Robust Least Squares Constant Modulus Algorithm to Signal Steering Vector Mismatches

The linearly constrained least squares constant modulus algorithm (LSCMA) may suffer significant performance degradation and lack robustness in the presence of the slight mismatches between the actual and assumed signal steering vectors, which can cause the serious problem of desired signal cancellation. To account for the mismatches, we propose a doubly constrained robust LSCMA based on explicit modeling of uncertainty in the desired signal array response and data covariance matrix, which provides robustness against pointing errors and random perturbations in detector parameters. Our algorithm optimizes the worst-case performance by minimizing the output SINR while maintaining a distortionless response for the worst-case signal steering vector. The weight vector can be optimized by the partial Taylor-series expansion and Lagrange multiplier method, and the optimal value of the Lagrange multiplier is iteratively derived based on the known level of uncertainty in the signal DOA. The proposed implementation based on iterative minimization eliminates the covariance matrix inversion estimation at a comparable cost with that of the existing LSCMA. We present a theoretical analysis of our proposed algorithm in terms of convergence, SINR performance, array beampattern gain, and complexity cost in the presence of random steering vector mismatches. In contrast to the linearly constrained LSCMA, the proposed algorithm provides excellent robustness against the signal steering vector mismatches, yields improved signal capture performance, has superior performance on SINR improvement, and enhances the array system performance under random perturbations in sensor parameters. The on-line implementation and significant SINR enhancement support the practicability of the proposed algorithm. The numerical experiments have been carried out to demonstrate the superiority of the proposed algorithm on beampattern control and output SINR enhancement compared with linearly constrained LSCMA.     

The Linearly Constrained LSCMA for Blind Multi-user Detection

The least square constant modulus algorithm (LSCMA) is a popular constant modulus algorithm (CMA) because of its global convergence and stability. But the performance will degrade when it is affected by the problem of interference capture in the MC-CDMA system that has several constant modulus signals. In order to overcome this shortage, a linearly constrained LSCMA multiuser detection algorithm is proposed by using the spreading code of the desired user to impose linear constraint on the LSCMA. The proposed algorithm ensures the algorithm convergence to the desired user. Thus the performance of the system is improved. The simulation results demonstrate that the proposed algorithm offers faster convergence rate and provides better output signal-to-interference-plus-noise-ratio (SINR) and bit error rate (BER) performance compared with the traditional LSCMA.     

A dynamic CSFICA and feature‐based collision detection method in multichannel space‐based AIS

To detect message collisions in multichannel spaced‐based automatic identification system (AIS), a dynamic complex symmetric fast independent component analysis (CSFICA) and feature‐based collision detection method is proposed in this paper. A fast and stable blind source separation algorithm, dynamic CSFICA, is utilized to separate signals dynamically and improve the signal‐to‐interference ratio (SIR) in each channel. A frequency and phase offset insensitive feature detection algorithm is used to calculate the test statistics in each channel. The false alarm is suppressed by applying the arithmetic to geometric mean (AGM) method, and test statistics of channels with sufficient signal quality are extracted to detect the preamble. Simulation results show that the proposed algorithm outperforms the reference feature detection algorithm under collision conditions and is insensitive to the SIR. The proposed algorithm is more resistant to false alarm caused by signal (FAS) than the differential correlation (DC) algorithm.     

The LSCM_SUB algorithm for blind multiuser detection in multipath CDMA channels

1 Introduction Multiuser detection (MUD) is applied mainly in CDMA to cancel the multiaccess interference. The single-user matched filter or RAKE receiver treats interference from other users as noise, but MUD takes advantage of other user’s interference…     

A fast tag identification anti‐collision algorithm for RFID systems

In this work, we propose a highly efficient binary tree‐based anti‐collision algorithm for radio frequency identification (RFID) tag identification. The proposed binary splitting modified dynamic tree (BS‐MDT) algorithm employs a binary splitting tree to achieve accurate tag estimation and a modified dynamic tree algorithm for rapid tag identification. We mathematically evaluate the performance of the BS‐MDT algorithm in terms of the system efficiency and the time system efficiency based on the ISO/IEC 18000‐6 Type B standard. The derived mathematical model is validated using computer simulations. Numerical results show that the proposed BS‐MDT algorithm can provide the system efficiency of 46% and time system efficiency of 74%, outperforming all other well‐performed algorithms.     

基于空闲时隙消除的超高频RFID防碰撞算法

标签防碰撞是射频识别系统中的一项重要研究课题.为了进一步提高射频识别系统的性能和降低复杂度,提出了一种基于空闲时隙消除的二进制分裂算法.该算法在二进制分裂算法中引入了单比特状态标识位,在识别过程中,标签在ID数据传输之前先发送单比特随机信号,用于判定时隙是否碰撞,从而避免了冗余的信息传输.由于该算法彻底消除了传统二进制随机数分裂方法中的空闲时隙,因此节省了识别过程中的协调时间开销.最后通过理论分析和仿真结果证明：ISE-BS算法的吞吐率稳定在40.65%左右,时间效率稳定在32.46%左右,ISE-BS算法相比于现有的防碰撞算法性能更优.从实现的角度,比较了各个算法的浮点运算成本,结果显示提出的算法可以极大的降低系统复杂度.     

