基于小波变换/小波包变换的多载波调制技术

小波/小波包在通信系统中的应用是近年来一个新的研究领域,而基于小波/小波包变换的多载波调制技术是其中一大研究热点。由于小波/小波包基函数具有良好的正交性与时频局域性等特点,基于小波/小波包变换的多载波调制技术,能够有效地提高通信系统性能。本文介绍了当前几种主要的基于小波/小波包变换的多载波调制方案,分析了这些方案的性能特点及发展趋势,并与其他方案进行了比较。     

小波包分复用系统子载波的构造及调制实现

小波包分复用(WPDM)系统中作为子载波的小波包基函数必须是连续解析的,但实际中很难得到,通常需要对其进行逼近.通过滤波器系数采用迭代卷积的方法来对小波包基函数进行离散逼近,构造出的子载波满足小波包基函数的正交性.同时用此方法实现了多载波调制,并将该系统与正交频分复用(OFDM)系统在多径时延信道下进行了比较.仿真结果表明,WPDM系统在抑制ISI和ICI方面以及对定时偏差的影响上更具优势.     

基于神经网络均衡器的小波包多载波扩频系统

在多径衰落信道下,本文提出了一种基于神经网络均衡器的小波包多载波扩频系统(Neural Network Equalizers Wavelet Packet Spread Spectrum,NNE-WPSS).本文利朋基于最小均方算法(Least Mean Square algorithm,LMS)的复径向基函数神经网络均衡器(Complex Radial Basis Function Network Equalizers,CRBF)来抑制由多径衰落信道引起的码间干扰(Inter-Symbol Interference,ISI)并且利用最大似然算法对解调后的码元进行检测.在多径衰落信道和白高斯噪声情况下,本文分析了基于神经网络均衡器的新型小波包多载波扩频系统的传输性能.仿真结果表明,本文所提出的基于神经网络均衡器的新型小波包多载波扩频系统的性能要优于传统的基于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)多载波扩频系统;本文提出的复径向基函数神经网络均衡器(CRBF)的性能也优于迫零均衡器(Zero-Forcing Equalizer,ZFE).     

APSK信号解调算法研究

针对APSK数字调制信号的解调测试需求,设计适用于信号分析仪的APSK数字调制信号解调方法。本文采用前馈解调方案,首先经过载波粗同步去除较大载波频偏,其次通过定时同步恢复出符号周期的最佳采样时刻,最后经过载波细同步流程去除剩余频偏,完成信号解调。经过采集数据验证,证明了本文所提算法可实现APSK信号的大频偏、高精度解调,满足解调测试需求。     

基于小波包变换的多址通信

新一代无线通信系统要求大容量、高速率、综合业务、适用于各种环境。为满足上述要求,宜采用ＣＤＭＡ／ＴＤＭＡ／ＦＤＭＡ混合多址方式,其中多载波ＣＤＭＡ已成为目前研究热点。本文提出一种基于小波包变换的多载波ＣＤＭＡ或正交小波包分解复用（ＯＷＰＤＭ）－ＣＤＭＡ通信方式,介绍了其基本结构和主要优点。这是一种很有发展前景的多址通信技术。     

一种模数混合的PGC解调方案

分析了相位载波(PGC)技术的模拟数字混合解调方案,提出了一种改进的模拟数字混合系统。此系统可降低采样频率,消除寄生调幅的影响,同时克服了因载波漂移带来的解调困难。采用多量子阱激光器作为光源,使载波信号工作在较高的频率范围(0~20 MHz),从而提高了系统带宽和动态范围。试验表明,通过该方案建立的系统满足解调要求。由于较低的采样频率,该方案适合时分复用的光纤传感器阵列。     

电力线低速信息传输的实时控制：逆维弗法单边带解调算法与自适应误差解调？

本文对基信号单国带调制解调方法和ＦＳＫ信号的调制解调方法进行了研究，提出了一种新单边带信号解调法－逆维弗法，以及一种新的自适应误差解调方法，逆维弗法无需从接收信号中恢复出相干载波，而其解计性能近相干解调的性能，而ＡＥＤＥＭ法与传统的自适应算法相比具有跟踪小频差速度快，误码度低失优点，以上两种算法均适用数字信号处理技术实现。     

一种能有效抑制窄带干扰的小波包多载波扩频系统

本文提出一种能有效抑制窄带干扰的基于小波包的多载波扩频接收系统.该系统通过小波包分析来自适应调整优化参数并进行抗干扰处理,使系统性能在高功率窄带干扰下得到改善.处理过程可与传统的基于小波包的多载波扩频系统解调解扩方式很好的相匹配,系统复杂度很低.研究与仿真结果表明,这种方案简单实用,具有良好的性能.在相同的处理条件下,性能要大大优于基于离散傅立叶变换(DFT)的多载波扩频系统.     

