多输入多输出衰落信道的最小互信息盲均衡

提出了多输入多输出衰落信道的基于广义高斯分布近似的最小互信息盲均衡器.采用输出信号的广义高斯分布近似,基于互信息最小化目标函数自适应调整均衡器的系数.比较了基于广义高斯分布近似和非线性变换的两种最小互信息盲均衡算法.仿真实验表明基于广义高斯分布近似的方法比非线性变换方法有更大的星座图距离,更快的收敛速率和更好的误码性能.     

单通道带通信号的复基带盲解卷积算法

该文提出了一种基于多途信道单通道接收的带通数据(波束或传感器输出)自相关函数的盲解卷积算法。该算法先通过复解调将带通信号频谱搬移到0频率附近,然后进行低通滤波和降采样率,得到其复基带信号。再针对单通道复基带信号,以其自相关函数在零延时之外某区间内的实部平方和最小为准则,推导出复基带多途信号盲解卷积的LMS自适应迭代算法。该方法能够适用于带通高斯信号和非高斯信号,与基于高阶统计量的方法相比,对源信号概率分布具有较宽的适用面,计算机仿真结果验证了该方法的正确性。     

异步CDMA系统中基于预处理递归最小二乘恒模算法的盲自适应接收

该文提出一种基于预处理递归最小二乘恒模算法(PP-RLSCMA)的多径异步CDMA系统盲自适应接收技术。首先对接收信号进行自适应预处理,并分析了预处理器的复杂性和稳定性。预处理的目的是通过对干扰和噪声的部分抑制以提高恒模接收的性能,所提出的预处理方法只与多径信道的最大长度有关。鉴于统计恒模算法收敛速度慢的缺点,提出一种快速递归最小二乘恒模算法的盲自适应接收。仿真表明,该文算法的误码率及收敛性能比LCMMV,LCCMA好。     

基于广义高斯分布模型的小波域自适应盲水印方案

文章提出了一种基于小波系数广义高斯分布模型的自适应盲检测算法.算法通过估计小波各个子带广义高斯分布模型的形状参数,采用局部最优检测器,实现了小波域盲水印的自适应检测.仿真实验结果证明了该方案比符号相关检测器具有更好的鲁棒性.     

对多个斯威林4型目标的检测及估计

首先分析了两个斯威林4型目标情况下单脉冲雷达接收机输出信号近似为高斯分布的条件,得到了与现有文献稍有不同的结论;接着研究了多个目标下输出信号近似为高斯分布的条件;在近似条件下,提出采用最大似然估计加最小描述长度算法对多目标进行检测及分辨.仿真结果证实在得到的近似条件下采用上述检测及估计算法是可行的.     

非线性盲辨识补偿处理的宽带超外差接收机

提出了一种基于非线性盲辨识补偿处理的新型宽带超外差接收机。在时域,分别提取接收前端输出信号的大信号成分（大功率频率分量）和小信号成分（主要包含非线性失真分量）,并以大信号的非线性模型与小信号的残差平方和最小作为其非线性行为模型参数的辨识准则,利用加权迭代改善算法实现模型参数的自适应提取和更新,最后在线实时地对接收机输出信号进行数字域后补偿处理。实测结果表明,在同时多信号接收的情况下,该非线性盲辨识补偿处理可将整机的无杂散失真动态范围(SFDR)提高超过20dB,极大地提高了在强干扰存在时对微弱信号接收与检测的能力。      

基于MIMO系统的MDCMA盲均衡算法

基于对线性多输入多输出(MIMO)系统的自适应盲源分离和盲均衡的研究,为了能够有效恢复输入信号,提出了一种在MIMO系统中引入抖动处理技术的修正抖动符号误差恒模算法.仿真结果表明,该算法可以在仅已知输入信号统计量的情况下跟踪信道变化,并且有效克服多个均衡器的输出可能锁定到相同的源信号问题,抑制ISI和MUI,恢复所有发射天线的发送信息.     

一种基于频移滤波器的混合信号盲恢复算法

针对单天线接收的频谱混叠的混合信号盲恢复问题,在频移滤波器结构上,提出了一种基于相关函数误差准则的自适应频移滤波信号盲恢复算法.该算法利用滤波器输出信号和参考信号以 及混合信号与参考信号之间的相关函数误差来调整自适应滤波器输出权值.分析了该算法的稳态性能.仿真结果表明:在信噪比大于-5 dB的条件下,该算法对混合...     

