虚拟时间反转镜啁啾率键控的水声多用户通信

针对频率选择性衰落严重的浅海信道多用户通信问题,提出了一种虚拟时间反转镜(VTRM,Virtual Time Reversal Mirror)啁啾率键控(CRK,Chirp-Rate Keying)的水声多用户通信方式。该算法采用啁啾信号作为载波,接收端利用啁啾信号中心频率与分数阶傅里叶变换域的关系还原出原始信息,并使用虚拟时间反转镜技术减少了多径环境对系统的影响,采用啁啾调频率分集作为多址接入方式。在10 kHz的带宽内,可支持4个用户进行可靠通信,每用户通信速率425 bps。水池及海洋实验结果表明:该算法能够有效地传输数据,并且误码率在10-3数量级以下。      

正交频分复用无源时间反转信道均衡方法研究

针对水声信道多途信号引起的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信系统符号间干扰的问题,提出了无源时间反转均衡的方法,将发送的探测信号时间反转与OFDM信号做卷积,利用无源时间反转镜的时间聚焦原理减小信道多途带来的符号间干扰,在OFDM符号中不使用导频的情况下实现信道均衡,简化了均衡步骤并提高了OFDM符号频带利用率。分析比较了无源时反均衡方法与最小平方信道均衡在水声多途信道下的误码性能。仿真研究和湖上实验表明,无源时反信道均衡算法可以有效的减小多途信道对OFDM水声通信系统带来的影响。      

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.     

Analysis and simulation of MDMA—A spectrum efficient non-orthogonal multiple access scheme for 5G communication

In this paper, an analysis and simulation approach is used to verify the performance of a recently proposed non-orthogonal multiple access scheme called multipath division multiple access (MDMA). The spatial multipath channel (SMC), which is the distinct feature for each user, is introduced to model the matrix channel of each user, taking into account the multipath structure and massive antennas. The signal and interference powers are then derived. Thus, the corresponding bit error probability can be approximated in a closed form. Moreover, computer simulation results are shown to be consistent with the analysis results. Most importantly, it is revealed that the MDMA system can achieve the superior cellular spectrum efficiency of 25 bps/Hz/cell which fulfills the 5G cellular system requirement.     

一种裕量最大的高速载波比特功率分配算法

在国家电网公司Q/GDW 1379.4-2013技术规范对智能电能表载波通信单元功率消耗的限定要求下,为保障低压远程电力集抄台区本地通信链路的传输速率稳定可靠,给智能用电实时交互平台提供带宽支持,提出了一种裕量最大的高速载波比特功率分配算法。该算法以兼并窄带载波和宽带载波优势的G3-PLC技术为应用对象,使用约束注水法限定各子载波的传输比特数,根据时变的电力信道增益自适应调整比特功率分配方案,并响应通信服务质量QoS对系统误码率和目标传输速率的要求,结合信噪比门限算法对约束注水法进行界定和优化,得到了功率裕量最大化的表达式。仿真结果表明：提出的算法优于低反馈开销算法,能够适应低压电力线信道。在系统目标传输速率为200kbps时,达到了最大裕量值20,极大程度地降低了通信单元调制解调芯片实际的功率消耗。     

Coherent underwater communication using passive time reversal over multipath channels

Passive time reversal exploits underwater acoustic channels’ spatial and temporal diversity. It can refocus multipath propagated signal at the receiver and can be realized simply by the passive phase conjugation (PPC) method. By the temporal focusing, time delay spread caused by multipath propagation is mitigated for spectral efficient coherent communications. However, the PPC method is unable to eliminate multipath and is limited by channel variations. An adaptive equalizer is therefore needed to compensate residual multipath after refocusing and to track channel temporal variations. Spatial diversity is obtained by using a vertical receiving array. In this paper we used 4-hydrophone array and demonstrated that the adaptive decision feedback equalization in conjunction with PPC significantly decreased the bit error rate.     

Method for efficient representation of the information on the weighting coefficients of a transmitting beamformer in wireless digital communication systems with multielement adaptive antennas

We consider the problem of transmission of channel state information for a transmitting beamformer in digital communication systems with adaptive transmitting and receiving antennas. It is shown that using the unitary property of the weighting matrices of the transmitting beamformer, we can significantly reduce the amount of transmitted information with the help of the well-known Givens decomposition. We propose a method for determining the optimal bit allocation for quantization of the complex weighting coefficients of the transmitting beamformer. Results of mathematical simulation of a wireless digital communication system with multielement adaptive antenna arrays are shown for a multipath Rayleigh channel. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 51, No. 9, pp. 814–823, September 2008.     

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.     

采用去网格相关向量机的水下多径稀疏信道估计（英文）

In the scenario of underwater acoustic sparse channel estimation with training sequences,grid points in the measuring matrix are caused by discretizing procedure.Estimated accuracy might not be guaranteed with the state-of-the-art methods when multipath delays don't exactly locate on the grid points.In this paper,we construct a gridless measuring matrix for sparse channel estimation which contains an off-grid adjusting factor.The Relevance Vector Machine(RVM) algorithm is employed to estimate this factor.The numerical experiments for two different underwater channels are performed to testify the newly proposed method.The results demonstrate that this method outperforms conventional ones in terms of estimating error and bit error rate,especially when the grid gets coarser.     

