OFDM分集接收系统上行链路信道估计研究

对采用时频块组帧的OFDM(正交频分复用)上行链路信道估计进行了研究,给出了基于二维DFT(离散傅里叶变换)的信道估计算法,针对传统二维信道估计方法的边缘效应提出了一种改进办法,即采用分块拟合的方法对信道曲面边缘部分进行补偿估计。仿真表明,改进的二维DFT信道估计方法可以有效地消减边缘效应,从而获得更好的系统性能。     

OFDM系统信道估计算法研究

在OFDM技术应用于移动通信领域时,其信道估计技术是一项关键技术。分析了级联的一维的信道估计方法,采用加窗的方式改进了基于FFT一维级联信道估计算法,在此基础上提出一种新的基于DCT（EIDCT）变换的信道估计算法。最后给出了改进算法的性能仿真,并对仿真结果进行分析。     

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.     

OFDM系统信道估计方法研究

分析了现有实用OFDM系统的信道估计方法及其硬件结构,并根据信道的统计特征给出了一种改进的门限滤波方法与其对应的硬件结构.在提高性能的同时,这种方法复杂度并不高,且不需要任何已知的信道统计特性.通过实验验证,这种新方法(尤其是二维的方法)明显优于传统的基于FFT的方法和最小二乘方法.     

适用于高数据速率和高速移动环境的多相位匹配信道估计方法

本文给出了多相位匹配信道估计方法，通过这种方法，可以有效地将高维的PSK调制的性能改善到低维的PSK性能，使得在高速移动环境中可以应用高维的PSK调制，因而这是一种适用于高数据速率和高速移动环境的一种有效的信道估计方法。     

一种低复杂度的基于多径时延跟踪的OFDM信道估计算法

本文针对宽带正交频分复用（OFDM）系统，提出了一种低复杂度的基于对多径时延跟踪的信道估计算法，并分析了信道估计的均方误差性能和计算复杂度。分析和仿真结果表明，这种算法通过对多径的跟踪降低了需要估计问题的维数，从而提高了信道估计器的性能，并且降低了运算的复杂度。     

适用于任意阵列的多径信道二维方向角与相对时延的联合估计方法

在多径传输的情况下,经常需要估计各路径的二维波达方向角度及相对时延.本文给出了在信道冲激响应可以估计的前提下,一种基于波达方向矩阵法的二维方向角与相对时延的联合估计方法,该方法充分利用了已知的信号码形信息,给出了一种无需进行搜索的闭式解,与基于多维MUSIC或多维ESPRIT的方法相比,具有运算量小的优势.     

基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM系统的组合信道估计方法。采用AR过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE(minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波算法的信道估计性能相当。     

OFDM系统中的自适应信道估计

分析了现有的基于导频的OFDM信道估计技术,提出了一种低复杂度的自适应信道估计方法,并给出了最大时延扩展的实时估计方法,最后通过计算机仿真,给出了多径信道下MSE曲线,以及在DVB-T系统中的BER仿真曲线,验证了其可靠性和良好的性能。     

MIMO-OFDM系统的一种改进型LS信道估计算法

基于多输入多输出正交频分复用(MIMO-OFDM)系统,研究了LS信道估计算法,提出了一种训练序列和块状导频联合LS信道估计算法,给出了权值的计算公式.理论推导和计算机仿真表明,这种改进型的LS信道估计方法提高了LS信道估计的误码率性能,并具有较高的灵活性和较低的复杂度增长.     

Model-based channel estimation for OFDM signals in Rayleigh fading

This paper proposes a robust pilot-assisted channel estimation method for orthogonal frequency division multiplexing (OFDM) signals in Rayleigh fading. Our estimation method is based on nonlinear regression channel models. Unlike the linear minimum mean-squared error (LMMSE) channel estimate, the method proposed does not have to know or estimate channel statistics like the channel correlation matrix and the average signal-to-noise ratio (SNR) per bit. Numerical results indicate that the performance of the proposed channel estimator is very close to the theoretical bit error propagation lower bound that is obtained by a receiver with perfect channel response information     

