基于归一化LMS算法自适应均衡器的Simulink实现

为了克服硬件实现归一化LMS算法自适应均衡器的缺点,构造了数据传输系统中采用归一化LMS算法自适应均衡器的Simulink仿真模型.首先介绍了归一化LMS算法,给出基于归一化LMS算法自适应均衡器的建模过程,最后研究了抽头输入向量相关矩阵的特征值和步长参数对该自适应均衡器性能的影响.仿真结果同时验证了该模型的正确性和Simulink作为仿真工具的有效性.     

自适应均衡器在LVDS总线长距离传输中的应用

自适应均衡器可自动为信号损耗提供补偿,使电缆传来的串行数字信号可以重新恢复其原有强度.利用这一特点,采用高速串行数字接口（SDI）自适应电缆均衡器及电缆驱动器芯片构建系统,可以扩大LVDS技术的数据传送范围,以满足高速率条件下长距离传送的要求.详细介绍自适应电缆均衡器CLC012的结构和工作原理;给出以Belden型同轴电缆和五类未屏蔽双绞线为载体进行实验的结果.     

非线性通信信道的神经FIR自适应幅值Laguerre均衡器

针对数字通信系统中线性和非线性信道干扰问题,在分析神经FIR滤波器、判决反馈结构和Laguerre滤波器的基础上,提出了神经FIR自适应幅值判决反馈均衡器和神经FIR自适应幅值Laguerre均衡器.其中神经FIR自适应幅值Laguerre均衡器结构简单,具有IIR和FIR滤波器特点,能够使用较少的阶数达到较好的均衡效果,且理论分析证明该均衡器是稳定的(0相似文献   

DVB-C接收机中的均衡器设计

提出一种DVB-C基带芯片中自适应均衡器的解决方案,并对其进行了仿真。     

自适应均衡器的FPGA实现

在无线通信系统中,由于多径效应的干扰导致信号在传输过程中不可避免地产生码间干扰,因此必须在接收端增加均衡器,以消除码间干扰,提高传输质量。该自适应均衡器设计以FPGA为设计平台,使用自上而下的模块化的设计方法,利用StratixⅡ系列EP1C20F324C6芯片,采用横向滤波器结构,设计并行结构的8阶复数滤波器。最后在QuartusⅡ中进行仿真与综合,结果显示I、Q两路误差信号趋于零,从而实现自适应均衡,降低误码率。     

一种高速通信中的模拟自适应均衡器设计

由于LVDS传输线在高速数据传输中存在着码间干扰,限制了传输数率和传输距离.因此引入均衡器来补偿数据的高频损耗就变得尤其重要.鉴于模拟自适应均衡器的诸多优点,设计一个基于CMOS工艺的高速模拟自适应均衡器.采用了TSMC 0.25μm CMOS工艺实现,能够很好的均衡传输数率为2Gbps的数据信号.     

一种神经网络判决反馈均衡器

在分析Chebyshev正交多项式神经网络非线性滤波器的基础上,利用判决反馈均衡器的结构特点,提出了一种Chebyshev正交多项式神经网络判决反馈均衡器,给出了对应的自适应NLMS算法.数值仿真结果表明,该均衡器结构能够更有效地消除码间和非线性干扰,降低信号的误码率.     

16QAM解调器的FPGA实现

描述了一个用于微波传输设备的16QAM接收机解调芯片的FPGA实现,芯片集成了定时恢复、载波恢复和自适应盲判决反馈均衡器(DFE),采用恒模算法(CMA)作为均衡算法。芯片支持高达25M波特的符号速率,在一片EP1C12Q240C8(ALTERA)上实现,即将用于量产的微波传输设备中。     

基于判决反馈结构的自适应均衡算法仿真研究

在数字通信中,接收信号通常会受到码间干扰的影响,尤其是在多径衰落无线信道环境中,这种现象更为严重。采用自适应均衡技术可以对信道响应进行补偿。由于在数字通信系统中,信道往往为非最小相位系统,此时线性均衡器性能不佳,因此该文对比研究了非线性结构的自适应波特间隔判决反馈均衡器和自适应分数间隔判决反馈均衡器,并对其性能进行了计算机仿真。仿真结果表明,对于非最小相位信道,自适应分数间隔判决反馈均衡器的性能优于波特间隔判决反馈均衡器。     

自适应变模SCA盲均衡算法

提出一种适用于MQAM数字通信系统的自适应变模方形轮廓线盲均衡算法(AVSCA).该算法在方形轮廓线算法(SCA)基础上,针对MQAM信号的多模特点,用多模零误差曲线替代常模零误差曲线,并通过判决条件对均衡器输出信号进行判?使得均衡器自适应调节其零误差曲线.理论分析和在典型音频带信道上仿真结果表明该算法有效地降低了残留码间干扰和提高了收敛速度,具有很好的均衡性能.     

改进的非线性卫星信道均衡器

针对常用的Volterra结构均衡器运算量大的问题,提出一种改进结构的非线性卫星信道自适应均衡器。通过对截断Volterra级数进行数学分析,得到了具有非线性均衡器和线性均衡器级联形式的新均衡器结构。新结构均衡器将Volterra结构均衡器表达式中的三阶记忆项相乘转变为新模型非线性部分的二阶记忆项相乘,降低了信号通过均衡器所需的复数乘法次数。仿真结果表明,改进结构的非线性卫星信道自适应均衡器运算所需的复数乘法次数在信道记忆很深的情况下约为Volterra结构均衡器的1/9,有利于信号的实时处理。与此同时,经改进均衡器均衡输出的16振幅移相键控调制（16APSK）信号的星座点更为紧凑。     

A negentropy minimization approach to adaptive equalization for digital communication systems

