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.     

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.     

Pilot design and doubly-selective channel estimation for faster-than-Nyquist signaling

Being capable of enhancing the spectral efficiency (SE), faster-than-Nyquist (FTN) signaling is a promising approach for wireless communication systems. This paper investigates the doubly-selective (i.e., time- and frequency-selective) channel estimation and data detection of FTN signaling. We consider the intersymbol interference (ISI) resulting from both the FTN signaling and the frequency-selective channel and adopt an efficient frame structure with reduced overhead. We propose a novel channel estimation technique of FTN signaling based on the least sum of squared errors (LSSE) approach to estimate the complex channel coefficients at the pilot locations within the frame. In particular, we find the optimal pilot sequence that minimizes the mean square error (MSE) of the channel estimation. To address the time-selective nature of the channel, we use a low-complexity linear interpolation to track the complex channel coefficients at the data symbols locations within the frame. To detect the data symbols of FTN signaling, we adopt a turbo equalization technique based on a linear soft-input soft-output (SISO) minimum mean square error (MMSE) equalizer. Simulation results show that the MSE of the proposed FTN signaling channel estimation employing the designed optimal pilot sequence is lower than its counterpart designed for conventional Nyquist transmission. The bit error rate (BER) of the FTN signaling employing the proposed optimal pilot sequence shows improvement compared to the FTN signaling employing the conventional Nyquist pilot sequence. Additionally, for the same SE, the proposed FTN signaling channel estimation employing the designed optimal pilot sequence shows better performance when compared to competing techniques from the literature.     

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.     

Joint fast time-varying channel estimation with noise elimination and ICI cancellation for LTE-V2X systems

Vehicle-to-everything (V2X) communication is essential for intelligent transportation systems (ITS) and critical technology to ensure traffic safety. Aiming at the problems of noise interference, time-varying, and inter-carrier interference (ICI) in the LTE-V2X channel, a joint fast time-varying channel estimation with noise elimination and ICI cancellation is proposed in this paper. Firstly, using the autocorrelation characteristics of the Zadoff Chu (ZC) pilot sequence, a modified discrete Fourier transform (M-DFT) channel estimation algorithm is proposed to eliminate the noise in cyclic prefix (CP). Secondly, a joint iterative direct decision (IDD) and time-varying channel fitting (CF), called IDD-CF channel estimation algorithm, is proposed to track the rapid changes of channels on different symbols and eliminate ICI. The system simulation results show that the proposed joint fast time-varying channel estimation algorithm can effectively eliminate the noise and ICI, improve the performance of channel estimation, and have better robustness under different Doppler frequency shifts than the representative channel estimation algorithm.     

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     

Downlink channel estimation in FDD cell-free massive MIMO

In frequency-division duplexing (FDD) cell-free massive multiple-input multiple-output (MIMO) systems, an excessive channel estimation overhead is a critical issue that limits the system performance. In this paper, by exploiting the sparse channel characteristics of such a cell-free system, we apply compressive sensing to estimate the channel state information and solve the excessive pilot overhead problem. The proposed algorithm estimates several channel coefficients with significant gains in the power domain and ignores the approximately zero coefficients. Compared to minimum mean square error (MMSE) estimation with orthogonal pilots, the proposed method significantly reduces the pilot overhead in an FDD cell-free massive MIMO system. The access points (APs) that contribute low gains feature reduced energy consumption because the power coefficients corresponding to zero gains in the sparse channel are assigned zeros in the power control process. Therefore, to improve the energy efficiency, the ignored channel coefficients reduce the power overhead.     

时间反转滤波器组多载波水声通信方法

针对水声滤波器组多载波(Filter Bank MultiCarrier,FBMC)传统均衡方法效率低、复杂度高等问题,提出了单阵元无源时间反转镜(Passive Time Reversal Mirror,PTRM)和虚拟时间反转镜(Virtual Time Reversal Mirror,VTRM)的均衡算法,该算法利用时间聚焦原理可以降低水声信道带来的符号间干扰(Inter Symbol Interference,ISI),并且不需要在FBMC符号中插入导频,进一步提高了通信速率.通过仿真和外场实验验证了水声FBMC系统采用单阵元PTRM和VTRM的有效性,结果表明,这两种均衡方法能够有效减少ISI,提高系统可靠性能。      

水声通信中基于信道辨识的盲turbo均衡方法

水声信道多途效应明显,造成接收信号存在严重的码间干扰(ISI,Intersymbol interference)。基于最小均方误差(MMSE,Minimum mean square error)准则的turbo均衡器级联了均衡和信道译码,能够有效去除ISI,并获得优良的性能。由于水声信道的时变性,传统MMSE-turbo均衡需要周期性的训练序列,以实现连续可靠的通信。训练序列虽然提高了通信的可靠性,但降低了信息的有效传输速率。因此,为提高通信效率,本文提出了一种盲turbo均衡方法,该方法通过引入新的盲信道辨识器来同时获得信道估计响应和已去除部分ISI的初步均衡输出信号,并为turbo均衡提供初始的响应参数和比特软信息。与水声通信中应用较多的盲判决反馈均衡器(DFE,Decision feedback equalizer)相比,海上实验结果证明本文提出的盲turbo均衡方法抗信道多途衰落的能力较强,并且与传统MMSE-turbo均衡相比无需训练序列,因此提高了信息的有效传输速率。     

