Progressive intercarrier and co‐channel interference mitigation for underwater acoustic multi‐input multi‐output orthogonal frequency‐division multiplexing

Multi‐input multi‐output orthogonal frequency‐division multiplexing (MIMO‐OFDM) has been actively studied for high data rate communications over the bandwidth‐limited underwater acoustic (UWA) channels. Unlike existing receivers that treat the intercarrier interference (ICI) as additive noise, in this paper, the proposed receiver considers ICI explicitly together with the co‐channel interference (CCI) due to parallel transmissions in MIMO‐OFDM. Using a recently developed progressive receiver framework, the proposed receiver starts with low‐complexity ICI‐ignorant processing and then progresses to ICI‐aware processing with increasing ICI levels. The key components of the proposed receiver include the following: (1) compressed sensing‐based sparse channel estimation, (2) soft‐input soft‐output minimum mean square error/Markov chain Monte Carlo detector for interference mitigation, and (3) soft nonbinary low‐density parity check decoding. In addition to simulation, we use real data from the Surface Processes and Acoustic Communications Experiment 2008 (SPACE08) and the Mobile Acoustic Communications Experiment 2010 (MACE10) to verify the system performance, where the transmitter in SPACE08 was stationary and that in MACE10 was slowly moving. Simulation and experimental results show that explicitly addressing ICI and CCI significantly improves the performance of MIMO‐OFDM in UWA systems. Copyright © 2012 John Wiley & Sons, Ltd.     

基于SAMP重构算法的OFDM系统稀疏信道估计方法

为了提高OFDM系统稀疏信道估计的精度和减少导频子载波的数目,本文将OFDM系统频率选择衰落信道时域稀疏冲激响应的参数估计问题转化为压缩感知理论中在稀疏度未知及存在噪声干扰情形下复数稀疏信号的重构问题,提出了分别基于基追踪降噪（BPDN）和稀疏度自适应匹配追踪（SAMP）的两种OFDM系统稀疏信道估计方法。在导频数和信噪比均相同的情形,与传统的最小二乘法（LS）、匹配追踪-最小二乘法（MP-LS）的信道估计方法相比,仿真结果表明所提出的两种方法无须将信道的稀疏度作为先验知识,并具有归一化均方误差小和误比特率低的优点。在所提出的两种方法中,基于SAMP的方法比基于BPDN的方法具有运行速度快、性能更接近Cramer-Rao界的优点,且导频子载波仅为系统子载波的12.5%,信噪比约大于10dB时,采用基于SAMP的方法在信道稀疏度未知的情形也能获得满足实际应用的误比特率。      

A channel estimation algorithm for optical orthogonal frequency division multiplexing systems

A simple channel estimation （CE） scheme, which is pilot-aided with just a little number of pilots inserted in the first half part of the subcarriers, is proposed and simulated for resisting the fiber dispersion in optical orthogonal frequency division multiplexing （OFDM） systems. The simulation results verify that the receiver sensitivity is improved by 2-3 dBm for bit error rate （BER） of 10^-3 with the proposed CE algorithm than that with other kinds of CE algorithms based on linear square principle. The good constellation performance for a 40 Gbit/s transmission system can be also obtained by the proposed scheme.     

Channel‐estimate‐based frequency‐domain equalization (CE‐FDE) for broadband single‐carrier transmission

A channel‐estimate‐based frequency‐domain equalization (CE‐FDE) scheme for wireless broadband single‐carrier communications over time‐varying frequency‐selective fading channels is proposed. Adaptive updating of the FDE coefficients are based on the timely estimate of channel impulse response (CIR) to avoid error propagation that is a major source of performance degradation in adaptive equalizers using least mean square (LMS) or recursive least square (RLS) algorithms. Various time‐domain and frequency‐domain techniques for initial channel estimation and adaptive updating are discussed and evaluated in terms of performance and complexity. Performance of uncoded and coded systems using the proposed CE‐FDE with diversity combining in different time‐varying, multi‐path fading channels is evaluated. Analytical and simulation results show the good performance of the proposed scheme suitable for broadband wireless communications. For channels with high‐Doppler frequency, diversity combining substantially improves the system performance. For channels with sparse multi‐path propagation, a tap‐selection strategy used with the CE‐FDE systems can significantly reduce the complexity without sacrificing the performance. Copyright © 2004 John Wiley & Sons, Ltd.     

