基于粒子滤波的Turbo盲均衡

粒子滤波是一种基于贝叶斯估计的算法,在信道盲辨识和盲均衡问题上具有快收敛、抗深衰信道等优势。Turbo盲均衡在低信噪比条件下有较好的误码性能。为了在深衰信道下使通信具有良好的误码性能,对粒子滤波盲均衡算法进行改进,改进算法的重要性采样函数利用了粒子的先验信息,得到一种软输入软输出的粒子滤波盲均衡算法。依据Turbo盲均衡的框架结构实现了一种基于粒子滤波的Turbo盲均衡算法,该算法利用信道编码带来的编码增益,提高了均衡和信道辨识的性能。仿真结果表明相比粒子滤波盲均衡算法本文提出算法的误码率性能提高1dB左右,误帧率性能则提高了3dB以上,经分析可知在信道系数估计较为准确的条件下,系统数据帧几乎没有误码。      

基于隐马尔科夫模型的CPM信号盲Turbo均衡算法

针对高阶连续相位调制信号(CPM)盲均衡中存在的均衡性能较差以及不容易收敛等问题,从隐马尔科夫模型(HMM)的角度出发,建立一种新的EM-SOVA信道盲均衡方法,并结合Turbo均衡思想,提出了一种适用于高阶CPM信号的盲Turbo均衡算法。该算法通过将SOVA内嵌到EM算法的迭代过程中,有效改善了信道均衡效果,同时使用Turbo均衡的软信息迭代处理来进一步提高低信噪比条件下系统性能。理论分析和仿真结果表明,所提算法具有良好的盲均衡性能以及收敛性。     

一种水声通信Turbo均衡中的软迭代信道估计算法

 Turbo均衡技术是水声相干通信克服信道多径、消除码间干扰(ISI)的有效工具。Turbo均衡实际使用时需要对时变、多径信道进行良好的估计。为了提高信道估计的效果,该文基于时变横向滤波和相位旋转信道模型,提出一种水声通信Turbo均衡中的软迭代信道估计算法。该算法采用快速自优化最小均方算法得到各数据符号处的横向滤波器系数矢量并与二阶锁相环联合优化计算。通过仿真比较,该算法明显优于硬迭代信道估计算法,且相位估计性能优于其他文献中的软迭代信道估计算法。在海上试验中,水声通信距离5 km,方向近似垂直,接收阵起伏周期10 s,起伏幅度5 m左右,在此情况下进行数据采集。将该算法用于对海试数据的单通道Turbo均衡处理,实现无误码输出,验证了所提算法在软迭代信道相位估计方面的优势。     

无人飞行器通信中联合信道估计和Turbo均衡

Turbo均衡技术能有效克服信道多径、消除符号间干扰(ISI),从而提高接收机整体性能。针对无人飞行器地空视距链路信道这种快时变多径信道,提出了一种联合信道估计和Turbo均衡的迭代接收算法。该算法采用单载波调制体制,通过信道估计和Turbo均衡之间相互反馈软信息来消除ISI。Matlab仿真结果表明,经过2次以上的迭代后,相比较于传统的单载波频域Turbo均衡算法,新算法的误码率性能得到了显著改善。     

基于FABA-SISO的时变频率选择性衰落信道CPM信号盲均衡

该文针对时变频率选择性衰落信道下高阶连续相位调制(CPM)信号盲均衡中存在的均衡性能较差、复杂度较高以及收敛速度慢等问题,从双向自适应信道均衡的角度出发,将线性调制信号均衡中使用的前后向自适应软输入软输出(FABA-SISO)算法推广,建立一种新的基于FABA-SISO的信道盲均衡方法,并结合逐幸存处理(PSP)思想和Kalman滤波,提出一种适用于高阶CPM信号的自适应盲均衡算法。该算法通过使用FABA-SISO算法,同时利用过去、现在和将来的观察数据进行Kalman滤波信道估计,有效改善了信道估计的精度,同时使用PSP算法来降低系统的复杂度,使得算法具有较好的工程应用性。仿真结果表明所提算法具有良好的盲均衡性能以及收敛性。     