移动无线多媒体通信中的多载波调制技术

无线通信的发展方向是提供灵活的、无缝的、高质量的多媒体业务。为适应这种业务发展,无线通信系统需要满足多媒体业务对宽带高速率的更高要求。多载波调制技术能有效地提高频谱利用率,对于宽带高速无线传输系统性能的改善具有重要的意义。OFDM技术是高频谱利用率的多载波调制技术,在多径衰落信道中传输宽带高速数据时其性能有很强的鲁棒性。小波包调制则是一种采用了新的正交变换方法的多载波调制技术。通过对基于DFT的OFDM技术和小波包调制进行比较,小波包的优越性能有益于多载波调制性能的改进。     

一种偏移载波调幅信号的频域优选新方法

为了解决民航地空通信中机载电台接收到的多个偏移载波调幅信号互相干扰的问题,提出了一种在频域进行最佳载波搜索的优选方法。该方法采用能量重心法对接收信号的频谱幅度和频率进行校正,通过搜索频谱幅度的最大值,优选出一路载噪比最高的调幅信号进行解调,同时对其他调幅信号进行抑制。仿真实验和电台通信实验均表明该方法可以正确地实现多个偏移载波调幅信号的优选和解调,明显降低干扰,解调后话音的平均意见分提高了3分,具有实际工程应用价值。     

On the Dual-Tree Complex Wavelet Packet and $M$-Band Transforms

The two-band discrete wavelet transform (DWT) provides an octave-band analysis in the frequency domain, but this might not be ldquooptimalrdquo for a given signal. The discrete wavelet packet transform (DWPT) provides a dictionary of bases over which one can search for an optimal representation (without constraining the analysis to an octave-band one) for the signal at hand. However, it is well known that both the DWT and the DWPT are shift-varying. Also, when these transforms are extended to 2-D and higher dimensions using tensor products, they do not provide a geometrically oriented analysis. The dual-tree complex wavelet transform , introduced by Kingsbury, is approximately shift-invariant and provides directional analysis in 2-D and higher dimensions. In this paper, we propose a method to implement a dual-tree complex wavelet packet transform , extending the as the DWPT extends the DWT. To find the best complex wavelet packet frame for a given signal, we adapt the basis selection algorithm by Coifman and Wickerhauser, providing a solution to the basis selection problem for the . Lastly, we show how to extend the two-band to an -band (provided that ) using the same method.     

Compression of biomedical signals with mother wavelet optimization and best-basis wavelet packet selection

We propose a novel scheme for signal compression based on the discrete wavelet packet transform (DWPT) decompositon. The mother wavelet and the basis of wavelet packets were optimized and the wavelet coefficients were encoded with a modified version of the embedded zerotree algorithm. This signal dependant compression scheme was designed by a two-step process. The first (internal optimization) was the best basis selection that was performed for a given mother wavelet. For this purpose, three additive cost functions were applied and compared. The second (external optimization) was the selection of the mother wavelet based on the minimal distortion of the decoded signal given a fixed compression ratio. The mother wavelet was parameterized in the multiresolution analysis framework by the scaling filter, which is sufficient to define the entire decomposition in the orthogonal case. The method was tested on two sets of ten electromyographic (EMG) and ten electrocardiographic (ECG) signals that were compressed with compression ratios in the range of 50%-90%. For 90% compression ratio of EMG (ECG) signals, the percent residual difference after compression decreased from (mean +/- SD) 48.6 +/- 9.9% (21.5 +/- 8.4%) with discrete wavelet transform (DWT) using the wavelet leading to poorest performance to 28.4 +/- 3.0% (6.7 +/- 1.9%) with DWPT, with optimal basis selection and wavelet optimization. In conclusion, best basis selection and optimization of the mother wavelet through parameterization led to substantial improvement of performance in signal compression with respect to DWT and randon selection of the mother wavelet. The method provides an adaptive approach for optimal signal representation for compression and can thus be applied to any type of biomedical signal.     

Receiver design for wavelet-based multicarrier CDMA communications

Wavelet packets have good properties such as orthogonality and multirate flexibility, and have resulted in a number of works for its applications to code-division multiple-access (CDMA) communications. In this paper we investigate the use of a special set of the wavelet packets, i.e., the waveforms formed from a full binary wavelet packet tree, in multicarrier CDMA systems. In the conventional multicarrier CDMA systems, a simple frequency-domain combining receiver is commonly used to achieve frequency diversity. To combat multipath channel effects, guard intervals are inserted between consecutive symbols. On the other hand, wavelet packets have the property of localization in both time and frequency domains. A novel receiver design utilizing this property to achieve both frequency and time diversity is proposed and evaluated in this paper. This receiver eliminates the need for guard intervals. Simulations are given to support the system and receiver design. This analysis can be extended to the more general wavelet packet basis waveform sets.     

