使用混沌扩频序列增强DS/SS系统性能

基于Logistic映射,利用交织器设计扩频序列发生器,其产生的混沌序列具有良好的相关特性和旁瓣特性,并且是不必寻优而自身平衡的。将这种序列作为扩频序列应用于直接序列扩频系统中,能够有效地减少多址干扰,提高系统的容量,增强系统性能,信息也能够被加密。将这种序列和传统的扩频序列以及普通的混沌序列应用于扩频系统,仿真结果表明,设计的混沌序列性能优于其他的扩频序列。     

Performance evaluation of cyclic prefix CDMA systems with frequency domain interference cancellation

Direct-sequence code division multiple access (DS/CDMA) systems transmitting over multipath channels suffer from intersymbol interference (ISI) and multiple access interference (MAI). Recently, DS/CDMA with frequency domain equalization (FDE) has attracted much attention for its ability to obtain an excellent performance even in strong frequency selective fading channels. However, the presence of residual interference after the FDE degrades the orthogonality among the spreading codes and hence the BER performance deteriorates. Parallel interference cancellation (PIC) is an effective method to suppress the MAI and improve the CDMA system capacity. In this paper, we propose three interference cancellation architectures for downlink cyclic prefix CDMA systems. The common thread between these three architectures is their implementation in frequency domain. A comparison between such architectures is presented. Simulation results show that the combination of PIC and FDE provides an efficient solution to suppress the MAI in downlink CDMA systems over frequency selective fading channels.     

DS-CDMA downlink systems with fading channel employing the generalized receiver

In this paper, we investigate a generalized receiver (GR) constructed on the basis of the generalized approach to signal processing (GASP) in noise employing by direct-sequence code-division multiple access (DS-CDMA) downlink wireless communication system with multipath fading. Transmitted signaling technique is based on using the orthogonal unified complex Hadamard transform spreading sequences. The use of GR allows us to maintain the orthogonality between users and reduce the multipath fading effect and interference from other users. A general multipath-fading model is assumed. Bit-error rate (BER) performance of system is evaluated by means of the signal-to-interference-plus-noise ratio (SINR) at the output of GR employed by DS-CDMA downlink wireless communication system. Using the orthogonal unified complex Hadamard transform spreading sequences as the transmitted signaling technique, we obtain that SINR at the GR output is independent of the phase offsets between different paths. If the Walsh–Hadamard (WH) spreading sequences are used as the transmitted signaling technique, the SINR at the output of GR employed by the same system is a function of squared cosine of path phase offsets. As a result, the BER performance of the last DS-CDMA downlink wireless communication system is worse in comparison with that of the first system. Comparative analysis between the BER performance of DS-CDMA downlink wireless communication systems employing both the GR and the Rake receiver, which consists of a bank of correlation receivers, with each individual receiver correlating with a different arriving multipath component, shows us a superiority of the first system over the second one both at high and low SINRs.     

基于正交混沌多用户混沌通信及其误码率

为了解决多用户混沌通信系统中由于通信用户数目的增多以及混沌序列间的准正交性所引起的信道干扰问题,对不同混沌信号采用施密特(Schmidt)正交化方法产生其对应的正交混沌序列作为扩频码在加性高斯白噪声(AWGN)和瑞利(Rayleigh)衰落信道下研究多用户混沌通信系统中的误码率(BER)。首先将其统计自相关和互相关特性作为刻画正交混沌扩频码序列性能的重要指标,测试并分析各正交混沌序列的统计相关特性,同时也对其互相关特性曲线的均值和方差进行了测试与分析;然后通过两种信道仿真实验获取各正交混沌扩频码的BER,并将其与对应统计相关特性作对比揭示其内在关联性;最后比较分析两种不同信道下多用户混沌通信系统的BER,并揭示信道对其的影响。仿真实验表明,两种信道下相空间混沌信号中的空时正交混沌序列都能获得较低BER,尤其是在Rayleigh衰落信道下的空时正交混沌序列能够获得更低的BER,说明所提方法能更有效地降低多用户通信中信道间的干扰,更有利于多用户通信需要。     