基于Rimoldi分解的连续相位调制信号Turbo频域均衡算法

针对高阶部分响应连续相位调制(CPM)信号均衡中存在的复杂度高和性能较差等问题,该文从Rimoldi分解的角度出发,设计了一种新的适用于倾斜相位CPM信号的发射帧结构,并在此基础上结合单载波频域均衡(FDE)和Turbo均衡的思想,提出了一种适用于高阶CPM信号的Turbo频域均衡算法。该算法通过将信号均衡转化到频域进行处理,避免了时域均衡算法在计算均衡器系数时存在的大矩阵求逆问题,同时使用Turbo均衡的软信息迭代处理来改善系统的性能。理论分析和仿真结果表明,对于四阶部分响应CPM信号,在存在严重符号间干扰的多径衰落信道的条件下,该算法与现有的基于符号的频域均衡算法相比,在保持较低复杂度的同时,具有大约1.5 dB的性能增益。     

DFT-S-OFDM系统中基于DFT的软迭代信道估计

在基于傅里叶变换扩展的正交频分复用（DFT-S-OFDM）系统中,为了消除由多径传播和多普勒效应导致的信道间干扰（ICI）,提出了一种基于离散傅里叶变换（DFT）的软迭代信道估计算法。该算法将传统DFT信道估计技术与Turbo均衡技术相结合,利用Turbo均衡器反馈的软信息来更新初始信道估计响应,进而消除噪声和ICI。Matlab仿真结果表明,在多径信道下,经过2次以上的迭代后,该算法的误码率（BER）性能得到了显著的改善。     

比特谱相关改进循环谱的单通道混合信号参数估计快速算法

为了应对复杂环境下非合作通信、电磁频谱监管等宽带接收中存在的先验信息缺失,针对单通道混合信号的参数盲估计问题,提出了一种基于比特谱相关算法改进循环谱估计的快速算法。针对信号集{BPSK、QPSK、OQPSK、8PSK、8QAM、16QAM、16APSK、32APSK、CPM},系统给出整套参数估计算法流程,通过高阶累积量以及功率中心方法确定信号个数以及载波频率,然后利用改进循环谱提取符号速率谱线,完成单通道混合信号参数估计。论文对改进算法的统计特性进行了理论推导。理论和实验表明:算法不需要同步码等先验信息,适用于高斯噪声信道和多径平坦衰落信道,同时降低了计算复杂度、存储空间、估计方差以及数据量的需求,当混合信号等功率混合时,且信噪比分别为-4 dB和-1 dB时,算法对载波频率和符号速率的估计正确率可以达到90%,验证了算法的有效性和可行性。      

瑞利衰落信道下的Turbo均衡

Turbo均衡是一种将Turbo原理和均衡技术结合起来的技术。他通过反复均衡和信道译码来提高接收机性能。针时瑞利衰落信道，采用基于线性滤波器的软输入／软输出均衡器来消除码间干扰，其系数由最小均方误差准则确定。译码器采用最大后验概率算法时卷积码译码。考虑到瑞利衰落信道为随机信道，用非相干检测时信道进行估计。接收机通过联合均衡和译码以充分利用已经获得的信息，实现信道估计及信道均衡与信道译码的迭代更新。仿真结果表明其性能不仅远远优于非迭代系统．而且在信噪比高于4dB时几乎可以完全消除符号间干扰的影响，与MAPSE相比其复杂度大大降低。     

用于盲接收的turbo均衡与迭代信道估计

Turbo均衡是一种将信道均衡和差错控制译码联合迭代处理的均衡机制,与传统的均衡器相比,能在更低的信噪比条件下克服严重信道失真导致的符号间干扰(ISI)。该文提出一种用于盲接收的turbo均衡和迭代信道估计方案,不依赖于训练序列或发送符号的先验知识,采用初始盲均衡处理来启动迭代信道估计和turbo均衡。在该方案中,初始盲均衡算法的选择是十分关键的,它需要在恶劣的信道条件为后续迭代处理的启动提供足够的先验信息。该文根据turbo均衡的特点,选择了超指数算法作为初始盲均衡。仿真结果表明,该文提出的用于盲接收的turbo均衡方案是有效的。     

Carrier initial phases estimation for single-channel adjacent-frequency mixture of digitally modulated signals

For single-channel mixture of adjacent-frequency digitally modulated signals which have the fixed frame length and sync codes in non-cooperative satellite communications,a carrier initial phases estimation algorithm which can be applied to both low-order and high-order digitally modulated mixtures was provided according to the differences of parameters in the source signals.The sync data eliminated the frequency offset was added in the interval of frame length firstly,then timing synchronization was accomplished for the added result in terms of power maximization rule,thus the initial phases information was derived.Moreover,the modified Cramer-Rao bound (MCRB) of carrier initial phases for single-channel mixture of adjacent-frequency digitally modulated signals was derived for comparison.Simulation results show that,difference between estimation performance of the proposed algorithm and MCRB becomes smaller with the increase in the number of added frames.     

