Doubly selective channel estimation and equalization based on ICI/ISI mitigation for OQAM-FBMC systems

Over a doubly selective channel, broadband transmission systems face challenges in channel estimation and equalization. High mobility causes inter-carrier interference (ICI), while multipath transmission induces inter-symbol interference (ISI). In this paper, we present a mitigation method of ICI/ISI for the offset quadrature amplitude-modulated filter bank multi-carrier (OQAM-FBMC) system. It features low inherent imaginary interference (IMI) sensitivity and high efficiency. Specifically, a pilot indices optimization algorithm and a sparse adaptive orthogonal subspace pursuit (SAOSP) algorithm are presented based on the 2-D channel modeling scheme. The guard pilots are first added to mitigate the effect of ICI. Then the index optimization and SAOSP algorithms are applied to achieve a high-accuracy estimation of sparse channel coefficients. In addition, a threshold judgment suboptimal minimum mean square error (MMSE) equalization method is presented based on the variability of the interference power. The method uses normalized interference power thresholds to estimate the ISI dimension and reduce the equalization data, thus mitigating the effect of ISI and achieving efficient equalization. To verify the above methods, single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) models are built. Simulation results indicate a 3-5 dB improvement in channel estimation accuracy. The suboptimal MMSE equalization results are close to the optimal MMSE with about four orders of magnitude reduction in complexity.     

基于LMS/SOLMS算法的时变多径水声信道估计方法

缓变信道下基于LMS算法的信道估计算法具有较好的跟踪性能,但对快变信道,LMS算法跟踪性能下降。SOLMS算法具有比LMS算法更好的跟踪性能,尤其是在快变的信道下。但由于SOLMS算法在收敛阶段的振荡性,这时收敛速度较LMS算法慢。本文提出一种收敛模式下用LMS算法获得信道的参数,收敛后则切换成SOLMS算法跟踪信道的变化的信道估计方法。新方法结合了LMS算法收敛快和SOLMS算法跟踪性能好的优点。对时变多径水声信道估计的计算机仿真实验证明了该方法的有效性。     

水声正交频分复用系统载波偏移与脉冲干扰估计技术

载波频率偏移和脉冲干扰是水声通信系统中常见的干扰形式。为了提高系统的鲁棒性,消除这两种类型干扰的影响,提出利用空载波对载波频率偏移和脉冲干扰进行估计。空载波估计技术采用了分步优化和联合优化估计两种方法。分步优化估计首先利用重采样和空载波进行载波频率偏移估计,补偿后利用空载波对脉冲噪声进行消除。考虑到载波频率偏移和脉冲噪声估计时的相互影响特性,利用二者的联合估计得到优化解。仿真和水池实验结果表明,两种优化算法都取得了良好的效果;同时联合优化估计比分步优化估计得到更大的系统性能增益,在系统误比特率为10-2时,联合优化解得到了3dB左右的系统性能增益。通过对载波频率偏移和脉冲干扰的估计消除,大大提高了水声通信系统的鲁棒性。      

Time reversal acoustic communication receivers: DSP implementation and fast channel estimation

A communication system is implemented on digital signal processors (DSPs) for the underwater acoustic environment. The implemented receiver uses time reversal multi-channel combining followed by a single-channel decision feedback equalizer. Periodic channel estimation is employed to track the channel fluctuations. These techniques are used to mitigate time-varying inter-symbol interference, which is the main challenge in the underwater acoustic channel at operating frequencies greater than 10 kHz. Various optimization tasks are performed to reduce the receiver computational complexity. A fast implementation of the matching pursuit algorithm is tested on the DSP platform. Its performance, in terms of accuracy and run-time, is compared with that of the basic matching pursuit algorithm. Experimental results of the transmission and demodulation of binary phase-shift keying signals at three different symbol rates were obtained in the local Delaware Bay. The low bit error rates demonstrate the effectiveness of our implementation.     

