一种新型衰弱信道预测算法

提出了一种基于支持向量机的衰落信道预测算法.在相空间中构建学习样本,然后借助支持向量机的学习与判决能力实施预测.对Jakes衰落信道的预测实验表明,该算法是有效的.同时也表明嵌入维数对预测准确度有着较大影响.     

基于重建相空间的衰落信道非线性预测算法

基于多径快速衰落信道所具有的混沌行为,利用坐标延迟,重建系统的相空间和混沌吸引子,从而获得比标量时间序列更多的系统信息,另外从非线性动力学的角度讨论了快速衰落信道的可预测性,并根据混沌吸引子的稳定性和分形性,提出了非线性快速衰落信道的预测算法,通过引入加权函数,平衡了预测点的邻域对于预测所提供的信息.最后对65.9毫秒的数据进行了预测,仿真结果表明该算法适于进行较大时间范围的预测,预测性能高于无加权预测算法,在信噪比大于15dB时,预测结果可以接受.     

基于支持向量域的快衰落信道混沌预测

以多径无线衰落信道存在奇怪吸引子为前提，从支持向量域SVD出发，研究了无线衰落信道的响应特性。根据相空间延迟重构理论建立了快衰落信道的预测模型，使用训练集合作为支持对象元素，通过机器自学习缩小模型泛化误差上界，采用最小二乘支持向量域，实现了非线性高维相空间映射，预测了衰落信道。实验结果表明：支持向量域含支持向量数少，运算速度快，顽健性强，核函数选择灵活，为自适应实时估计和检测提供了一种方法。该方法在小样本和未知信道概率密度下，信道预测值和真实值取得了一致。     

基于最小二乘支持向量机的Jakes衰落信道预测

将LS-SVM用于Jakes衰落信道预测,进而提出了一种新的衰落信道预测算法.该算法利用衰落信道系数的既有观测值构建学习样本,然后借助LS-SVM的学习与判决能力实施非线性预测.对Jakes衰落信道的预测实验表明,文中预测算法可行且有效.另外,在实验中也讨论了嵌入维参数对预测准确度的影响,并给出最优嵌入维的选取方法.     

基于相空间重构与最小二乘支持向量机的时延预测

针对网络控制系统的时延预测问题,提出一种基于相空间重构与最小二乘支持向量机的时延预测方法.首先利用0-1测试法确定时延序列具有混沌特性,引入相空间重构技术提高预测精度.对实际采集的时延序列进行Hurst指数分析,选择最小二乘支持向量机作为预测模型.然后利用C-C方法确定时延序列相空间重构参数,通过递归图确定时延序列的局部可预测性,利用遗传算法对最小二乘支持向量机的参数进行离线优化.最后通过优化后的最小二乘支持向量机并结合相空间重构对时延序列进行在线预测.与其它预测方法进行了仿真对比,结果表明本文方法具有更高的预测精度与更小的预测误差,同时并未降低预测算法的实时性.     

基于支持向量机的非线性信道盲均衡算法研究

针对非线性信道盲均衡问题,考察了一种基于支持向量机的单输入单输出(SISO)盲均衡算法,该算法利用通信信号的常数模特性,将非线性盲均衡问题转化为非线性支持向量回归问题。在此基础上,本文利用分集技术,将该算法拓展至单输入多输出(SIMO)的情况。对两种算法进行的计算机仿真表明,基于支持向量机的SISO盲均衡算法能够有效地抑制信道中的非线性码间干扰;本文提出新算法由于更好地利用了信道的时空特性,具有剩余平均模误差小的优点。     

粒子群算法优化支持向量机的网络流量混沌预测

针对传统网络流量预测方法存在预测平均绝对误差较大的问题,提出基于粒子群算法优化支持向量机的网络流量混沌预测方法。采用粒子群算法对支持向量机方法进行优化,利用优化后的支持向量机方法对网络流量进行混沌预测,预测结果表明,采用改进预测方法时,其预测的平均绝对误差值相比FCM-LSSVM网络流量预测方法、Morlet-SVR和ARIMA组合预测方法分别降低了65.3%,34.3%,具有一定的优势。     