基于压缩感知的同频干扰下LTE系统信道估计算法

本文提出一种基于压缩感知的同频干扰下长期演进系统信道估计方法。与现有方法不同,本文将干扰和噪声区别对待,利用干扰信号结构建立该系统下多小区信道估计模型(MCCE)。由于无线信道在宽带系统下表现出较为明显的稀疏特性,本文将压缩感知技术应用于上述模型,通过求解新的感知矩阵,并利用多输入多输出信道共有非零支撑集的特性,提出了适用于长期演进系统的联合改进子空间追踪算法(J-MSP),解决了上述模型下字典矩阵列相关度较高的问题;由于所提模型中含有未知的干扰符号,因此还需解决信道和干扰符号的联合估计。仿真结果和分析表明,本文方法在干扰与本小区同步时相比单小区信道估计方法性能显著提升,异步时与最大似然算法性能相当,同时也适用于无干扰场景。      

Channel estimation in ACO-OFDM employing different transforms for VLC

The pronounced eminency of assuring simultaneous illumination and communication has driven Visible Light Communication (VLC) to gain significant ubiquity in recent times. This paper proposes comb type pilot arrangement based channel estimation for Asymmetrically Clipped Optical OFDM (ACO-OFDM) and different multicarrier transmission systems like Discrete Hartley Transform (DHT)-based ACO-OFDM and Fast-Walsh Hadamard transform (FWHT)-based Hadamard Coded Modulation (HCM) over dispersive VLC channel. Various channel estimation algorithms like Least Square (LS), Minimum Mean Square Error (MMSE), and Interpolation techniques namely Linear, Spline, and Low-Pass are evaluated and compared for the aforesaid systems employing different orders of constellation. Here, an elaborate mathematical analysis is accomplished and Cramer Rao Lower Bound (CRLB) is derived for the channel estimation error. Simulated results emphasize that, ACO-OFDM and DHT-based ACO-OFDM have improved Bit Error Rate (BER) performance than HCM at lower Signal to Noise Ratio (SNR), while at higher SNRs HCM dominates the former. Furthermore, the simulated results evidences that, in all multicarrier systems MMSE algorithm has reducible probability of error than LS because, at higher SNRs LS is more susceptible to noise and Spline Interpolation outperforms both LS and MMSE. The simulated results are validated analytically demonstrating good agreement.     

Channel estimation and error correction for UWOC system with vertical non-line-of-sight channel

Recently, underwater wireless optical communication (UWOC) system has placed more attention towards increasing data rate, high accuracy, higher bandwidth and providing highly secured transmission. Generally, light propagation in underwater medium is disturbed due to some degrading effects such as turbulence, scattering and absorption which will degrade the performance. Therefore, channel estimation is essential and need to adapt suitable correction techniques that compensate the errors due to those effects. In this work, channel estimation and error correction technique are proposed for the UWOC system with vertical non-line-of-sight channel based on MIMO-OFDM approach. Initially, input sequence error is eliminated by HVD Turbo coding method and error rectified signal is modulated with M-ary OAM-PPM modulation technique. Modulated signal is transmitted through Vertical NLOS channel. During transmission, the signal undergoes scattering, absorption and channel fading. In receiver side, channel characteristics are estimated by invariant embedding method. Finally, estimated signal is demodulated and decoded by same techniques. MATLAB environment is used to implement the proposed work. Resultant performances like channel capacity, BER, SNR, data rate, receiving power and MSE for different water types like pure sea water, ocean water, costal water and turbid water are compared and results are examined.

     

Channel estimation with ISFLA based pilot pattern optimization for MIMO OFDM system

In multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems, the channel state information should be known by the receiver for obtaining transmitted data. Channel estimation algorithms are used to examine the multipath effects of frequency selective Rayleigh fading channels. In this paper, Compressed Sensing (CS) based channel estimation technique is considered for reconstructing the signal with improved spectral efficiency. It requires transmitting the known pilot data to the receiver for estimating channel information. The optimum pilot patterns are selected through reducing the mutual coherence of measurement matrix. In order to maximize the accuracy of sparse channel estimation and to reduce the computational complexity, an optimization algorithm Improved Shuffled Frog Leaping (ISFL) is proposed. When compared with the traditional estimation methods like least squares (LS), and minimal mean square error (MMSE), 4.7% of spectral efficiency is increased with ISFLA based channel estimation. Implementation results show that, by using the proposed algorithm, the bit error rate (BER) and Mean Square Error (MER) performance of the system is increased with 1.5 dB and 2 dB respectively.     