Alternative threshold-based channel estimation and message-passing-based symbol detection in MIMO-OTFS systems using superimposed pilots

In this work, we investigate the challenging problem of channel estimation in high-mobility environments for advanced mobile communication systems (5G and beyond). First, we propose an iterative algorithm for channel estimation and symbol detection in the delay-Doppler domain for multiple-input multiple-output orthogonal time–frequency space (OTFS) system. The proposed algorithm is based on a superimposed pilot pattern to improve the spectral efficiency of the system. It iterates between data-aided channel estimation and message-passing-aided data detection. The channel estimation step is based on a threshold method. This step considers interference-plus-noise caused by the data symbols and the additive noise to adapt the threshold at each iteration. The data detection step is based on an adapted version of the message-passing algorithm proposed in the literature for uncoded OTFS. Then, to improve the channel estimation efficiency, we suggest an interference cancellation scheme executed at each iteration of the proposed algorithm. Finally, we compare the computational complexity and the achieved performance in terms of normalized mean square error of channel estimation, bit error rate, and spectral efficiency against five state-of the-art methods.     

水声通信系统中双向turbo均衡算法

提出了一种水声通信系统中直接自适应双向turbo均衡算法。摒弃了信道估计步骤,采用基于直接自适应的turbo均衡器,并利用内嵌数字锁相环的判决反馈均衡器结构跟踪时变信道,采用最速优化算法自适应调整迭代步长,使得收敛速度和算法性能得到很好折中。此外,利用最小均方误差准则,得到最优权重因子,对正向与反向turbo均衡结果加权求和,消除误差传播效应。仿真和湖上实验验证了方法的正确性,双向均衡的性能优于单向均衡。湖上实验结果表明,基于直接自适应算法相比于基于信道估计的算法,对时变信道不敏感,能获得更低的误比特率。      

水声通信系统中双向turbo均衡算法研究（英文）

A direct-adaptation based bidirectional turbo equalizer for underwater acoustic communications is proposed.Abandoning the channel estimation process,the direct-adaptation based turbo equalizer embedded with digital phase-locked loop is adopted to track time-varying channel.The fast self-optimized algorithm is used to adjust the step size,thus a good tradeoff between the convergence speed and performance has been made.Furthermore,by minimizing the mean squared error,an optimal weighting factor is derived to exploit bidirectional diversity gain.The forward turbo equalizer is combined with the backward turbo equalizer to eliminate error propagation effect.Simulated and experimental results demonstrate that the bidirectional turbo equalizer outperforms the single directional one.It can be seen from the experimental results that,compared with the channel estimation based algorithm,the direct-adaptation based algorithm is less sensitive to the time-varying channel and has a lower bit error rate.     

基于哈达玛积扩展子空间的到达时间和波达方向联合估计

在窄带阵列天线正交频分复用系统的到达时间和波达方向联合估计中, 针对阵元数目较少时波达方向估计精度不高, 特别是多径数目大于阵元数目导致的波达方向无法估计问题, 提出一种基于哈达玛积扩展子空间的到达时间和波达方向联合估计算法. 该算法首先利用各阵元上的频域信道估计构成扩展信道频域响应矢量, 然后计算扩展信道频域响应矢量自相关矩阵, 并进行特征值分解得到哈达玛积扩展噪声子空间, 最后构造伪谱函数并进行二维谱峰搜索, 从而实现到达时间和波达方向的联合估计. 仿真结果表明, 与现有算法相比, 在复杂度没有大幅提高的前提下, 该算法的估计结果均方根误差更加接近克拉美罗界, 且到达时间和波达方向估计能够自动配对, 在多径数目大于阵元数目时依然适用.     