A sequential Monte Carlo blind receiver for OFDM systems infrequency-selective fading channels

We consider the application of the sequential Monte Carlo (SMC) methodology to the problem of blind symbol detection in a wireless orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective fading channel. Bayesian inference of the unknown data symbols in the presence of an unknown multipath fading channel is made only from the observations over one OFDM symbol duration. A novel blind SMC detector built on the techniques of importance sampling and resampling is developed for differentially encoded OFDM systems. The performance of different schemes of delayed-weight estimation methods is studied. Furthermore, being soft-input and soft-output in nature, the proposed SMC detector is employed as the first-stage demodulator in a turbo receiver for a coded OFDM system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations     

Performance enhancement of UWA‐OFDM communication systems based on FWHT

The available bandwidth of underwater environment tends to several kilohertz, which considers the main challenges of communications under sea water. On the other hand, the bit‐error‐rate (BER) performance degrades because of several reasons such as multipath propagation, time variabilities of the channel, attenuation, and water temperature. In this paper, we aim to improve the underwater acoustic (UWA) BER system performance by using orthogonal frequency division multiplexing (OFDM) based on fast Walsh‐Hadamard transform (FWHT) instead off fast Fourier transform (FFT). We proposed a low‐complexity equalization and carrier frequency offset (CFO) compensation for UWA‐OFDM–based FWHT using banded‐matrix approximation concept. Simulation results show that the UWA‐OFDM–based FWHT with low‐density parity check (LDPC) codes give a good improvement performance compared with traditional OFDM in UWA system especially in case of estimation errors.     

Channel Estimation for Cyclic Postfixed OFDM

A novel channel estimation algorithm is presented in this paper for the recently proposed cyclic postfix based on orthogonal frequency division multiplexing （OFDM） systems. Phase equalization with the erasure decision is used to reduce both the channel estimation error and the computational complexity. Simulation results show that the proposed channel estimation algorithm can effectively estimate the channel impulse response （CIR） and the performance of the proposed phase equalization with erasure decision is comparable with the minimal mean square error （MMSE） equalization, but it offers less computational complexity.     

一种改进的快变信道展开模型

 在高速移动正交频分复用系统（OFDM）中,信道的快速变化引起载波间干扰,降低系统性能,且使信道的准确估计变得更为困难. 由于在接收端待估计的信道参数多于接收信号样点数,信道估计方程无确定解. 为了解决这一问题,通常将快变信道展开为基函数叠加的近似表达形式,信道估计问题变成对展开系数的估计,待估计的参数大大减少. 本文分析并比较了常用的基展开模型的特点,指出了它们的不足,并在此基础上提出一种改进的快变信道展开模型,该模型的核心思想是在过采样基础上通过基线补偿减小吉布斯效应的影响,从而减小展开误差. 该模型性能与信道的统计性质无关,且在展开基的变化赶不上实际信道变化速度时,展开误差不会明显增大,优于CE-BEM, GCE-BEM, KL-MEM等模型,可用于高速移动OFDM系统的快变信道估计.     