In this paper, we introduce and investigate a new adaptive equalization method based on minimizing approximate negentropy of the estimation error for a finite-length equalizer. We consider an approximate negentropy using nonpolynomial expansions of the estimation error as a new performance criterion to improve performance of a linear equalizer based on minimizing minimum mean squared error (MMSE). Negentropy includes higher order statistical information and its minimization provides improved converge, performance and accuracy compared to traditional methods such as MMSE in terms of bit error rate (BER). The proposed negentropy minimization (NEGMIN) equalizer has two kinds of solutions, the MMSE solution and the other one, depending on the ratio of the normalization parameters. The NEGMIN equalizer has best BER performance when the ratio of the normalization parameters is properly adjusted to maximize the output power(variance) of the NEGMIN equalizer. Simulation experiments show that BER performance of the NEGMIN equalizer with the other solution than the MMSE one has similar characteristics to the adaptive minimum bit error rate (AMBER) equalizer. The main advantage of the proposed equalizer is that it needs significantly fewer training symbols than the AMBER equalizer. Furthermore, the proposed equalizer is more robust to nonlinear distortions than the MMSE equalizer.     

Equalization of nonlinear time-varying channels using type-2 fuzzyadaptive filters

Presents a kind of adaptive filter: type-2 fuzzy adaptive filter (FAF); one that is realized using an unnormalized type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system (FLS). We apply this filter to equalization of a nonlinear time-varying channel and demonstrate that it can implement the Bayesian equalizer for such a channel, has a simple structure, and provides fast inference. A clustering method is used to adaptively design the parameters of the FAF. Two structures are used for the equalizer: transversal equalizer (TE) and decision feedback equalizer (DFE). A decision tree structure is used to implement the decision feedback equalizer, in which each leaf of the tree is a type-2 FAF. This DFE vastly reduces computational complexity as compared to a TE. Simulation results show that equalizers based on type-2 FAFs perform much better than nearest neighbor classifiers (NNC) or equalizers based on type-1 FAFs     

采用LMS算法的频域均衡技术研究

LMS(最小均方)算法是一种经典自适应算法,最初应用于时域均衡.本文采用LMS算法,根据信道的特性来更新频域均衡器的均衡系数,实验结果表明该算法可明显改善频域均衡系统的性能.     

采样延迟对调制自适应均衡性能影响的研究

自适应均衡系统用于各种类型数字通信系统,随时均衡传输信号有畸变的信道.研究一基于LSL(最小平方格型)算法的QPSK(正交相移键控)自适应均衡器,均衡效果良好.然后结合仿真实验分析研究系统采样延迟对调制自适应均衡性能的影响,实验结果表明其影响作用明显,不可忽略.     

Neural FIR adaptive Laguerre equalizer with a gradient adaptive amplitude for nonlinear channel in communication systems

To mitigate the linear and nonlinear distortions in communication systems, two novel nonlinear adaptive equalizers are proposed on the basis of the neural finite impulse response (FIR) filter, decision feedback architecture and the characteristic of the Laguerre filter. They are neural FIR adaptive decision feedback equalizer (SNNDFE) and neural FIR adaptive Laguerre equalizer (LSNN). Of these two equalizers, the latter is simple and with characteristics of both infinite impulse response (IIR) and FIR filte...     

A simple recursive least square algorithm of space–temporal joint equalizer

The environment of the communication system will be more complicated in the future. Therefore, the adaptive array alone cannot cancel all the interferences in future communication system. Many space–temporal joint equalizers (STE) have been proposed to further enhance the capability of canceling the co-channel interferences (CCI) and the multi-path inter-symbol interferences (ISI). The recursive least square (RLS) algorithm of those joint methods will suffer the problems of system structure is complex, the convergent rate of performance is slow or number of calculations is large. In this paper, we propose a simple RLS algorithm (SRLS) of the STE to reduce the computation load, simplify the system structure and improve the system performance. The SRLS algorithm uses the output signal of STE to adjust the weights of adaptive array and equalizer simultaneously without using a transversal filter. Since there is no transversal filter required in the system, the system is simpler in comparison to the conventional STE. Besides, the RLS algorithm of conventional STE adjusts the weights of equalizer after the weights of adaptive array. The convergent rate of weights is slowly in those STE systems. The SRLS algorithm adjusts the weights of adaptive array and equalizer simultaneously. Therefore, the convergent rate of system will improve by the SRLS. Furthermore, the SRLS algorithm is found with input vectors of adaptive array and equalizer separately. Another STE method, which combines the input vectors of adaptive array and equalizer into a large dimension input vector, needs more number of calculations than the SRLS method. Thus, the SRLS of STE can simplify the complexity of system structure, reduce the computation load and improve the convergent performance of system effectively.     

基于免疫算法的RBF网络在信道均衡中的应用

针对严重非线性失真信道,提出了一种基于免疫算法的径向基函数(RBF)网络自适应均衡器.这种均衡器引入了判决反馈均衡器的结构,并采用免疫算法确定RBF网络隐层(非线性层)的结构和参数.免疫 算法具有全局搜索能力,它通过引入多样性保持机制和免疫记忆机制提高了算法的优化效率,并在一定程度上克服了未成熟收敛现象.仿真结果表明,这种基于免疫算法的RBF网络均衡器性能优良,具有很强的抑制非线性失真的能力.􀁱     

一种在多径信道下LDPC码的解码设计

本文首先简单介绍了基带编码调制的LDPC系统与信道模型,接着设计了一种适合应用在多径信道下的自适应均衡器;然后,对LDPC码以及编译码模块进行了构造;最后,本文对所提出的由自适应均衡滤波器和LDPC解码器组成的自适应LDPC译码系统的误比特率（BER）性能进行了仿真,仿真结果表明新的译码系统可以解决在多径信道下BER性能较差的问题。