿真结果表明,变论域模糊控制法在跟踪速度上相较于电导增量法提高了近一倍,且在论域失配与光伏系统模型失配情况下,相比于常规模糊控制能够更好地实现光伏系统MPPT控制。     

Performance of symbol-sampled receivers over unknown continuous-time Rayleigh channels

The performance of symbol-sampled receivers is usually evaluated via Forney's finite impulse response (FIR) model for the equivalent channel [discrete-time transversal filter (DTTF)]. This model contains a matched filter, and, thus, requires prior knowledge of the continuous-time channel-impulse response. Therefore, if the channel is continuous and unknown, it is unrealistic to use the DTTF model, which leads to an upper bound on the system performance. Using an alternative model for the equivalent discrete-time channel, where the matched filter is replaced by a receive filter matched to the symbol waveform, we propose a framework to quantitatively investigate the performance loss from a theoretical perspective. The theoretical results are corroborated using a practical system.     

Blind estimation of a fractionally sampled FIR channel for OFDM transmission using residue polynomials

This paper introduces blind-channel estimation methods using residue polynomials for orthogonal-frequency-division-multiplexing (OFDM) transmission under the assumption that the channel is finite-impulse response (FIR). In terms of z transform, if the received signal is multiplied by the inverse of the transmitted signal, the resulting z transform renders the channel transfer function when additive noise is absent in the channel. For an FIR channel, samples of the recovered impulse response must be zero in the region of zeros of the channel impulse response. Based on this observation, the blind estimation problem is formulated as a solution of linear equations, treating the transmitted symbols as unknown variables. Polynomial residue arithmetic turns out to be very useful for deriving the linear equations. The proposed method is computationally more efficient than subspace methods that are applied for OFDM transmission systems. In addition, unlike subspace methods, the proposed method is deterministic and does not require estimation of the autocorrelation matrix of received signals, which is required in subspace methods.     

Modified Metaheuristic Algorithms for the Optimal Design of Multiplier-Less Non-uniform Channel Filters

Reconfigurable non-uniform channel filters are now being widely used in software define radio (SDR). The hardware implementation of these filters requires low complexity, low chip area and low power consumption. The frequency response masking (FRM) approach is proved to be a good candidate for the realization of a sharp digital finite impulse response (FIR) filter with low complexity. To reduce the complexity further, this paper gives an optimal design method which makes the channel filters totally multiplier-less. This is done in two steps. The channel filters are designed using the FRM approach with continuous filter coefficients. To obtain multiplier-less design, these filter coefficients are converted to finite-precision coefficients using signed power of two (SPT) space and the filter coefficients are synthesized in the canonic signed-digit (CSD) format. But this may lead to degradation of the filter performance. Hence the filter coefficients synthesis in the CSD format is formulated as an optimization problem. Several meta-heuristic algorithms like Differential Evolution (DE), Artificial Bee Colony (ABC), Harmony Search Algorithm (HSA) and Gravitational Search Algorithm (GSA) are modified and deployed and the best one is selected.