SIMO信道组合优化递推序列检测算法

传统的盲均衡算法主要基于高阶统计量(HOS)法或信道输出过采样的二阶统计量(SOS)算法，而这些算法不能实际应用于时变环境。与现有的自适应均衡LMS算法、RLS算法不同。提出了一种基于有限字符集信息的组合递推算法，实现单输入多输出(SIMO)信道盲序列检测。仿真表明：该算法具有较快的收敛速度和较低的稳态误码。     

基于WLS-TIR的多目标识别认知雷达波形自适应方法

 针对多个雷达目标的识别问题,研究认知雷达的波形自适应方法,对目标冲激响应线性加权求和获得多个目标的加权表示,基于互信息准则,通过最大化接收到的信号与目标冲激响应线性加权和(WLS-TIR)的互信息获得了针对多目标识别的最优波形,给出了权值的计算方法和多目标识别的自适应机制.仿真实验表明,本文提出的方法相对于传统的线性调频信号(LFM)对多目标的识别性能有明显的提高,并具有较强的实用性和可行性.     

基于二次差频的多频连续波测距方法研究

多频测距解模糊的实现方式通常有两种:二次差频和参差双频.二次差频测距具有原理简单、接收机和发射机设计相对容易等优点.本文对二次差频测距的基本原理进行了详细推导,并对正确解模糊对信噪比的要求给出了理论分析,最后通过仿真实验验证了该方法的有效性,为多频连续波测距雷达的设计提供了一定的理论依据.     

Outage mutual information of space-time MIMO channels

We derive analytical expressions for the probability density function (pdf) of the random mutual information between transmitted and received vector signals of a random space-time independent and identically distributed (i.i.d.) multiple-input multiple-output (MIMO) channel, assuming that the transmitted signals from the multiple antennas are Gaussian i.i.d.. We show that this pdf can be well approximated by a Gaussian distribution, and such a Gaussian approximation is based on expressions for the given pdfs mean and variance that we derive. We prove that at high signal-to-noise ratio (SNR), every factor of 2 increase in SNR leads to an increase in outage rate in the amount of min(M,N) bits, where M and N denote the number of transmit and receive antennas, respectively. A simple expression for the moment generating function (MGF) of the mutual information pdf is also provided, based on which we establish normality of the pdf, when both M and N are large, and the SNR is large.     

Simple Detection Based on Soft‐Limiting for Binary Transmission in a Mixture of Generalized Normal‐Laplace Distributed Noise and Gaussian Noise

In this letter, a simplified suboptimum receiver based on soft‐limiting for the detection of binary antipodal signals in non‐Gaussian noise modeled as a generalized normal‐Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman‐Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL‐plus‐Gaussian distribution.     

On the Outage Capacity of Correlated Multiple-Path MIMO Channels

The use of multiple-antenna arrays can dramatically increase the throughput of wireless communication systems. Thus, it is important to characterize the statistics of the mutual information for realistic correlated channels. Here, a mathematical approach is presented, using the method of replicas, that provides analytic expressions not only for the average, but also for the higher moments of the distribution of the mutual information for the most general zero-mean Gaussian multiple-input multiple-output (MIMO) channels when the channel is known at the receiver. These channels include multitap delay paths, and channels with covariance matrices that cannot be written as a Kronecker product, such as general dual-polarized correlated antenna arrays. This approach is formally valid for large antenna numbers, in which case all cumulant moments of the distribution, other than the first two, scale to zero. In addition, it is shown that the replica-symmetric result is valid if the variance of the mutual information is positive and finite. In this case, it is shown that the distribution of the mutual information tends to a Gaussian, which enables the calculation of the outage capacity. These results are quite accurate even for few antennas, which makes this approach applicable to realistic situations.     