MC-CDMA系统中基于QR分解的多址干扰消除算法

多址干扰是导致MC-CDMA系统误码性能下降的重要因素。为了消除多址干扰,提出基于接收信号功率排序和QR分解的多址干扰消除算法（Power-based MMSE Sorted QR Decomposition,P-based MMSE-SQRD）对MC-CDMA系统的上行链路进行检测。仿真结果显示,与传统的串行干扰消除算法相比,P-based MMSE-SQRD的误码性能有明显的提高,而且其复杂度也相对较低。     

Bursty traffic over CDMA: predictive MAI temporal structure, rate control and admission control

We study data communications for the downlink in code-division-multiple-access (CDMA) networks. The focus of this paper is to exploit the predictive temporal structure of the multi-access interference (MAI) for adaptive resource allocation, particularly for rate control and admission control. We also investigate the impact of fading and traffic burstiness on the system performance. We first present our result that when the input data traffic corresponds to multiple ON–OFF heavy tailed sources, the MAI process is asymptotically self-similar (with Hurst parameter 1/2<H<1). Thus the MAI has a non-trivial predictive temporal structure that enables accurate interference prediction. We exploit the predictive MAI structure to construct a multiple time-scale interference predictor. Rate adaptation is carried out based on the predicted interference level. Our numerical results show that this rate control scheme achieves significantly better performance than that using the packet-level MAI prediction only. We also devise a joint rate control and admission control scheme. To this end, we propose a sliding observation window scheme that has a two-tier flavor: Each observation window is divided into many time slots, rate control based on the interference prediction is conducted in each slot, and the corresponding throughput in the observation window is used for admission control accordingly.     

基于空间自适应哈希算法的并行双音频指纹技术

针对非法音频拷贝的检索跟踪性能问题进行研究,提出了一种基于新哈希的并行双音频指纹方法。为了提高检测片段的完整性,应用了并行的特性,通过沃尔什—哈达玛转换生成两组实时并行的指纹;通过新哈希方法对两组指纹进行相似性计算;最后检索时让并行的两组指纹进行匹配,合并得到最终结果。实验结果表明,该方法不仅对采用不同方法处理的音频具有良好的鲁棒性,能稳定地表征音频整体特性,与所考虑的其他方法相比,所提出的方法在匹配段完整性方面有所提高。     

地空信道下基于OFDM/OQAM系统的时频同步算法

针对正交频分复用/交错正交幅度调制（OFDM/OQAM）系统无循环前缀而对时偏误差敏感,以及在具有大多普勒频移的快时变地空信道下对频偏估计要求较高的问题,提出了一种适用于地空信道OFDM/OQAM系统的自相关估计（ACE）时频同步算法。该算法中符号定时采用较少的辅助序列实现快速捕获和定时,频偏估计通过优选同步自相关序列进行两次自相关运算,将两次运算估计的频偏值进行加权平均,获得最终频偏估计值。在计算机上进行仿真,其中与改进最小二乘（MLS）算法和训练序列（TR2）算法相比,ACE算法符号定时相关峰值对比度提高至原来的3倍;在飞行状态下系统误码率（BER）为10^-2时有10dB信噪比增益,在地空信道到达状态下BER为10^-3时有3dB信噪比增益。仿真结果表明,ACE算法进一步提升了时频同步精度和误码性能。     

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.     

基于PWHT的删除卷积码识别方法

介绍了删除卷积码的定义,根据删除卷积码与源卷积码之间的关系,构建了删除卷积码识别的数学模型,针对Walsh-Hadamard变换在删除卷积码校验矩阵识别中存在运算量和数据量过大的问题,对校验矩阵方程组进行了变形,提出部分Walsh-Hadamard变换（PWHT）,有效地识别出校验矩阵,并在此基础上识别源码的生成矩阵和删除模式,进行仿真实验。结果表明在误码率为0.03的情况下,识别概率达到99.8%以上。     