Deep Learning Based Semi-Blind Tracking for Aging Wireless Communication Channels

The time-varying nature of the wireless propagation channel under high user mobilities, termed as channel aging, is a major performance impediment in many communication systems. In this paper, we discuss deep learning models for semi-blind channel estimation in a single input single output wireless communication system under channel aging. In our proposed scheme, we first use pilot based training to obtain initial channel estimates. Following this, we treat the detected symbols as pilots and perform further channel estimation using an Encoder-Decoder LSTM network for constant and sliding window schemes. To show the effectiveness of our method, we show the training capabilities of our models and the BER vs SNR graphs for multiple simulations. We discuss integrating these Encoder-Decoder LSTM models with deep learning enabled symbol detection techniques like the DetNet to further improve spectral efficiency. The Encoder-Decoder LSTM network gives us a low BER, with the moving window scheme outperforming the constant window scheme.

     

Performance Analysis of Subspace Based Downlink Channel Estimation for W-CDMA Systems Using Chaotic Codes

This paper presents blind channel estimation for downlink W-CDMA system that employs chaotic codes and Walsh codes for spreading information bits of the multiple users. In a W-CDMA system, while transmitting over multipath channels, both intersymbol interference (ISI) as a result of Inter Chip Interference and multiple access interference (MAI) cannot be easily eliminated. Although it is possible to design multiuser detectors that suppress MAI and ISI, these detectors often require explicit knowledge of at least the desired users’ signature waveform. Earlier work focused on a subspace based channel estimation algorithm for asynchronous CDMA systems to estimate the multiple users’ symbols, where only AWGN channel was considered. In our work, we study a similar subspace-based signature waveform estimation algorithm for downlink W-CDMA systems, which use chaotic codes instead of pseudo random codes, that provide estimates of the multiuser channel by exploiting structural information of the data output at the base station. In particular, we show that the subspace of the (data+noise) matrix contains sufficient information for unique determination of channels, and hence, the signature waveforms and signal constellation. We consider Rayleigh and Rician fading channel model to quantify the multipath channel effects. Performance measures like bit error rate and root mean square error are plotted for both chaotic codes and Walsh codes under Rayleigh and Rician fading channels.     

A new derivation of least-squares-fitting principle for OFDM channel estimation

Many channel estimation and data detection algorithms of the orthogonal frequency division multiplexing (OFDM) system have been proposed. Some of these algorithms are based on the principle of linear minimum mean-square error (LMMSE) estimation, which is theoretically optimal. There are also some algorithms developed based on the least-squares-fitting (LSF) principle, which finds a regression polynomial to fit a block of tentative channel estimates in the least-squares sense. The LSF principle is a non-statistical approach, while the LMMSE algorithm is statistical and it needs to known or estimate the channel statistics like correlation matrices and signal-to-noise ratio (SNR). This letter proposes a novel viewpoint of the LSF principle. We show that the non-statistical LSF principle can be derived alternatively from the statistical LMMSE principle by eigenvector approximation. This constructs a link between these two principles. The mean-square estimation error (MSEE) analysis shows that there are common terms in the MSEE expressions of these two principles. This further validates the constructed link. Based on the derived link and MSEE analysis, we also give some characteristics and discussions of the LSF principle.     

Performance Analysis of Ranging Process in Diversity Incorporated Wireless Systems Suffering from Narrowband Jamming

Ranging is a process where the base station (BS) identifies a mobile station (MS) among many other MSs with the help of Ranging code set, which is unique to each MS. Also, an estimation process is made to find the transition time delay which is the difference between the time at which the MS sends some data and the time at which the BS receives data. In this paper, the effect caused by jamming on the Ranging process will be analyzed. Jamming destroys orthogonality/pseudo orthogonality of the Ranging code set which affects the estimation of the codes. This in turn affects parameters like detection miss rate. This paper also discusses the improvement in the Ranging process where diversity techniques like maximal ratio combining (MRC), selection combining (SC), and equal gain combining are used. These diversity techniques are used in various fading channel models like Rayleigh, Rician, and Nakagami. The analyses indicate that for a Rayleigh fading channel, the code word error rate (CER) decreases by two orders of magnitude for a SC case as compared to the no diversity case, and that CER reduces by three orders of magnitude for an Equal Gain/MRC case as compared to the no diversity case. Similar results are observed for Rician and Nakagami fading channels also.