The teletraffic analysis of the multi-server loss model with renewal distributions

This paper presents a loss model in which a general renewal arrival stream is served by any number of general renewal servers, i.e., theGI/GI/s/s model. Using linear algebraic queueing theory (LAQT), we provide the exact steady-state solution of the number of customers in theGI/GI/s/s model at general, arrival, and departure times. We show that the steady-state solution at arrival times can be used to approximate those at general times and that the third moment of the arrival process significantly affects this approximation. Finally, we show that a conjectured inequality does not hold.This work was performed while at the University of Missouri-Kansas City.     

An examination of correlation effects among warranty claims

This paper models & examines the impact of correlation in a failure arrival process which generates a warranty claim with each occurring failure. We show that even slight positive correlation in the warranty claims arrival process can significantly impact the expected number of claims observed, and the length of the transient period. We are not suggesting that renewal processes are necessarily inappropriate or incorrect as models for the arriving warranty claims process. Rather, we emphasize the importance of considering correlation in the claims arrival process, and suggest that more research is needed to explore mathematical models which explicitly consider correlation in the warranty analysis framework.     

Approximation techniques for computing packet loss infinite-buffered voice multiplexers

Three different approximation techniques are examined. The performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e., the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process, and performance calculations are based only on the first two moments of the renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP attempts to capture aspects of the arrival process in a more intuitive manner than previously proposed approaches for determining the MMPP parameters and is shown to compute loss more accurately. Finally, a fluid flow approximation for computing packet loss is evaluated. For all three approaches, a unifying example, the case of multiplexing voice sources over a T1-rate link is considered. The main conclusion is that both the MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest     

基于矢量水听器线谱法目标方位估计

利用矢量水听器收集到的声压和振速信息,研究基于互谱法分析单目标的强线谱来进行目标方位估计。提出了单线谱法和多线谱法两种目标方位估计方法。其中,在分析多线谱法方位估计时,采用了直接平均和加权平均两种处理方法对多线谱进行处理,旨在提高目标方位估计精度。在原理阐述的基础上,通过仿真和湖试实验进一步分析比较了两种方位估计方法。     

Entropy and the timing capacity of discrete queues

Queueing systems which map Poisson input processes to Poisson output processes have been well-studied in classical queueing theory. This paper considers two discrete-time queues whose analogs in continuous-time possess the Poisson-in-Poisson-out property. It is shown that when packets arriving according to an arbitrary ergodic stationary arrival process are passed through these queueing systems, the corresponding departure process has an entropy rate no less (some times strictly more) than the entropy rate of the arrival process. Some useful by-products are discrete-time versions of: (i) a proof of the celebrated Burke's (1956) theorem, (ii) a proof of the uniqueness, amongst renewal inputs, of the Poisson process as a fixed point for exponential server queues proposed by Anantharam (1993), and (iii) connections with the timing capacity of queues described by Anantharam and Verdu (1996).     

网络通信业务量的标值更新模型

本文利用标值更新过程，提出了一个较为通用的通信量统计模型。该模型可以对具有任意带宽分布和递减非凸自相关函数的通信量提供直接的拟合，不仅可以用于通信量的模拟，也可用于理论分析。讨论了该模型在通信量模拟中的应用，具有参数估计算法简单的特点，最后将该模型用于ＡＴＭ网络中的可变比特率视频源的模拟，数值结果表明其具有良好的模拟性能。     

Markovian Arrival Process Parameter Estimation With Group Data

This paper addresses a parameter estimation problem of Markovian arrival process (MAP). In network traffic measurement experiments, one often encounters the group data where arrival times for a group are collected as one bin. Although the group data are observed in many situations, nearly all existing estimation methods for MAP are based on nongroup data. This paper proposes a numerical procedure for fitting a MAP and a Markov-modulated Poisson process (MMPP) to group data. The proposed algorithm is based on the expectation-maximization (EM) approach and is a natural but significant extension of the existing EM algorithms to estimate parameters of the MAP and MMPP. Specifically for the MMPP estimation, we provide an efficient approximation based on the proposed EM algorithm. We examine the performance of proposed algorithms via numerical experiments and present an example of traffic analysis with real traffic data.      