时变信道下的被动时间反转扩频水声通信

本文研究了时变信道条件下采用被动时间反转的直接序列扩频水声通信方案。多通道被动时间反转可通过对信道多径进行时间、空间聚焦实现信道匹配,但低信噪比、时变特性造成的信道特性失配对被动时间反转处理的性能造成严重影响。在垂直阵接收的基础上,本文采用码片级信道估计获取水声信道特性并进行周期性更新,并采用已判决码元产生的扩频码片作为信道估计训练序列,结合应用稀疏信道估计算法抑制零值抽头上的估计噪声,从而可有效改善时变、低信噪比条件下的被动时间反转处理的时、空多径聚焦效果,提高扩频通信性能。通过湖试实验比较了采用稀疏信道估计、传统信道估计算法的时反扩频接收机,以及经典直扩接收机的通信性能,实验结果表明：本文方案可在低信噪比获得较好的性能,并有效抑制时变信道对时反扩频通信性能的影响。     

单载波频域均衡中的水声信道频域响应与噪声估计

本文对单载波频域均衡(SC-FDE)中的信道和噪声估计进行研究,理论分析了形成误码率平台的可能原因,提出了基于Chu序列的联合信道时频域响应和噪声功率估计算法.利用水声信道响应的稀疏特性和门限确定信道能量集中区域,进行信道估计的去噪处理和噪声功率计算.借助于水声射线模型对所提出的算法进行了仿真,分析了噪声估计对SC-FDE性能的重要影响.仿真结果表明,所提出的信道和噪声估计算法可以有效减缓或消除SC-FDE中的误码率平台.     

基于状态估计的混沌直扩信号联合均衡与解调

针对混沌直接序列扩频信号(以下称混沌直扩信号)通过非理想信道,利用信道和混沌直扩信号的状态方程及其均衡和解调的关联性,提出一种基于状态估计的联合均衡与解调算法.算法采用多扩展卡尔曼滤波(extended kalman filter,EKF)结构,一边对信道均衡,一边估计二进制信息码,二者互为因果,同时进行,不仅可以有效克服非理想信道所带来的多径信道畸变、加性噪声等对信号的影响,还可将掩藏在混沌直扩信号中的原始二进制信息码解调出来,比均衡和解调分离的做法更有效地利用信息,有更好的实时性.仿真结果表明,所提出的算法收敛速度快,能在信道特性未知情况下较好地抵御多径效应和噪声影响,实现了混沌直扩信号在非理想信道条件下的有效可靠传输. 关键词： 混沌直扩通信 非理想信道 联合均衡与解调算法 扩展卡尔曼滤波     

Deep-BiGRU based channel estimation scheme for MIMO–FBMC systems

Deep Learning (DL)–based wireless communication systems have the potential to improve the conventional functions and current architecture of communication systems. In this paper, we propose a novel DL-based channel estimation scheme for multiple-input multiple-output filter bank multicarrier with offset quadrature amplitude modulation (MIMO-FBMC/OQAM) systems called deep bidirectional gated-recurrent unit (BiGRU) scheme. This scheme can easily be applied to a single-input single-output (SISO) system. The proposed scheme is divided into two stages: offline and online. The network is first trained in the offline stage. The prediction of channel information and estimation of the channel matrix using the trained network is then performed in the online stage. The simulation results in terms of the normalized mean square error (NMSE) and bit error rate (BER) demonstrate that, under different time-varying channel models, the proposed DL scheme significantly improves the channel estimation performance of FBMC for single and multiple antennas compared to conventional interference approximation method (IAM) channel estimation methods.     

OFDM symbol detection integrated with channel multipath gains estimation for doubly-selective fading channels

Orthogonal Frequency Division Multiplexing (OFDM) is a technique for wideband transmission that is commonly used in modern wireless communication systems because of its good performance over frequency selective channels. However OFDM systems are sensitive to channel time variations resulting in Inter-Carrier Interference (ICI), that without suitable detection methods can degrade performance significantly. Channel State Information (CSI) is essential to various OFDM detection schemes, and its acquisition is a critical factor over time varying channels. This work considers a Kalman filter channel multipath gains estimation technique for time varying environments, integrated with a novel detection scheme for OFDM based on a Sphere Decoding (SD) algorithm derived to exploit the banded structure of the channel matrix. This combined scheme employs decision–feedback from the SD requiring only a low pilot symbol density, and hence improves bandwidth efficiency. Three techniques for integrating the Kalman filter operating in decision–feedback mode, with SD data detection that produces these decisions, are considered in this paper. When compared with other competing schemes, this integrated symbol detection and channel multipath gains estimation approach for OFDM provides performance advantages over time varying channels. Furthermore, it is shown that for moderate Doppler shifts the degradation that carrier phase noise induces in this scheme is small.     