优化混沌扩频序列的抗干扰性能分析

为了提高基于混沌序列的直序码分多址系统(DS/CDMA)抗干扰性能,提出一种优化混沌序列性能的优选算法,将得到的优化序列应用于DS/CDMA系统中,研究分别在加入单频干扰、部分频段干扰、脉冲干扰情况下的抗干扰性能。结果表明优化后的改进型Logistic映射混沌序列可利用的码数目众多,抗干扰能力强,且系统误码率较低,与Gold序列相比,在相同误码率情况(10^(-1))下,信噪比至少可改善2dB,更适合用于DS/CDMA系统和通信抗干扰技术中。     

自适应滤波器在自编码扩频系统中的应用

为满足自编码扩频系统中信源序列随机化的要求,对信源随机化方法进行了研究,使用了一种自适应滤波器,利用其前向预测功能从信源序列中提取自编码扩频序列.该滤波器是在线性自适应滤波器中引入非线性神经元网络层构成,采用了一种新的变步长的更新算法,并简化了滤波器各项参数的更新,实现了一种基于自适应滤波器的信源随机化方法.仿真实验结果表明,使用自适应滤波器提取的自编码扩频序列完全满足自编码扩频通信的要求,系统误码率有所改善.     

Improved gait recognition by gait dynamics normalization

Potential sources for gait biometrics can be seen to derive from two aspects: gait shape and gait dynamics. We show that improved gait recognition can be achieved after normalization of dynamics and focusing on the shape information. We normalize for gait dynamics using a generic walking model, as captured by a population Hidden Markov Model (pHMM) defined for a set of individuals. The states of this pHMM represent gait stances over one gait cycle and the observations are the silhouettes of the corresponding gait stances. For each sequence, we first use Viterbi decoding of the gait dynamics to arrive at one dynamics-normalized, averaged, gait cycle of fixed length. The distance between two sequences is the distance between the two corresponding dynamics-normalized gait cycles, which we quantify by the sum of the distances between the corresponding gait stances. Distances between two silhouettes from the same generic gait stance are computed in the linear discriminant analysis space so as to maximize the discrimination between persons, while minimizing the variations of the same subject under different conditions. The distance computation is constructed so that it is invariant to dilations and erosions of the silhouettes. This helps us handle variations in silhouette shape that can occur with changing imaging conditions. We present results on three different, publicly available, data sets. First, we consider the HumanlD Gait Challenge data set, which is the largest gait benchmarking data set that is available (122 subjects), exercising five different factors, i.e., viewpoint, shoe, surface, carrying condition, and time. We significantly improve the performance across the hard experiments involving surface change and briefcase carrying conditions. Second, we also show improved performance on the UMD gait data set that exercises time variations for 55 subjects. Third, on the CMU Mobo data set, we show results for matching across different walking speeds. It is worth noting that there was no separate training for the UMD and CMU data sets.     

基于卡尔曼滤波的线性共轭半盲多用户检测

考虑实际的多载波CDMA（MC-CDMA）上行链路系统,深入研究了基于卡尔曼滤波的盲自适应多用户检测和线性共轭多用户检测,提出MC-CDMA系统下一种基于自适应卡尔曼滤波的线性共轭半盲多用户检测算法。该算法利用小区内所有用户的扩频码和伪自相关矩阵的信息设计了一种基于平均输出能量（MOE）准则的线性共轭半盲检测器,结合修正的PASTd算法和卡尔曼滤波算法自适应得到MOE权向量。仿真实验验证了所提算法的有效性,与卡尔曼滤波盲自适应算法相比,提出的算法有更好的输出信干比和误码率性能,并保持较低的复杂度。     

一种利用预测运动矢量改进的H.264快速运动估计算法

针对H.264标准推荐使用的快速运动估计算法——非对称十字型多层次六边形格点搜索（Unsymmetrical cross multi-hexagon grid search, UMHexagonS）算法搜索速度慢的问题,提出了一种改进算法。在起始搜索点的预测环节,建立预测矢量集,并根据预测矢量集的长度信息决定后续的搜索策略;在全局搜索环节,利用预测运动矢量之间的相关性适当跳过某些搜索步骤,并更换一些搜索模板;并且,根据整数变换和量化的特性检测全零系数块,提前终止运动估计过程。实验结果表明,在量化步长为28时,本文算法比UMHexagonS算法平均减少了34.80%的运动估计时间,同时编码性能基本不变。该算法在不同量化步长的条件下能够适应不同运动强度的视频序列,是一种适合H.264的速度快且性能好的快速运动估计算法。     