Efficient VLSI Architecture for Lifting-Based Discrete Wavelet Packet Transform

This brief presents a novel very large-scale integration (VLSI) architecture for discrete wavelet packet transform (DWPT). By exploiting the in-place nature of the DWPT algorithm, this architecture has an efficient pipeline structure to implement high-throughput processing without any on-chip memory/first-in first out access. A folded architecture for lifting-based wavelet filters is proposed to compute the wavelet butterflies in different groups simultaneously at each decomposition level. According to the comparison results, the proposed VLSI architecture is more efficient than the previous proposed architectures in terms of memory access, hardware regularity and simplicity, and throughput. The folded architecture not only achieves a significant reduction in hardware cost but also maintains both the hardware utilization and high-throughput processing with comparison to the direct mapped tree-structured architecture     

基于最优小波包基的信号增强算法研究及应用

本文介绍了小波包分析的基本理论以及小波包信号降噪的基本原理,与小波变换相比,小波包变换则是对小波分解中所得到的高频部分再继续细分为一些子频带,具有更精细的信噪分离能力,所以对包含大量中、高频信息的信号能更好地进行时频局部化分析。小波包变换在信号去噪中有着非常重要的应用,因此利用小波包对信号进行消噪也越来越受到科学界的关注。本文的主旨在于研究最优小波包基函数的选取方法,以小波包分析为基础,根据最小代价原理研究信号分解的最佳小波包基,从而在最优小波包基的基础上获得最好的信号增强效果。     

自适应的混合域音频水印新算法

本文结合小波包变换和离散余弦变换，提出了一种基于听觉模型的混合域自适应音频盲水印算法，在不引入听觉失真的前提下，实现了自适应的水印嵌入。算法首先对音频信号进行小波包分解，使得分解后的子带更接近人耳临界频带。其次对每个子带的小波包系数进行离散余弦变换，计算出子带掩蔽阈值。根据子带掩蔽阈值自适应的选取噪声敏感度小的音频段作为水印嵌入段，选取功率值低于掩蔽阈值的频域系数作为水印嵌入位置，同时采用噪声掩蔽比调整水印嵌入强度。二值水印图像通过量化索引调制的方法嵌入到音频信号的中低频系数中，提取水印时不需要原始音频载体。本算法在水印容量、不可感知性和鲁棒性之间达到了很好的平衡，水印容量在576.7bps到689.5bps之间，算法对添加噪声、重新量化、重新采样、低通滤波和MP3压缩均具有很好的鲁棒性。      

A kind of PAPR reduction method based on pruning WPM and PTS technology

Wavelet packet multicarrier system gains widespread concern because of its better resistance performance to Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI), as well as the higher spectrum efficiency. However, multicarrier system has a high Peak to Average Power Ratio (PAPR), which will lead to many problems such as lower system performance. In order to solve the problem, a kind of PAPR reduction method based on pruning Wavelet Packet Modulation (WPM) and Partial Transmit Sequences (PTS) technology is proposed in this paper, through proper pruning of the full-tree structure of wavelet packet modulation in the PTS technology to reduce the number of nodes in the system, and finally improve the reduction effect of PAPR. Simulation results show that when Complementary Cumulative Distribution Function (CCDF) is 10^?3, PTS based on pruning WPM compared with PTS technique and pruning technique has improved about 1 dB and 1.5 dB, which will not affect the system’s Bit Error Rate (BER) performance in the wavelet packet multicarrier system.     

一种实现非等带宽多载波调制的新方法

传统的多载波调制都是采用对传输信道进行等带宽划分的方式。为了更好地适应信道传输特性，一个很有应用前景的发展方向是采用非等带宽划分信道的多载波调制方式。本文提出了一种利用正交小波包变换实现的非等带宽划分信道的多载波调制方法。理论分析和实验结果表明，这种方法对于提高信道的传输性能有很大的潜力。     

一种新的基于小波包分解的EEG特征抽取与识别方法研究

为了提高脑思维任务分类精度,提出一种新的脑电特征抽取与识别方法.首先进行小波包分解,然后结合能反映脑电信号在时域与频域上的能量分布特征的小波包熵概念,从小波包库中选择最优小波包基,对各个最优基所对应的小波系数求取统计特性,然后根据不同脑思维任务下左右半脑各导联间的差异性对各个导联对求取不对称率构成分类特征向量,最后利用SVM分类器对其进行分类.实验结果表明:相对于一般的小波包分解,最优小波包基和自回归特征抽取方法,该方法对5类不同脑思维任务的所有10种不同组合任务对的平均分类预测精度可以达到95.41％～99.65％.