压缩采样匹配追踪在水声MIMO-OFDM信道估计的应用

针对水声MIMO-OFDM系统,利用水声多径信道冲激响应的稀疏特性,提出一种基于压缩采样匹配追踪 (Compressive Sampling Matching Pursuit, CoSaMP)的信道估计方法。该算法首先利用观测矩阵构建一个向量代替信道,然后采用匹配追踪思想确定这个向量的非零抽头系数位置,最后利用最小二乘法对非零抽头系数进行估计,通过对该向量的估计实现信道响应的估计。与传统最小二乘法（least square, LS）相比,信道估计性能得到很大的提高,与正交匹配追踪（Orthogonal Matching Pursuit,OMP)相比,提高信道估计性能的同时,降低了计算复杂度。通过仿真分析,不但验证了该算法的有效性,还比较了该算法在不同通信系统中的信道估计性能。      

一种无线通信信道的设计与算法仿真

无线信道在实际中难以测试,但信道仿真可以解决这一问题。文中给出了一种灵活且适应性强的无线移动信道模型,并给出了该模型中的衰落信道模型及算法,运用该算法对衰落信道进行仿真,给出衰落信号的仿真结果以及输入信号经衰落信道处理后的结果。     

非理想载波同步下OFDM快衰落信道的稀疏与感知

针对稀疏导频 OFDM 系统,提出非理想载波同步 OFDM 快衰落信道稀疏表示与感知方法。首先提出了一种稀疏化信道核向量的广义信道冲激响应矩阵稀疏化表示方法;推导了稀疏导频快衰落信道估计压缩感知模型;利用OMP算法重构稀疏化信道核向量与广义信道冲激响应矩阵,从而完成非理想载波同步下的 OFDM 快衰落信道估计。仿真结果表明,该算法能有效降低非理想载波同步的稀疏导频 OFDM 系统的误码率。     

Noise reduction for fast fading channel by Recurrent Least Squares Support Vector Machines in embedding phase spaces

A new strategy for noise reduction of fast fading channel is presented. Firstly, more information is acquired utilizing the reconstructed embedding phase space. Then, based on the Recurrent Least Squares Support Vector Machines （RLS-SVM）, noise reduction of the fast fading channel is realized. This filtering technique does not make use of the spectral contents of the signal. Based on the stability and the fractal of the chaotic attractor, the RLS-SVM algorithm is a better candidate for the nonlinear time series noise-reduction. The simulation results shows that better noise-reduction performance is acquired when the signal to noise ratio is 12dB.     

MC-CDMA系统盲空时干扰抑制

该文研究在频率选择性瑞利衰落信道中MC-CDMA系统的盲空时干扰抑制。考虑对应于子载波的衰落系数是信道冲激响应的离散傅里叶变换,通过研究多径信号频域码空间和数据矢量空间,采用噪声子空间技术进行盲信道估计。为了抑制多址干扰(MAI),提出一种基于投影的辅助矢量(PAV)算法,用前一级滤波矢量的输出重构最大比合并(MRC)滤波矢量,将重构滤波矢量投射到由基本滤波矢量和前几级辅助矢量张成子空间上的正交投影作为辅助矢量,将前一级滤波矢量和新产生辅助矢量线性合并得到新的滤波矢量。仿真结果验证了该算法的有效性。     

Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems

Adaptive transmission methods can potentially aid the achievement of high data rates required for mobile radio multimedia services. To realize this potential, the transmitter needs accurate channel state information (CSI) for the upcoming transmission frame. In most mobile radio systems, the CSI is estimated at the receiver and fed back to the transmitter. However, unless the mobile speed is very low, the estimated CSI cannot be used directly to select the parameters of adaptive transmission systems, since it quickly becomes outdated due to the rapid channel variation caused by multipath fading. To enable adaptive transmission for mobile radio systems, prediction of future fading channel samples is required. Several fundamental issues arise in the design and testing of fading prediction algorithms for adaptive transmission systems. These include complexity, robustness, choice of an appropriate channel model for algorithm validation, channel estimation and noise reduction required for reliable prediction, and design and analysis of adaptive transmission methods aided by fading prediction algorithms. We use these criteria in the review of recent advances in the area of fading channel prediction. We also demonstrate that reliable fading prediction makes adaptive transmission feasible in diverse wireless communication systems.     