Performance of multi-processing gain QS-CDMA over AWGN and Rayleigh fading channels

In this paper, we analyze the bit error rate performance of multi-processing gain quasi-synchronous (QS) code division multiple access (CDMA). Analysis is carried out for deterministic spreading sequences over additive white Gaussian noise (AWGN) and frequency selective slowly Rayleigh fading channels. We also find the bit error rate performance of multi-processing gain QS-CDMA for random spreading sequences and compare to that of deterministic spreading sequences. Results show that deterministic Gold codes outperform random codes considerably and perform differently for different rates while random codes give almost the same performance for all rates.     

基于LMS的自适应半盲多用户检测

基于MOE准则，充分利用小区内所有用户的扩频码给出一种MOE半盲检测器，结合修正的PASTd算法和LMS算法自适应得到MOE半盲检测器的权向量，提出MC-CDMA系统下一种基于LMS的自适应半盲多用户检测算法。该算法利用已知的信息使系统的输出信干比和误码率优于LMS盲多用户检测，同时避免LMS算法中的特征值分解问题，显著降低计算量。仿真实验验证了该算法的有效性和优越性。     

Performance bottleneck of subsequence matching in time-series databases: Observation, solution, and performance evaluation

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper identifies a performance bottleneck in subsequence matching, and then proposes an effective method that substantially improves the performance of entire subsequence matching by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post-processing steps of subsequence matching through preliminary experiments. Based on these results, we show that the post-processing step is a main performance bottleneck in subsequence matching. Then, we argue that the optimization of the post-processing step is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple yet highly effective method for expediting the post-processing step. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancies of disk accesses and CPU processing that occur in the post-processing step. Our method is fairly efficient, and does not incur any false dismissal. We quantitatively demonstrate the superiority of our method through extensive experimentation. The results show that our method produces a significantly faster post-processing step; When using a data set of real-world stock sequences, our method was 43.36-96.75 times faster than previous methods, and when using data sets of large numbers of synthetic sequences, our method was 12.48-26.95 times faster than previous methods. Also, the results show that our method reduces the weight of the post-processing step over entire subsequence matching from more than 97% to less than 67%. This implies that our method successfully resolves the performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. Compared with previous methods, our method is 16.17-32.64 times faster when using a data set of real-world stock sequences and 8.64-14.29 times faster when using data sets of large numbers of synthetic sequences.     

引入时频聚集交叉项干扰抑制的大数据聚类算法

面向大数据集管理的数据聚类方法研究在模式识别、故障诊断和数据挖掘等领域具有重要的研究意义。传统的大数据聚类算法采用混合差分进化的粒子群算法,因数据信息流分量之间的交叉作用而出现的类间交叉项干扰影响了聚类分量的正确判断,聚类效果不好。提出了一种基于时频聚集交叉项干扰抑制的大数据聚类算法。在面向传播学视域下物联网大数据库中生成大数据聚类的信息特征向量,对任意两个分簇矢量进行近邻样本的隶属度训练,在时间滑动窗口模型中进行信息调度,采用高频分量抑制方法实现对时频聚集交叉项的干扰抑制,通过频域卷积相似度融合处理,采用粒子群优化算法进行聚类适应度计算,以实现数据聚类算法改进。仿真结果表明,采用该算法进行大数据聚类,具有较好的抗干扰性和自适应性,聚类准确度较高。     

Direct synthesis based tuning of the parallel control structure for integrating processes

A controller tuned for servo/regulatory application gives significant performance degradation when used for regulatory/servo purpose. The degradation in the overall performance can be minimised by a two degree-of-freedom control structure. The parallel control structure reported recently decouples set-point tracking from disturbance rejection. In the present work, the two controllers of parallel control structure are designed using direct synthesis approach to achieve robust closed-loop performance for a class of integrating processes. Simulation examples show that improved servo and regulatory performances are achieved by the proposed method as compared to the recently reported strategies when the controllers are tuned to have the same degree of robustness.