A new anti‐collision protocol based on information of collided tags in RFID systems

Radio frequency identification (RFID) technology has recently become an integral part of a wide range of applications. One of the challenges in RFID systems is the tag anti‐collision issue, for which several anti‐collision tag identification protocols have been proposed. This paper proposes a novel slotted ALOHA‐based RFID tag anti‐collision algorithm which can be employed for tag identification. The main idea of this algorithm is to use the information available in collision slots, called collided data, to identify tags uniquely. For this purpose, the collision slots that include only two tags are selected. Then, the non‐conflict bits in these slots are used to possibly identifying the tags. Because in the proposed algorithm readers use both single slots and also the collision slots for tag identification, the performance is increased significantly compared with other protocols. Results of the study indicate that in the proposed algorithm, the optimal frame size for an individual tag number is equal to the half of tags number and the efficiency of the proposed protocol is improved to about 73%. Copyright © 2015 John Wiley & Sons, Ltd.     

基于子空间的线性约束最小二乘恒模算法

线性约束最小二乘恒模算法能够有效克服恒模算法中存在的干扰捕获问题,然而,在实际的系统中,由于受到来自噪声子空间分量的影响,从而导致性能下降。针对这一问题,该文提出了一种基于子空间方法的线性约束最小二乘恒模(SLSCM)多用户检测算法并对其性能进行了理论分析。该算法收敛速度快,信道跟踪能力强,有较好的输出信干噪比和误码率性能。理论分析和仿真实验验证了该文算法的有效性和优越性。     

Network application profiling with traffic causality graphs

A network application profiling framework is proposed that is based on traffic causality graphs (TCGs), representing temporal and spatial causality of flows to identify application programs. The proposed framework consists of three modules: the feature vector space construction using discriminative patterns extracted from TCGs by a graph‐mining algorithm; a feature vector supervised learning procedure in the constructed vector space; and an application identification program using a similarity measure in the feature vector space. Accuracy of the proposed framework for application identification is evaluated, making use of ground truth packet traces from seven peer‐to‐peer (P2P) application programs. It is demonstrated that this framework achieves an overall 90.0% accuracy in application identification. Contributions are twofold: (1) using a graph‐mining algorithm, the proposed framework enables automatic extraction of discriminative patterns serving as identification features; 2) high accuracy in application identification is achieved, notably for P2P applications that are more difficult to identify because of their using random ports and potential communication encryption. Copyright © 2014 John Wiley & Sons, Ltd.     

Gen2‐Based Tag Anti‐collision Algorithms Using Chebyshev's Inequality and Adjustable Frame Size

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti‐collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation‐2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti‐collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti‐collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.     

一种改进的盲自适应波束形成算法

本文在最小二乘恒模（LSCMA）和梯度下降法（SDCMA）的基础上，提出了一种基于预解扩的判决反馈盲自适应波束形成算法，称为LS—SDCMA。本文分别在加性白高斯和多径衰落信道的环境中进行了仿真，仿真结果表明，本文提出的LS—SDCMA算法比传统的LSCMA、OCMA和SDCMA算法具有较强的抗多址干扰能力。     

Frequency offset insensitive demodulation algorithm for satellite‐based automatic identification system

The frequency offset caused by the Doppler shift and the oscillators instability degrades the performance of satellite‐based demodulators for automatic identification system (AIS) signals unless proper synchronization algorithms are used. A noncoherent demodulation algorithm (NDA) based on cyclic redundancy check (CRC) error correction is proposed in this paper, which is able to tolerate large frequency offsets, thus avoiding the use of an explicit frequency synchronizer. To reduce the complexity, the number of CRC register states for error correction can be limited. Simulation results of the proposed algorithm are presented and compared with other demodulation algorithms in the literature in terms of bit error rate (BER) and packet error rate (PER).     

A constant false alarm rate frame detector for satellite‐based automatic identification system

Frame detection is an important step in satellite‐based automatic identification system for its contributions in verifying the presence of automatic identification system signal before frame synchronization. In this paper, a constant false alarm rate frame detector is proposed, which exploits the feature implied in the training sequence, to realize frame detection in the presence of additive white Gaussian noise and frequency offset. False alarm probability is related with a threshold, which is independent of the signal and noise. For fixed false alarm probability, the relationship between detection performance and E_b/N₀ is analyzed. Simulations prove that the proposed detector outperforms the detector based on cyclic autocorrelation when message collisions exist. Copyright © 2016 John Wiley & Sons, Ltd.     