一种改进的最小频移键控调制信号定时同步方法

MSK信号具有良好的频谱效率和功率效率,在通信系统中应用十分广泛。同步作为解调的前提,对MSK信号同步方法的研究十分必要,从而达到解调分析信号的目的。在复杂电磁环境中,信号可能受到噪声和信道衰落等影响,增加了MSK信号的正确盲同步处理难度。因此,提出了一种基于新型非线性变换与前馈结构的MSK信号同步方法,可对信号实现符号定时同步。该方法适用于较低信噪比的情况,算法精度高且计算复杂度较低,还可在缺少先验信息的条件下对MSK信号实现同步,能在一定程度上有效克服信道衰落等因素的影响,获得较好的处理性能。     

Adaptive MAPSD algorithms for symbol and timing recovery of mobileradio TDMA signals

Dual-mode adaptive algorithms with rapid convergence properties are presented for the equalization of frequency selective fading channels and the recovery of time-division multiple access (TDMA) mobile radio signals. The dual-mode structure consists of an auxiliary adaptive filter that estimates the channel during the training cycle. The converged filter weights are used to initialize a parallel bank of filters that are adapted blindly during the data cycle. When the symbol timing is known, this filter bank generates error residuals that are used to perform approximate maximum a posteriori symbol detection (MAPSD) and provide reliable decisions of the transmitted signal. For channels with timing jitter, joint estimation of the channel parameters and the symbol timing using an extended Kalman filter algorithm is proposed. Various methods are described to reduce the computational complexity of the MAP detector, usually at the cost of some performance degradation. Also, a blind MAPSD algorithm for combining signals from spatially diverse receivers is derived. This diversity MAPSD (DMAPSD) algorithm, which can be easily modified for the dual-mode TDMA application, maintains a global set of MAP metrics even while blindly tracking the individual spatial channels using local error estimates. The performance of these single-channel and diversity MAPSD dual-mode algorithms are studied via computer simulations for various channel models, including a mobile radio channel simulator for the IS-54 digital cellular TDMA standard     

Blind equalization algorithm based on complex support vector regression

A new blind equalization algorithm for complex valued signals was proposed based on the framework of complex support vector regression(CSVR).In the proposed algorithm,the error function of multi-modulus algorithm (MMA) was substituted into CSVR to construct the cost function,and the regression relationship was established by widely linear estimation,and the equalizer coefficients were determined by the iterative re-weighted least square (IRWLS) method.Different from spliting the complex valued signals into real valued signals used in support vector regression,the Wirtinger’s calculus was used in complex support vector regression to analyze the complex signals directly in the complex regenerative kernel Hilbert space.Simulation experiments show that for QPSK modulated signals,compared with the blind equalization algorithm based on support vector regression,the equalization performance of the proposed algorithm is significantly improved in linear channel and nonlinear channel by choosing appropriate kernel function and iterative optimization method.     

Blind identification and equalization based on second-orderstatistics: a time domain approach

A new blind channel identification and equalization method is proposed that exploits the cyclostationarity of oversampled communication signals to achieve identification and equalization of possibly nonminimum phase (multipath) channels without using training signals. Unlike most adaptive blind equalization methods for which the convergence properties are often problematic, the channel estimation algorithm proposed here is asymptotically ex-set. Moreover, since it is based on second-order statistics, the new approach may achieve equalization with fewer symbols than most techniques based only on higher-order statistics. Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel     

修正恒模算法分数间隔盲均衡

分数间隔均衡(FSE)能够降低对时间同步误差的敏感性,本文通过修正恒模算法(CMA)的误差函数,提出了一种分数间隔盲均衡修正恒模算法(MCMA).利用通信信号8PSK,对修正恒模算法和传统恒模算法进行了盲均衡性能比较,在噪声环境下的频率选择性信道中,MCMA比CMA具有更强的鲁棒性.模拟结果显示MCMA能够通过提高收敛速率、降低稳态均方误差和符号间干扰(ISI),有效地改进了信道均衡性能.