New Phase Adjustment and Channel Estimation Methods for RF Combining Applicable in Mobile Terminals

Antenna diversity is able toalleviate multipath fading in a wireless communications system.Traditionally, multiple down-conversion chains have to be used inorder to implement antenna receive diversity, making it difficultfor implementation in mobile terminals, where the physical size,power consumption and implementation cost are three major limitingfactors. RF combining, which combines the received signals at RFlevel, is well applicable for mobile terminals as it requires onlyone down-conversion chain. This paper investigates RF combiningtechniques for improving downlink performance by applying atwo-element array at the mobile terminal. A new phase adjustmentalgorithm is suggested in order to combine the RF signals whileminimizing noise effect. Also, a new channel estimation methodbased on the suggested phase adjustment algorithm is proposed, andfurther applied to systems with transmit diversity. Computersimulations have shown that with the new channel estimation methodtogether with the new phase adjustment algorithm, the RF combiningtechniques can improve the BER performance considerably,especially for fast fading environment.     

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。     

一种新的无线通信随机相位线性均方估值方案

本文提出了一种新的无线通信随机相位线性均方估值方案，分析了其性能；针对瑞利度落信道进行了计算机模拟，并将模拟结果与理论值进行了比较。理论分析和模拟结果表明，该方法是一种有效的无线通信随机相位估值方法。     

Breaking Chaotic Direct Sequence Spreading Spectrum Signals Under the Multipath Fading Channel

In order to break chaotic direct sequence spreading spectrum (CD3S) signals under the multipath fading channel, a particle filter based algorithm combining blind channel equalization with chaos fitting is proposed. To implement this algorithm, the intruder substitutes a different chaotic equation into the state-space equations of the channel and the chaos fitting, and then multiple particle filters are used for blind channel equalization and chaos fitting simultaneously by implementing them in reciprocal interaction. As a result, the impact brought about by the multipath fading channel and additive noises can be overcome. Furthermore, the range-differentiating factor is used to make the inevitable chaos fitting error advantageous based on the chaos fitting method. Thus, the CD3S signals can be broken according to the range of the estimated message. Simulations show that the binary message signal can be extracted from the CD3S signals without any knowledge of the chaotic transmitter’s structure, parameters, initial value, or the channel characteristics.     

Prediction/cancellation techniques for fading broadcastingchannels. I. PSK signals

An approach for reducing the effects of multiplicative noise, such as fading, on the performance of mobile broadcasting transmission systems is introduced. The proposed method is based on a noise prediction/cancellation technique and is applied to phase-shift keyed (PSK) signals. By exploiting the statistical characteristics of the multipath fading signal and its strong correlation properties, a novel sequential receiver structure is derived that uses a detection algorithm which identifies the most probable transmitted sequence in the maximum-likelihood detection sense. The algorithm has been obtained for both Rayleigh and Rician fading channels. The proposed detection technique has been evaluated for various QPSK schemes operated in channels corrupted by a combination of additive white Gaussian noise (AWGN) and fading. The computer simulation results obtained show that by using a relatively simple receiver with a prediction algorithm of second order, considerable error floor reductions are achieved by the proposed receivers. As a direct result of these error floor reductions substantial bit error rate (BER) improvements of more than three orders of magnitude over conventionally detected schemes are obtained     

一种基于ML算法及盲信道识别的DWPM系统

该文提出了一种基于ML算法及盲信道估计的离散小波包调制(Discrete Wavelet Packet Modulation,DWPM)系统.本文通过基于导频信号的盲信道识别方法,获得信道的状态信息,并且利用基于ZF(Zero Forcing)算法的H矩阵消除码间干扰,最后,利用ML(Maximum Likelihood)算法检测解调后的码元,并且通过仿真分析了该系统在多径衰落信道下的性能.仿真结果表明,该系统的性能要比传统的OFDM系统的性能好.