语音去噪LMS自适应滤波器算法的改进

对LMS自适应算法进行了详细的性能分析与讨论,针对LMS算法运算较复杂、适应性较弱、稳定性差的缺点提出了一种HLMS(混合LMS)算法.建立了自适应噪声抵消系统,利用MATILAB软件对食堂、体育馆两处的录音信号进行计算机语音去噪仿真分析.实验结果表明,两种自适应方法均能有效抑制各种噪声污染,提高语音信噪比为60%～8...     

Generalized Robust Multichannel Frequency‐Domain LMS Algorithms for Blind Channel Identification

Recently, several noise‐robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments.     

基于时变步长最小均方算法的射频干扰对消

针对同时同频全双工系统中射频域干扰对消收敛速度与对消比相互制约的问题,提出基于时变步长最小均方算法的射频自干扰对消方法.该方法在正交两路合成干扰对消方案基础上,利用Logistic函数非线性关系实时改变步长因子,在最小均方准则下实现两路衰减器的快速精确调整,完成自干扰信号的有效对消.最后,理论分析了该对消方法的收敛性和稳态失调误差,给出了收敛状态下能够获得对消比的闭合表达式.理论分析和仿真表明,该方法的收敛时间缩短为已有变步长对消方法的1/4,最终达到的对消比与已有方法相比提高了约5 dB.     

Overlapped universal filtered multicarrier system for uplink wireless communication

Universal filtered multicarrier (UFMC) is a promising new waveform that eliminates cyclic prefix and performs filtering on a chunk of successive subcarriers. Therefore, it is suitable for applications with requirements on high spectral efficiency and low latency. However, the limited bandwidth may be an obstacle for reliable communication in frequency selective channels. This paper proposes a new transmitter structure for uplink wireless communication system based on UFMC waveform. The basic idea is to allow a user to transmit its information on more than one subband simultaneously, increasing its robustness against frequency selectivity. To eliminate the multiuser interference brought by the overlapped transmission strategy, an iterative receiver with parallel interference cancellation is designed. Rate analysis is provided to reveal the rationale of the proposed scheme. Simulations on the symbol error rate performance are conducted to validate the transceiver design. It is found that the proposed scheme outperforms existing UFMC design without sacrificing any other performance metrics with only moderately increased complexity.     

Cross‐level PRC transmitter for TH‐PAM UWB systems

A cross‐level pre‐RAKE combining (PRC) scheme for time hopping pulse amplitude modulation ultra wideband (TH‐PAM UWB) transmitter is studied in this paper. A two‐stage cross‐level PRC (CL‐PRC) scheme is proposed. The conventional PRC schemes suppress all the chip‐wise interference. However, the proposed scheme suppresses only the specific frame‐wise inter‐symbol interference (ISI) by exploiting the characteristic that the information bits are transmitted only at ultra short time slots. This results in a low complexity pre‐equalizer without bit error rate (BER) performance degradation. Furthermore, an order selection rule is presented to achieve the tradeoff between signal‐to‐interference ratio (SIR) and computational complexity. Simulation results illustrate the superior SIR and BER performance of our proposal. Copyright © 2009 John Wiley & Sons, Ltd.     

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.     

Adaptive reference code‐based MAI cancellation for DS‐CDMA

A computationally efficient and practically deployable adaptive reference code‐based multiple access interference (MAI) cancellation scheme, in which the conventional transmitter/receiver architecture is minimally modified only at the receiver (and/or transmitter) end, is proposed for direct sequence code division multiple access (DS‐CDMA) communication. Upon numerical and theoretical analyses, the proposed communications system is seen to always outperform the existing conventional communications system. The theoretical analyses and results as presented are generally useful and applicable to any situation wherein IS95 pseudo noise (PN) codes are employed towards multiple access. Copyright © 2009 John Wiley & Sons, Ltd.     

Performance analysis of multi‐stage interference cancellation for ultra‐wide band multiple‐access communication systems

In this contribution, a novel particle swarm optimization (PSO)‐based multi‐user detector (MUD) aided time‐hopping ultra‐wide band (TH‐UWB) system has been investigated in the multi‐path channel model. In this approach, the PSO‐based MUD employs the output of the Rake receiver as its initial value to search for the best solution which results in a formulated optimization mechanism. By taking advantage of the heuristic values and the collective intelligence of PSO technique, the proposed detector offers almost the same bit error rate (BER) performance as the full‐search‐based optimum MUD does, while greatly reducing the potentially computational complexity. Simulation results have been provided to examine the evolutionary behavior and the detection performance of the proposed PSO‐based MUD in both the additive white Gaussian noise and the multi‐path fading channel. Copyright © 2011 John Wiley & Sons, Ltd.     