Efficient processing of acoustic signals for high-rate information transmission over sparse underwater channels

For underwater acoustic channels where multipath spread is measured in tens of symbol intervals at high transmission rates, multichannel equalization required for bandwidth-efficient communications may become prohibitively complex for real-time implementation. To reduce computational complexity of signal processing and improve performance of data detection, receiver structures that are matched to the physical channel characteristics are investigated. A decision-feedback equalizer is designed which relies on an adaptive channel estimator to compute its parameters. The channel estimate is reduced in size by selecting only the significant components, whose delay span is often much shorter than the multipath spread of the channel. Optimal coefficient selection (sparsing) is performed by truncation in magnitude. This estimate is used to cancel the post-cursor ISI prior to linear equalization. Spatial diversity gain is achieved by a reduced-complexity pre-combining method which eliminates the need for a separate channel estimator/equalizer for each array element. The advantages of this approach are reduction in the number of receiver parameters, optimal implementation of sparse feedback, and efficient parallel implementation of adaptive algorithms for the pre-combiner, the fractionally-spaced channel estimators and the short feedforward equalizer filters. Receiver algorithm is applied to real data transmitted at 10 kbps over 3 km in shallow water, showing excellent results.     

Optimal design of phase function in Generalized DFT

Recently, a theoretical framework for Generalized DFT (GDFT) with nonlinear phase functions exploiting the phase space to design various constant modulus orthogonal transforms was introduced. This paper extends prior work to design longer bases widely used in real world communications systems. GDFT provides flexibilities in phase space yielding performance improvements over other code families including DFT in correlation metrics. GDFT phase functions are optimally designed in order to reduce inter carrier interference (ICI) and inter-symbol interference (ISI) that dictate the performance of a multiuser channel. It is presented in the paper that superior correlation of GDFT over DFT manifests itself in improved BER performance in direct sequence CDMA based multi-user communications systems     

Multi-input multi-output underwater communications over sparse and frequency modulated acoustic channels

This paper addresses multi-input multi-output (MIMO) communications over sparse acoustic channels suffering from frequency modulations. An extension of the recently introduced SLIM algorithm, which stands for sparse learning via iterative minimization, is presented to estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). The sparseness is exploited through a hierarchical Bayesian model, and because GoSLIM is user parameter free, it is easy to use in practical applications. Moreover this paper considers channel equalization and symbol detection for various MIMO transmission schemes, including both space-time block coding and spatial multiplexing, under the challenging channel conditions. The effectiveness of the proposed approaches is demonstrated using in-water experimental measurements recently acquired during WHOI09 and ACOMM10 experiments.     

光纤网络中的云数据并行调度

光纤网络的通信质量受到云数据调度均衡性影响很大,为了改善光纤网络通信质量,提高网络中云数据传输的吞吐量和保真率,通过云数据并行调度,实现云数据传输均衡,提出一种基于自适应判决反馈均衡的光纤网络云数据并行调度模型。构建光纤网络通信的传输信道模型,采用最小均方误差估计方法进行光纤网络的量化融合估计,运用匹配滤波检测器进行云数据中的干扰滤波处理,结合自适应判决反馈均衡方法进行信道均衡,在均衡的信道中对滤波输出的云数据进行并行调度和多线程输出调制。仿真结果表明,采用该方法进行光纤网络中的云数据并行调度的均衡性较好,输出数据的保真率较高,误码率较低,改善了光纤网络的整体性能。     

Delay-Doppler domain decision feedback turbo equalization for OTFS modulation

Emerging evidence indicates that orthogonal time–frequency space (OTFS) modulation is a potential candidate modulation scheme for high mobility wireless communications. However, OTFS may experience significant inter-symbol interference (ISI) and inter-Doppler interference (IDI) in the receiver. In this paper, we propose a soft decision feedback turbo equalization for OTFS transmission over delay-Doppler channels to jointly combat both interferences. A novel block decision feedback equalization (BDFE) algorithm is constructed using the band feature of the channels in the delay-Doppler domain. The feedforward and feedback filters are designed by the delay-time channels coefficients. According to the designed filter, an equivalent system model is employed to allow turbo equalization. The posterior probability is established using the soft prior information and feedback filter, and then fed back to the channel decoder as external information. Both theoretical analysis and simulation results demonstrate the effectiveness of the proposed scheme in improving the bit error rate (BER) performance and combat various interference. Numerical simulations are finally provided to justify the validity of the proposed scheme in improving the bit error rate (BER) performance and combating various interference.     

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.     