高斯近似法下LDPC码tanh法则优化近似新方法

该文利用高斯近似法,提出一种基于最小均方误差(MMSE)准则的tanh法则优化近似新方法。提出反对称分布与同构广义对称分布新概念,推导出同构广义对称分布条件下若干重要结论,并给出tanh法则最优近似式的计算实现方法。加性高斯白噪声(AWGN)信道下,对一系列(3,6)规则低密度校验(LDPC)码的实验仿真显示,与传统Hagenauer近似法相比,该最优近似方法在不明显增加译码复杂度前提下,对LDPC码译码性能够带来一定改善。     

单脉冲雷达导引头质心干扰检测方法

箔条质心干扰是反舰导弹末制导跟踪阶段面临的主要无源干扰样式,对箔条干扰进行检测可以为抗箔条干扰的策略使用提供时机参考。该文在将舰船目标和箔条干扰分别建模为Swerling IV型和Swerling II型目标的基础上,建立单脉冲雷达导引头接收机回波信号模型,通过理论分析和对比,箔条质心干扰条件下的单脉冲雷达导引头接收机输出信号可以近似为高斯分布,采用广义似然比检验方法实现了波束内不可分辨的箔条干扰检测。综合考虑虚警概率,脉冲积累数、目标到达方向、目标与干扰的功率比等因素进行了仿真实验,结果表明该检测算法是有效的。     

Lattice coding and decoding achieve the optimal diversity-multiplexing tradeoff of MIMO channels

This paper considers communication over coherent multiple-input multiple-output (MIMO) flat-fading channels where the channel is only known at the receiver. For this setting, we introduce the class of LAttice Space-Time (LAST) codes. We show that these codes achieve the optimal diversity-multiplexing tradeoff defined by Zheng and Tse under generalized minimum Euclidean distance lattice decoding. Our scheme is based on a generalization of Erez and Zamir mod-/spl Lambda/ scheme to the MIMO case. In our construction the scalar "scaling" of Erez-Zamir and Costa Gaussian "dirty-paper" schemes is replaced by the minimum mean-square error generalized decision-feedback equalizer (MMSE-GDFE). This result settles the open problem posed by Zheng and Tse on the construction of explicit coding and decoding schemes that achieve the optimal diversity-multiplexing tradeoff. Moreover, our results shed more light on the structure of optimal coding/decoding techniques in delay-limited MIMO channels, and hence, open the door for novel approaches for space-time code constructions. In particular, 1) we show that MMSE-GDFE plays a fundamental role in approaching the limits of delay-limited MIMO channels in the high signal-to-noise ratio (SNR) regime, unlike the additive white Gaussian noise (AWGN) channel case and 2) our random coding arguments represent a major departure from traditional space-time code designs based on the rank and/or mutual information design criteria.     

Gaussian codes and weighted nearest neighbor decoding in fading multiple-antenna channels

We investigate the fading multiple-antenna channel. The decoder is assumed to possess imperfect channel fading information. A modified nearest neighbor decoder with an innovative weighting factor is introduced and an expression for the generalized mutual information (GMI), the achievable rate, is obtained. We show that under certain conditions the achievable rate is equivalent to that of a fading multiple-antenna Gaussian channel where fading is known to the receiver and is equal to the channel estimation, and where noise is due to both the channel noise and the channel estimation error. We show that for our communication scheme, the minimum mean square error (MMSE) channel estimator is optimal in the sense that it achieves the highest value of GMI, and hence the highest communication rate. Additionally, a training based multiple-input multiple-output (MIMO) scheme in a block-fading channel is investigated and it is shown that the number of degrees of freedom depends on the signal-to-noise ratio (SNR).     

Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels

A promising new method from the field of representations of Lie groups is applied to calculate integrals over unitary groups, which are important for multiantenna communications. To demonstrate the power and simplicity of this technique, a number of recent results are rederived, using only a few simple steps. In particular, we derive the joint probability distribution of eigenvalues of the matrix GG^dagger , with G a nonzero mean or a semicorrelated Gaussian random matrix. These joint probability distribution functions can then be used to calculate the moment generating function of the mutual information for Gaussian multiple-input multiple-output (MIMO) channels with these probability distribution of their channel matrices G. We then turn to the previously unsolved problem of calculating the moment generating function of the mutual information of MIMO channels, which are correlated at both the receiver and the transmitter. From this moment generating function we obtain the ergodic average of the mutual information and study the outage probability. These methods can be applied to a number of other problems. As a particular example, we examine unitary encoded space-time transmission of MIMO systems and we derive the received signal distribution when the channel matrix is correlated at the transmitter end