OFDM水声通信CS限幅失真补偿与LS信道估计优化算法*

正交频分复用技术应用于水声通信系统时,会引起较高的峰均比,当采用限幅法对峰均比进行抑制时,会产生非线性失真。另外,系统采用最小二乘法进行信道估计受噪声的影响较大。针对以上问题,提出了一种基于压缩感知技术的补偿限幅非线性失真与最小二乘信道估计相组合的新算法,在接收端利用导频数据采用压缩感知算法对限幅失真进行补偿,同时对最小二乘信道估计进行优化运算,以减小噪声对其影响。理论分析和仿真结果均表明,新算法不但能够有效抑制限幅法造成的系统非线性失真问题,而且能够降低高斯白噪声对于信道估计的影响。     

An embedded pilot power based channel estimation and low-complexity feedback equalization scheme for OTFS system

Orthogonal Time Frequency Space modulation (OTFS) has evolved as an astounding modulation technique for high-speed communication in a doubly dispersive channel. In any wireless communication system, channel estimation and equalization are essential at the receiver to recover the transmitted data. To accomplish this for the emerging OTFS based systems, a modified embedded pilot-based channel estimation technique and low complexity feedback equalization algorithm for integer Doppler shifts in the delay-Doppler domain are proposed in this paper. Our channel estimation scheme exploits embedded-pilot arrangement, and the symbol equalization relies on the Interference calculation and its mitigation iteratively. To achieve this we contemplate a prudent arrangement of symbols in the OTFS frame in such a way that the Guard symbols prevent the interference between data symbols and the pilot symbol at the receiver. Two distinct lumps of received data of the same OTFS frame will be engaged in channel estimation and data detection. An analytical expression of the theoretical Cramer Rao Lower Bound (CRLB) is derived and plotted for the proposed channel estimation scheme. The attained simulation results for Bit-Error-Rate (BER) under the proposed scheme show a significant error rate improvement over the Minimum Mean Squared Error (MMSE) equalization algorithm. Further, a lower computational complexity is also achieved in comparison with modified MMSE detection and MP detection algorithms.     

ECM and SAGE based joint estimation of timing and frequency offset for DMIMO–OFDM system

Distributed multiple-input multiple-output (DMIMO) technology is a key enabler of coverage extension and enhancement of link reliability in wireless networks through distributed spatial diversity. DMIMO employs classic relay channels in between the source and the destination to opportunistically form a virtual antenna array (VAA) for emulating cooperative diversity. Use of multiple antennas at the relays further increases capacity and reliability of the relay–destination channel through multiplexing and diversity of MIMO antennas respectively. In such network, the signal received at the destination is characterized by multiple timing offsets (MTO) due to different propagation delay and multiple carrier frequency offsets (MCFO) due to independent oscillators of the relays. Hence, synchronization becomes a crucial issue in DMIMO in order to realize the distributed coherence. In this paper, we address joint estimation of MCFO and MTO in DMIMO orthogonal frequency division multiplexing (OFDM) with MIMO configuration at the relays for estimate-and-forward (EF) relaying protocol. Two iterative algorithms, based on expectation conditional maximization (ECM) and space alternating generalized expectation–maximization (SAGE) are proposed for joint estimation in presence of inter carrier interference (ICI). The robustness of both the estimators to ICI is evaluated by mathematical analysis and supported by extensive simulations. The performance of the proposed estimators is assessed in terms of mean square error (MSE) and bit error rate (BER). The theoretical Cramer–Rao lower bound (CRLB) of estimator error variance is also derived.     