无CP的OFDM联合信道估计和干扰抵消

无循环前缀OFDM无线通信系统可以提高频谱利用效率。提出一种基于无循环前缀(CP)OFDM系统的联合信道估计和干扰抵消算法。采用最小二乘法(Least Square)估计信道时域矢量,通过离散傅里叶变换(DFT)得到相应的OFDM信道的频域特性,由迭代算法对信号进行联合检测和干扰抵消。仿真结果表明,信道估计结果能够达到较高的精度,误码率也接近有循环前缀的OFDM无线通信系统。     

采用BICM-ID的PP-OFDM系统及后缀幅度优化

该文设计了一种用于正交频分复用(OFDM)系统的新型保护间隔信号-导频后缀(Pilot Postfix, PP),并构建了采用比特交织编码调制-迭代解码(BICM-ID)技术的PP-OFDM系统。PP由OFDM符号中的频域导频符号进行逆傅氏变换(IFFT)生成,在接收端可与OFDM符号中的导频相干合并,从而提高信道估计性能。该文给出了相应的信道估计、均衡和BICM-ID算法,并通过研究信道估值误差带来的接收信号有效信噪比变化,给出了PP幅度优化设计方法。仿真表明:选取适当的PP大小后,PP-OFDM比循环前缀/补零后缀-OFDM(CP/ZP-OFDM)的信道估计性能更好,误包率更低。     

On the use of EMD based adaptive filtering for OFDM channel estimation

Hilbert Huang transform (HHT) based data driven empirical mode decomposition (EMD) in conjunction with adaptive filter (AF) is proposed for estimation of communication channel in OFDM system. EMD can be viewed as alike of wavelet decomposition which decomposes the signal of interest to intrinsic mode functions (IMF), whose basis function is derived from signal itself. In this method, the length of channel impulse response (CIR), is approximated using Akaike information criterion (AIC). Then the estimation of CIR is performed using adaptive filter with EMD decomposed IMF of the received OFDM symbol. Conventional AF uses random initial weight vector. The novelty of the proposed method lies in the fact that it uses decimated version of one of the decomposed IMFs of received OFDM symbol as initial weight vector. The selection of useful IMF component is done based on correlation and kurtosis measures. This makes the proposed EMD based AF method converge to minimum mean square error (MMSE) in less number of iterations resulting in almost 50% saving of computations. Bit error rate (BER), mean square error (MSE) and normalized root mean square error (NRMSE) are computed. The simulation studies established the efficacy of proposed method; and comparative studies under different modulation schemes and fading conditions revealed improved performance. Simulations have shown an average improvement of 3 dB in BER performance for proposed EMD based AF as compared to conventional AF.     

移动水声通信多径传输非一致多普勒估计方法研究

现有水声通信中的多普勒估计方法一般都假定多径信道每条路径的多普勒因子相等,当各路径多普勒因子存在差异时,该类方法往往无法正确估计出每径的多普勒因子,导致补偿后的信号存在较大误差。为此该文在分析水声信道稀疏特性的基础上,提出一种基于稀疏表示理论的非一致多普勒估计方法。该方法结合水声多径信道与非一致多普勒稀疏特性生成包含信道信息的超完备字典,将每径的非一致多普勒因子估计转化为基于超完备字典的稀疏重构求解,实现非一致多普勒因子的准确估计。仿真结果表明,所提方法不仅能估计出差异较大的非一致多普勒因子,而且对于大多普勒频偏的估计也相当有效,特别适合于高速移动水声通信中的多普勒估计。     

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.     

Estimation of time-varying channels for pilot-assisted OFDM systems

Orthogonal frequency division multiplexing (OFDM) systems encounter performance degradations because of the time-varying (TV) channels common in wireless environments. The channel variations within one OFDM symbol introduce intercarrier interference. In this case, the frequency domain channel matrix is no longer diagonal, hence the corresponding channel estimation is challenging. In this article, two novel TV channel estimation approaches are proposed for the pilot-assisted OFDM systems, where the channel is approximated by the high-order linear model or the piece-wise linear model in time domain. The least square estimation is derived for the two kinds of channel approximations. The simulation is performed based on realistic TV channels with a fairly high Doppler spread. The results show the significant decreasing of the estimation mean square error using the proposed approaches.     