MC-CDMA系统中一种盲多用户检测算法

本文提出了MC-CDMA系统中一种预处理的盲多用户检测算法P-LSCMA,它是对MC-CDMA接收信号 进行预处理,消除部分多址干扰,然后再用LSCMA算法消除由于信道在各个子载波上对信号造成的影响,从而在每次 迭代合并中提高了系统的检测性能。     

Application of ICA-based anti-collision algorithm in RFID system

Data collision problem exists in radio frequency identification (RFID) system when tabs are present in the interrogation zone of a single reader at the same time. Though different anti-collision methods have been proposed, it still needs further study on how to improve the identification ability especially in the interference circumstance. This paper presents a new method based on independent component analysis (ICA) algorithm. Coded division multiple access (CDMA) technology is adopted at the transmitter and the maximum signal to noise ratio is applied at the receiver of the RFID system. The proposed method has been verified by computer simulation which shows that the system can separate different users’ source data correctly based on ICA algorithm and has better performance compared with the traditional CDMA technology.     

基于自适应波束形成的鱼雷对潜目标识别技术

通过鱼雷对潜目标准确识别,实现对目标的精确打击。当前的目标识别算法采用时频特征提取算法,随着海洋背景噪声强度的增大,准确识别概率不高。提出一种采用亮点回波信号自适应波束形成的鱼雷对潜目标识别算法,首先进行了鱼雷对潜攻击声探测亮点回波模型构建,采用级联滤波器进行回波信号降噪处理,对滤波后的输出信号进行自适应波束形成处理,实现信号的特征提取和指向性聚焦,提高目标亮点回波信号的检测性能,实现目标准确识别。仿真结果表明,采用该算法进行鱼雷对潜目标检测识别,准确检测概率高于传统算法,在低信混比下仍具有较好的准确识别率,抗干扰性能较好。     

Blind identification of autoregressive system using chaos

The problem of identifying an autoregressive (AR) model using chaos is investigated here. Based on the Cramer-Rao bound (CRB) analysis, it is proved here that when chaos is used to drive an AR system, identification using only the output signal can be as good as that based on using both input and output signals, that is, blind identification is equivalent to nonblind identification. A deterministic maximum likelihood (ML) is, therefore, developed to blindly identify an AR system driven by chaos. Combined with the global search technique genetic algorithm (GA), the proposed GA-ML method is found to achieve the optimal identification performance imposed by the CRB. The theoretical mean square error (MSE) performance of the proposed GA-ML method is derived, and the result is validated using computer simulations. Compared to conventional methods based on white Gaussian driving signal, the chaos approach is shown to have superior performance. The improvement is proved to be the result of the positive and finite Lyapunov exponent of the chaotic signal. The proposed chaos identification method is applied to blind equalization of a spread spectrum (SS) communication system where chaos is used to modulate the information signal. Computer simulations show that the proposed chaos approach has a satisfactory equalization performance even under strong channel effects.     

改进型动态时隙冲突跟踪树标签防碰撞算法

射频识别RFID(Radio Frequency Identification)系统内的读卡器在识别大数量标签时常因信号的碰撞而导致系统识别效率降低.动态时隙冲突跟踪树算法DSCTTA(Dynamic Slots Collision Tracking Tree Algorithm)采用动态时隙应答机制可减少前缀开销和迭代开销,但会产生大量空闲时隙.本文将DSCTTA和比特转换方式(BCM)相结合,得到改进型动态时隙冲突跟踪树标签防碰撞算法(IDSCTTA)以防止标签冲突,加快标签识别速度.理论分析及仿真结果表明,IDSCTTA不仅具有DSCTTA的全部优点,而且能够有效地减小识别时延和提高时隙效率,并且标签数目越大,算法性能越优越.     

星载AIS的复值FastICA算法改进

针对星载船舶自动识别系统( AIS )的含噪复值信号盲分离算法分离效果不佳的问题,提出了改进的复值快速独立分量分析算法( FastICA)。该改进算法针对混合信号数目大于源信号数目的超定情况,对含噪混合信号的协方差矩阵进行特征值分解,利用其噪声对应的几个较小特征值估计噪声方差,修正白化矩阵,再应用Huber M估计函数优化该算法的目标函数。实验结果表明,运用该算法信号均方误差( SMSE)变小,信干比( SIR)变大,提高了信号的分离性能;同时,优化后的目标函数使算法具有良好的稳健性。     

基于同步压缩小波变换的主信号抑制技术

在辐射源个体识别(SEI)技术中,能量较高的主信号往往导致微弱个体特征稳定性降低,进而影响最终的个体识别效果。为了解决该问题并提升辐射源个体识别性能,该文提出基于同步压缩小波变换的主信号抑制技术。首先,利用静态小波变换完成对带噪信号的去噪预处理;然后,利用同步压缩小波变换完成对主信号的检测和抑制,并以均方根误差和皮尔逊相关系数为数值指标,验证算法的有效性;最后,在主信号抑制的基础上,利用分形理论中盒维数完成对信号的特征提取,并利用单核支持向量机验证个体识别性能。实验结果表明,与主信号抑制之前相比,主信号抑制算法下个体识别率提升了10%左右,验证了同步压缩小波变换的主信号抑制算法对辐射源个体识别率提升的有效性。