A frequency domain multiple-antenna and channel estimation approach for facilitation of UWB technologies coexistence in heterogeneous WPANs

Ultra wideband (UWB) communications is a promising technology which provides high data rates for short-range communications. There are currently two proposals as UWB standards, namely, multiband orthogonal frequency division multiplexing (MB-OFDM) UWB and direct-sequence (DS) UWB. These two standards can cause interference on each other and also to other wireless technologies when they are located in their vicinity. In this paper, we focus on the mutual interference of these two UWB standards. In the first part of the paper, we address the channel estimation issue for DS-UWB receiver, in the presence of multi-user interference (MUI) and MB-OFDM interference within the framework of wireless personal area networks (WPANs). In fact, we use the minimum mean square error estimation (MMSE) to estimate the channel based on a pilot transmission scheme. In the second part, we propose a simple but effective design for the receiver structure of the DS-UWB which utilizes a frequency domain multiple-antenna approach in order to mitigate MUI as well as the MB-OFDM external interference. Channel estimation performed in part one will be used in the detection process in part two. Numerical results are provided to evaluate the effectiveness of the proposed techniques for interference mitigation in DS-UWB.     

点对点移动水声通信技术研究

点对点移动水声通信是实现由活动和静止节点共同构成的水声数据通信网的关键技术之一. 对移动水声通信声信道特性进行了分析,指出不同途径到达的声线对应的多普勒频偏不一致,进一步加大了多途扩展产生的码间干扰的复杂性,不利于水声通信. 提出单阵元被动式相位共轭镜信道均衡技术,可实时自动补偿多普勒频偏,并聚焦多途信号. 将单阵元被动式相位共轭应用于Pattern时延差编码移动水声通信系统,进行了移动水声通信试验,湖试结果验证了其消除码间干扰性能及本文水声通信系统的鲁棒性. 关键词： 移动水声通信 被动式相位共轭镜 时变信道 码间干扰     

The 650-nm variable optical attenuator based on polymer/silica hybrid waveguide

Visible light variable optical attenuators(VOA) are essential devices in the application of channel power regulation and equalization in wavelength-division multiplexing cross-connect nodes in plastic optical fiber(POF) transmission systems.In this paper, a polymer/silica hybrid waveguide thermo–optic attenuator based on multimode interference(MMI) coupler is designed and fabricated to operate at 650 nm. The single-mode transmission condition, MMI coupler, and transition taper dimensions are optimized through the beam propagation method. Thermal analysis based on material properties provides the optimized heater placement angle. The fabricated VOA presents an attenuation of 26.5 dB with a 21-mW electrical input power at 650 nm. The rise time and fall time are 51.99 and 192 μs, respectively. The time–stability measurement results prove its working reliability.     

多波束分集深海远程正交频分复用水声通信

针对深海远程信道传播衰减大、多途扩展严重的问题,提出一种单输入多输出（SIMO）模型下的水声正交频分复用（OFDM）多波束空间分集均衡方法。建立了深海远程信道下SIMO-OFDM接收信号模型,对宽带波束形成处理后的多个到达角度的波束输出进行独立的多普勒补偿和稀疏信道估计,最后基于最大比合并实现多波束均衡。相对于远程通信中常用的单波束处理方法,所提方法可获得额外的不同到达角度的多径分集增益;且基于阵列波束形成处理可明显提升各个波束输出信噪比,避免了单阵元信噪比过低导致的信道估计误差增大的问题。所提方法的计算复杂度大于单波束均衡,但低于多阵元最大比合并均衡。基于BELLHOP的数值仿真和中国南海实验结果表明,所提方法的误码率性能明显优于单波束均衡和最大比合并均衡,且在100 km的距离上实现了通信速率199 bps的无误码通信。      

Spectrum efficient power allocation schemes for OFDM cognitive radio with statistical interference constraints

In this paper, we study the power allocation problem for an orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) system. In a departure from the conventional power allocation schemes available in the literature for OFDM-based CR, we propose power allocation schemes that are augmented with spectral shaping. Active interference cancellation (AIC) is an effective spectral shaping technique for OFDM-based systems. Therefore, in particular, we propose AIC-based optimal and suboptimal power allocation schemes that aim to maximize the downlink transmission capacity of an OFDM-based CR system operating opportunistically within the licensed primary users (PUs) radio spectrum in an overlay approach. Since the CR transmitter may not have the perfect knowledge about the instantaneous channel quality between itself and the active PUs, the interference constraints imposed by each of the PUs are met in a statistical sense. We also study an optimal power allocation scheme that is augmented with raised cosine (RC) windowing-based spectral shaping. For a given power budget at the CR transmitter and the prescribed statistical interference constraints by the PUs, we demonstrate that although the on-the-run computational complexity of the proposed AIC-based optimal power allocation scheme is relatively higher, it may yield better transmission rate for the CR user compared to the RC windowing-based power allocation scheme. Further, the AIC-based suboptimal scheme has the least on-the-run computational complexity, and still may deliver performance that is comparable to that of the RC windowing-based power allocation scheme. The presented simulation results also show that both the AIC-based as well as the RC windowing-based power allocation schemes lead to significantly higher transmission rates for the CR user compared to the conventional (without any spectral shaping) optimal power allocation scheme.