Joint carrier frequency synchronization and channel estimation for OFDM systems via the EM algorithm

A joint carrier frequency synchronization and channel estimation scheme is proposed for orthogonal frequency-division multiplexing (OFDM) system. In the proposed scheme, carrier frequency synchronization and channel estimation are performed iteratively via the expectation-maximization (EM) algorithm using an OFDM preamble symbol. Moreover, we analytically investigate the effect of frequency offset error on the mean square error (MSE) performance of channel estimator. Simulation results present that the proposed scheme achieves almost ideal performance for both channel and frequency offset estimation.     

Iterative decision‐directed estimation and compensation of nonlinear distortion effects for OFDM systems

Orthogonal frequency division multiplexing (OFDM) has been adopted for several wireless network standards due to its robustness against multipath fading. Main drawback of OFDM is its high peak‐to‐average power ratio (PAPR) that causes a signal degradation in a peak‐limiting (e.g., clipping) channel leading to a higher bit error rate (BER). At the receiver end, the effect of peak limitation can be removed to some extent to improve the system performance. In this paper, a joint iterative channel estimation/equalization and clipping noise reduction technique based on minimum mean square error (MMSE) criterion is presented. The equalization weight that minimizes the mean square error (MSE) between the signal after channel equalization and feedback signal after clipping noise reduction is derived assuming imperfect channel state information (CSI). The MSE performance of the proposed technique is theoretically evaluated. It is shown that the BER performance of OFDM with proposed technique can be significantly improved in a peak‐limited and doubly‐selective (i.e., time‐ and frequency‐selective) fading channel. Copyright © 2011 John Wiley & Sons, Ltd.     

Time-domain channel estimator based on cyclic correlation for OFDM systems with guard interval

Channel impulse response （CIR） can be estimated on the basis of cyclic correlation in time-domain for orthogonal frequency division multiplexing （OFDM） systems, This article proposes a generalized channel estimation method to reduce the estimation error by taking the average of different CIRs. Channel impulse responses are derived according to the different starting points of cyclic correlation. In addition, an effective CIR length estimation algorithm is also presented. The whole proposed methods are more effective to OFDM systems, especialiy to those with longer cyclic prefix. The analysis and the simulation results verify that the mean square error performance is 4-5 dB better than the conventional schemes under the same conditions.     

Subspace Projection-based OFDM Channel Estimation

In this paper, we investigate the benefits of pre-processing received data by projection on the performance of channel estimation for orthogonal frequency division multiplexing (OFDM) systems. Projecting data onto its signal subspace will reduce the additive noise energy in the data. Least square (LS) estimation is a low-complex algorithm for training-based OFDM systems and the lower bound on the mean-square error of it is proportional to the noise variance. So, after the received data is pre-processed (projected onto its signal subspace), LS channel estimation on the pre-processed data will increase the performance of channel estimation. This method can also work in multiple-input and multiple-output (MIMO) case. Performance analysis and simulation results show that the proposed algorithm has a considerably smaller complexity than the linear minimum mean square error estimation while having almost the same performance.     

Practical robust uniform channel decomposition scheme for CSI mismatch in limited feedback MIMO systems

Uniform channel decomposition (UCD) has been proven to be optimal in bit error rate (BER) performance and strictly capacity lossless when perfect channel state information (CSI) is assumed to be available at both the transmitter and receiver side. In practice, CSI can be obtained by channel estimation at receiver and conveyed to transmitter via a limited-rate feedback channel. In such case, the implementation of traditional UCD by treating the imperfect CSI as perfect CSI cause significant performance degradation due to inevitable channel estimation error and vector quantization error. To overcome this problem, a practical robust UCD scheme was proposed in this paper, which includes two steps, firstly, a matching architecture was proposed to eliminate the mismatch between CSI at receiver (CSIR) and CSI at transmitter (CSIT), secondly, an MMSE based robust UCD scheme considering channel estimation error and vector quantization error as an integral part of the design was derived. Simulation results show that the proposed practical robust UCD scheme is capable of improving the BER performance greatly in the context of channel estimation error and vector quantization error compared with the traditional UCD scheme.     

Robust and Improved Channel Estimation Algorithm for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.