Reduction of Bit Error Probability during Parallel Transmission of Information in a MIMO System

We consider cellular communication systems with antenna arrays at both link ends, in which the data transmission is performed via parallel eigenchannels under conditions of a scattering medium. To reduce the bit error probability, we propose a method of information transmission based on the use of only part of the eigenchannels with maximum signal-to-noise ratios and ensuring a tradeoff of the data-transmission rate against the bit-error probability. Eigenchannels are separated into energy-strong and energy-weak channels with the help of the threshold technique. Two possible versions of using the proposed method under conditions of a random multipath spatial channel are studied. The results of numerical simulation in the case of Rayleigh fading of signals confirm the high efficiency of the proposed method of information transmission.     

一种水声信道均衡器的混合算法

水声高速相干通信中使用自适应均衡对抗信道在接收信号中产生的码间串扰。目前,1/2分数间隔采样的判决反馈均衡器结构得到了广泛的应用。本文分析了几种自适应算法在此种均衡器结构下的性能,结合浅海水声信道的特点,提出了一种快速卡尔曼滤波和快速自优化最小均方的混合算法,模拟及海试结果表明,该混合算法在计算复杂度、收敛速度以及稳定性方面都有很好的性能,已经应用到了水声实时高速通信系统当中。     

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.     

结合主动时间反转算法的短基线定位研究

短基线声学定位技术是水下运动目标定位的重要研究内容。为了解决定位系统工作于浅水或近岸时多途扩展严重造成的时延估计误差和系统工作不稳定的问题,本文提出一种结合时间反转算法的短基线宽带应答定位技术,该方法利用短基线阵元发射宽带信号,通过应答器接收该信号时间反转处理后再返回给短基线阵元位置,实现信道多途的自适应聚焦,进而提高时延估计精度及信号检测的鲁棒性。仿真研究和湖上试验表明,该方法能够充分利用信道多途信息实现聚焦,减少信道多途对定位信号时延估计的影响,具有较强的抗噪声和多途干扰的能力。相对传统定位方法,该方法可以抑制短基线定位过程中误差及野点的产生,改善了物体定位导航的精度。      

自适应功率分配可见光MIMO信道容量研究

可见光通信（VLC）系统通常采用多阵列光源布局方式来兼顾照明与通信双重功能,因此需要使用多输入多输出（MIMO）技术进行多天线协同传输来实现高速率通信。然而传统MIMO系统中采用平均功率分配来实现空间复用,无法充分体现MIMO多天线协调传输的优势。根据每组收发天线信道状态的差异,设计了一种低计算复杂度的快速迭代注水算法,可实现依据信道特征自适应的分配信息,从而提高系统的信道容量。仿真结果表明:在相同信噪比情况下注水算法自适应功率分配系统比等功率分配系统的信道容量提高了1.25 bit/Hz左右。     

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm is proposed, and a fitness function is provided. Simulations are conducted using the adaptive niche immune genetic algorithm, the simulated annealing algorithm, the quantum genetic algorithm and the simple genetic algorithm, respectively. The results show that the adaptive niche immune genetic algorithm performs better than the other three algorithms in terms of the multi-user cognitive radio network resource allocation, and has quick convergence speed and strong global searching capability, which effectively reduces the system power consumption and bit error rate.     

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.     

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.     

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.     

Channel temporal correlation-based optimization method for imperfect underwater acoustic channel state information

The rapid time variations and large channel estimation errors in underwater acoustic (UWA) channels mean that transmitters for adaptive resource allocation quickly become outdated and provide inaccurate channel state information (CSI). This results in poor resource allocation efficiency. To address this issue, this paper proposes an optimization approach for imperfect CSI based on a Gauss–Markov model and the per-subcarrier channel temporal correlation (PSCTC) factor. The proposed scheme is applicable to downlink UWA orthogonal frequency division multiple access systems. The proposed PSCTC factors are measured, and their long-term stability is verified using data recorded in real-world sea tests. Simulation and experimental results show that the optimized CSI effectively mitigates the effects of the temporal variability of UWA channels. It demonstrates that the resource allocation scheme using optimized CSI achieves a higher effective throughput and a lower bit error rate than both imperfect CSI and the CSI predicted by the recursive least-squares (RLS) algorithm.     

水声通信加权反馈双向Turb均衡器

为了提升自适应双向Turbo均衡器的收敛速度及降低误比特率,提出了采用加权反馈的双向Turbo均衡算法。首先在单个均衡器反馈输入中采用后验均值与先验均值混合的反馈方案,有效提升一轮迭代中均衡器输出的准确性;其次通过后验均值与先验均值的加权合并作为另一均衡器反馈的非因果项输入,在提升反馈输入准确性的同时提升了数据的利用率;最后在权值迭代中采用优化的比例归一化最小均方算法,提升训练阶段均衡器收敛速度。千岛湖试验中,在同样3.75 kbps通信速率的情况下,该方法误比特率仅为传统双向Turbo均衡器的1/3。仿真和试验数据表明,均衡器要达到同样的误比特率,本方法所需迭代轮数更少,在时变信道中系统稳定性更好,误比特率更低,提升了水声通信效率。