Adaline神经网络随机逼近LMS算法的仿真研究

基于最小二乘（LMS）统计算法的自适应线性元件（Adaline）神经网络是非线性分类的重要工具之一。从计算机仿真的角度研究随机逼近LMS学习方法的特点，从步长设置、收敛性、收敛速度、算法抗噪性、判断的准确率等多个参量评估随机逼近法的性能。仿真结果表明，对于不同的初始步长设置，神经元完成学习任务的训练时间不同；在保证学习收敛性的前提下，步长越大，收敛速度越快，但收敛的稳定性变差。权矢量的初始值设置对学习的收敛性没有影响。     

一种适用于强脉冲噪声下的对数型恒模盲均衡算法

针对脉冲噪声下恒模算法(Constant Modulus Algorithm,CMA)失败的问题,通过分析脉冲噪声的影响,提出了一种基于最小均方（Least Mean Square,LMS）准则的对数型恒模算法（Logarithmic-type CMA,LT-CMA）。LT-CMA利用对数函数的非线性变换特性自适应地抑制强脉冲噪声对误差函数的影响,并且利用l2-范数进行信号归一化处理以增强算法的稳健性。仿真结果表明,所提出的LT-CMA可以适应于高斯噪声环境和脉冲噪声环境;与经典自适应均衡算法相比,在收敛速度和稳健性两方面上,所提出的LT-CMA都有显著的提升。     

一种时频双选信道下OFDM系统的低复杂度迭代干扰抵消算法

为了消除正交频分复用(OFDM)系统在时频双选信道条件下由于信道快时变带来的载波间干扰,本文提出了一种新的低复杂度迭代干扰抵消方法.为了消除载波间干扰,已经提出了不少方法,但这些方法要么因为矩阵求逆运算带来了高计算复杂度,要么以性能退化为代价换来低计算复杂度.利用并行迭代干扰抵消技术,本文算法可以明显改善系统性能,同时借助带状矩阵近似和最小二乘QR分解(LSQR)迭代计算的特点来降低计算复杂度.仿真结果表明,在高信噪比条件下,随着迭代次数的增加,本文所提出的算法可以有效的减少"地板效应",在系统性能和计算复杂度之间取得更好的折中.     

自适应干扰抵消系统的双边带调幅干扰抵消特性

根据系统模型给出了自适应干扰抵消系统针对双边带调幅制干扰时的稳态权值表达式,推导出干扰抵消比计算式,分析了影响干扰抵消效果的因素及其作用规律,并给出了提高干扰抵消比的设计思路和方法。对于双边带调幅制信号,通过提高系统增益来提高干扰抵消比,将受到信号带宽和等效传输延迟距离的制约。信号带宽越宽或等效传输延迟距离越大,通过增大增益所能实现的干扰抵消比提高越有限。对于一定的信号带宽,可以通过增益和等效传输延迟距离的联合设计来提高干扰抵消比。仿真结果验证了理论分析的正确性和可行性。     

Sparse LMS/F algorithms with application to adaptive system identification

Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal‐to‐noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is slow convergence speed in high SNR case. Many finite impulse response systems are modeled as sparse rather than traditionally dense. To take advantage of system sparsity, different sparse LMS algorithms with l_p‐LMS and l₀‐LMS have been proposed to improve adaptive identification performance. However, sparse LMS algorithms have the same drawback as standard LMS. Different from LMS filter, standard LMS/F filter can achieve better performance. Hence, the aim of this paper is to introduce sparse penalties to the LMS/F algorithm so that it can further improve identification performance. We propose two sparse LMS/F algorithms using two sparse constraints to improve adaptive identification performance. Two experiments are performed to show the effectiveness of the proposed algorithms by computer simulation. In the first experiment, the number of nonzero coefficients is changing, and the proposed algorithms can achieve better mean square deviation performance than sparse LMS algorithms. In the second experiment, the number of nonzero coefficient is fixed, and mean square deviation performance of sparse LMS/F algorithms is still better than that of sparse LMS algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

Multistage linear receivers for DS-CDMA systems

A new family of multistage low-complexity linear receivers for direct sequence code division multiple access (DS-CDMA) communications is introduced. The objective of the proposed design is to mitigate the effect of multiple access interference (MAI), the most significant limiting factor of user capacity in the conventional DS-CDMA channel. The receivers presented here employ joint detection of multiple users and therefore require knowledge of all the signature codes and their timing. In addition, for a multipath environment, reliable estimates of the received powers and phases are assumed available for maximal ratio RAKE combining. Each stage of the underlying design recreates the overall modulation, noiseless channel, and demodulation process. The outputs of these stages are then linearly combined. The combining weights can be chosen to implement different linear detectors, including the decorrelating and minimum mean square error (MMSE) detectors. In this paper, we focus on implementing the MMSE detector. Simulation results illustrate that significant performance gains can be achieved in both synchronous and asynchronous systems.This work was presented in part at IEEE Communication Theory Workshop, April 23–26, 1995, and at IEEE MILCOM '95, November 5–8, 1995.This work was submitted in partial fulfillment of Ph.D. requirements at The City University of New York.     