Exploiting joint sparsity for underwater acoustic MIMO communications

MIMO communication has been recognized as a potential solution for high speed underwater acoustic communication, which unfortunately encounters significant difficulties posed by simultaneous presence of multipath and Co-channel interference (CoI). Sparsity contained in the multipath structure of underwater acoustic channels offers an effective way for improving channel estimation quality and thus enhancing the communication performance in the form of time reversal or channel estimation based equalization. However, for MIMO channels with extensive multipath and CoI, the performance gain achieved by classic sparsity exploitation channel estimation methods such as orthogonal matching pursuit (OMP) is still not enough to yield satisfactory performance. Under quasi-stationary assumption, underwater acoustic channels of adjacent data blocks exhibit correlated multipath structure, namely, multipath arrivals with similar time delay but different magnitude, which has not been exploited. In this paper, a joint sparse recovery approach is proposed to exploit the sparse correlation among adjacent data blocks to improve the performance of channel estimation. Under the framework of distributed compressed sensing (DCS), a joint sparse model which treats the multipath arrivals as sparse solutions with common time support is adopted to derive a joint sparse recovery algorithm for efficient channel estimation, the results of which are used to initialize and periodly update a channel estimation based time reversal receiver. Finally, underwater MIMO communication experimental results obtained in a shallow water channel are provided to demonstrate the effectiveness of the proposed method, compared to the same type of receiver that do not exploit the joint sparse.     

水声正交频分多址上行通信稀疏信道估计与导频优化

针对水声正交频分多址(OFDMA)上行通信中用户导频数量少、分布不均匀, 导致传统内插信道估计方法产生误码平层的问题, 提出一种稀疏信道估计与导频优化方法. 基于压缩感知(CS)理论估计稀疏信道冲激响应, 并依据CS理论中测量矩阵互相关最小化原理, 提出基于随机搜索的导频图案和导频功率联合优化算法. 仿真结果表明, 所提方法在不同多径扩展信道下的性能均优于基于线性内插的最小二乘估计、未经导频优化的CS信道估计以及单纯基于导频图案优化的CS信道估计. 水池实验分别验证了交织式和广义式子载波分配的水声OFDMA上行通信性能, 在接收信噪比高于10 dB时利用所提方法实现了两用户接入的可靠通信.     

矢量泰勒级数特征补偿的说话人识别

将矢量泰勒级数(Vector Taylor Series,VTS)特征补偿算法应用于说话人识别,给出了卷积噪声方差的近似闭式解,构建了联合快速估计卷积噪声和加性噪声均值和方差的框架。该算法可在无需失配环境先验信息的前提下,直接从失配语音中估计出卷积噪声和加性噪声的均值和方差,实现对环境失配的补偿。实验结果表明,在信道变化较大的无线信道下,卷积噪声方差的补偿最高可降低误识率3.24%.提升了系统的识别性能。在存在加性噪声的无线信道下,与基于线性失真模型的特征映射算法和倒谱均值减算法相比,本文算法可分别最大降低49.65%和68.06%的误识率,适合于信道变化较大的失配环境补偿。      

Scattered pilot-based channel estimation with joint noise reduction for PDM-CO-OFDM system

To improve the accuracy of the channel estimation in PDM-CO-OFDM system when LS algorithm is used, a joint denoising method is proposed in this paper. We have theoretically proposed and simulated designed scattered pilot pattern for PDM-CO-OFDM system, then multi-wavelet is used to denoise the LS channel estimation results which have been interpolation in frequency domain, ISFA is further used to denoise signals after interpolation in time domain. Simulation results show that for 4-QAM, 80 GB/s PDM-CO-OFDM system, the proposed joint denoising method has improved 0.96 dB in OSNR sensitivity at the BER of 1e−3 (threshold of FEC) compared to the common LS method and reduced system overhead at the same time.