Fixed-point blind adaptive multiuser detection algorithm for IR UWB systems in multipath channel

Using the hypothesis that data transmitted by different users are statistically independent of each other, this paper proposes a fixed-point blind adaptive multiuser detection algorithm for Time-Hopping (TH) Impulse Radio (IR) Ultra Wide Band (UWB) systems in multipath channel, which is based on Inde-pendent Component Analysis (ICA) idea. The proposed algorithm employs maximizing negentropy criterion to separate the data packets of different users. Then the user characteristic sequences are utilized to identify the data packet order of the desired user. This algorithm only needs the desired user’s characteristic se-quence instead of channel information, power information and time-hoping code of any user. Due to using hypothesis of statistical independence among users, the proposed algorithm has the outstanding Bit Error Rate (BER) performance and the excellent ability of near-far resistance. Simulation results demonstrate that this algorithm has the performance close to that of Maximum-Likelihood (ML) algorithm and is a subopti-mum blind adaptive multiuser detection algorithm of excellent near-far resistance and low complexity.     

Optimal and suboptimal receivers for code‐multiplexed transmitted‐reference ultra‐wideband systems

In this study, optimal and suboptimal receivers are investigated for code‐multiplexed transmitted‐reference (CM‐TR) ultra‐wideband systems. First, a single‐user scenario is considered, and a CM‐TR system is modeled as a generalized noncoherent pulse‐position modulated system. Based on that model, the optimal receiver that minimizes the bit error probability is derived. Then, it is shown that the conventional CM‐TR receiver converges to the optimal receiver under certain conditions and achieves close‐to‐optimal performance in practical cases. Next, multi‐user systems are considered, and the conventional receiver, blinking receiver, and chip discriminator are investigated. Also, the linear minimum mean‐squared error (MMSE) receiver is derived for the downlink of a multi‐user CM‐TR system. In addition, the maximum likelihood receiver is obtained as a performance benchmark. The practicality and the computational complexity of the receivers are discussed, and their performance is evaluated via simulations. The linear MMSE receiver is observed to provide the best trade‐off between performance and complexity/practicality. Copyright © 2011 John Wiley & Sons, Ltd.     

不相关高斯输入情况下LMS滤波器的收敛性分析

在分析最小均方自适应滤波器(LMS AF)均方误差(MSE)的收敛性时,文献常用统计自相关矩阵代替瞬时自相关矩阵以简化分析,由此得出的收敛条件比较粗糙。本文指出:不相关高斯输入情况下,无需如上简化,可依据高斯阶矩因式分解定理得到确切的MSE收敛条件,相应的失调表式能更准确地预报失调。     

FuzMet: a fuzzy‐logic based alert prioritization engine for intrusion detection systems

Intrusion detection systems (IDSs) are designed to monitor a networked environment and generate alerts whenever abnormal activities are detected. The number of these alerts can be very large, making their evaluation by security analysts a difficult task. Management is complicated by the need to configure the different components of alert evaluation systems. In addition, IDS alert management techniques, such as clustering and correlation, suffer from involving unrelated alerts in their processes and consequently provide results that are inaccurate and difficult to manage. Thus the tuning of an IDS alert management system in order to provide optimal results remains a major challenge, which is further complicated by the large spectrum of potential attacks the system can be subject to. This paper considers the specification and configuration issues of FuzMet, a novel IDS alert management system which employs several metrics and a fuzzy‐logic based approach for scoring and prioritizing alerts. In addition, it features an alert rescoring technique that leads to a further reduction in the number of alerts. Comparative results between SNORT scores and FuzMet alert prioritization onto a real attack dataset are presented, along with a simulation‐based investigation of the optimal configuration of FuzMet. The results prove the enhanced intrusion detection accuracy brought by our system. Copyright © 2011 John Wiley & Sons, Ltd.     

基于FPGA和符号LMS算法的自适应滤波器设计

为了减少实现基于FPGA和LMS算法的自适应滤波器过多消耗硬件资源的问题,提出了符号LMS算法,通过降低乘法运算的次数来提高自适应滤波器的运行速度,并使用流水线技术进行优化。软件仿真验证了符号LMS算法的可行性,硬件仿真证实了采用该算法和流水线技术的自适应滤波器的优越性。     

基于频域特性的时间交替模数转换系统采样时间误差校正算法

时间交替模数转换器(Time-Interleaved ADC,TIADC)通道间的采样时间相对误差严重影响了系统的无杂散动态范围(Spurious-Free Dynamic Range,SFDR).为校正采样时间相对误差,本文基于TIADC输出与模拟输入信号之间的频域关系,提出一种通过消除输出信号中的误差来校准TIADC的算法.该算法在对输出信号频率表达式进行泰勒近似的基础上构建理想输出信号,并采用最小均方差(LMS)算法来估算时间误差,旨在降低硬件设计的复杂度,提高误差校正的精确度.仿真和验证结果表明该校正算法很容易扩展到多通道,并且可以将输出频谱的SFDR提高约47dB.