Application of deterministic annealing EM algorithm to MAP/PH parameter estimation

This paper proposes a variant of EM (expectation-maximization) algorithm for Markovian arrival process (MAP) and phase-type distribution (PH) parameter estimation. Especially, we derive the deterministic annealing EM (DAEM) algorithm for MAP/PH parameter estimation. The DAEM algorithm is one of the methods to overcome a local maxima problem associated with the conventional EM algorithm. This paper derives concrete E- and M-step formulas for MAP parameter estimation from inter-arrival time data and PH parameter estimation from point samples in the framework of DAEM algorithm. Numerical examples demonstrate the DAEM algorithm for Markov-modulated Poisson process (MMPP) and several classes of PH distribution.     

Fairly adjusted multimode dynamic guard bandwidth admission control over CDMA systems

Guard-based call admission control schemes support admission priorities based on resources sharing with differentiated resource capacity limits. To minimize deviation from call blocking/dropping targets due to nonstationary call arrival condition, dynamic guard-based schemes with predictive adaptation control adjust differentiated capacity limits according to predicted future arrival rates based on specified estimation algorithms. Existing dynamic guard admission schemes are developed under the assumption of perfect estimation, which may not be possible in a highly nonstationary environment and, thus resulting in failures to maintain targeted blocking/dropping probabilities. This paper presents the fairly adjusted multimode-dynamic guard bandwidth scheme, which is a dynamic-guard-based scheme over code-division multiple-access systems with predictive adaptation control to adapt interference-based guard loading-limits under nonstationary call arrival condition; and reactive adaptation control to counteract arrival rate estimation errors. When the predictive adaptation control policy mode is not able to maintain long-term call blocking or dropping targets due to estimation error, this will trigger reactive adaptation control policy modes that include temporary blocking (preemption) of one or more lower priority classes subject to fairness constraints to ensure lower priority classes are not preempted at all costs during estimation error recovery. Analytical and simulation results show that proposed scheme is able to provide performance guarantees in terms of dropping probabilities under nonstationary traffic arrival and imperfect arrival rate estimation.     

Parameter estimation for partially observed queues

We consider parameter estimation for a FIFO queue with deterministic service times and two independent arrival streams of “observed” and “unobserved” packets. The arrivals of unobserved packets are Poisson with an unknown rate λ while the arrivals of observed packets are arbitrary. Maximum likelihood estimation of λ is formulated based on the arrival times and waiting times of k observed packets. The likelihood function is derived in terms of the transition probabilities of the unfinished work process which are calculated recursively. Sufficient conditions for consistency, asymptotic normality, and asymptotic efficiency are given. The mean and variance of the MLE are measured in simulation experiments. Numerical results indicate that the MLE is consistent and asymptotically normal     

一种基于余弦函数的相位干涉仪阵列DOA估计算法

该文针对相位干涉仪阵列估计波达角过程中的相位差模糊问题,提出一种基于余弦函数的波达角估计算法,并分析了该算法的估计值唯一性条件,该条件比相位差解模糊算法的唯一性条件更宽松。不同情况下的仿真结果表明,只要阵列的基线距离满足估计值唯一性条件,采用该算法能够有效进行高精度的波达角估计。     

Subspace Smoothing for Direction of Arrival Estimation in DS-CDMA Systems

In this paper a subspace processing method is introduced that can be used for direction of arrival estimation of coherent signals in an asynchronous DS-CDMA system. Conventional methods of direction of arrival estimation are not directly applicable to the case of multiple coherent signals that impinge on an antenna array from different directions. Some preprocessing is essential prior to estimation in this case. The proposed method exploits the spreading code and the path delays of the desired user to eliminate the contribution of undesired paths in the signal subspace. To this end, the signal subspace is mapped to a new subspace which contains the spatial-temporal signature of the desired signal. Once the desired subspace is created, conventional methods such as MUSIC and ESPRIT can be employed to estimate the desired directions of arrival. It is proved that the obtained direction of arrival estimator, based on the proposed method, is consistent. Also, the estimation performance is evaluated by comparing the proposed method with conventional estimation methods.     

稀疏表示框架下无需参数配对的二维到达角估计

现有二维到达角估计算法大多基于子空间理论及需要参数配对,针对这一问题,在稀疏表示理论框架下提出了一种参数自动配对的二维到达角估计新算法。该算法在L阵列下构建阵列互相关矩阵的稀疏表示模型,利用奇异值分解降低复杂度并基于群LASSO(Least Absolute Shrinkage and Selection Operator)获得方位角估计。在方位角估计的基础上,基于向量化操作构建稀疏空间谱匹配模型,然后利用LASSO 获得俯仰角估计。与参数配对ESPRIT 和改进的传播算子方法相比,所提算法不仅无需参数配对过程,而且可以提供改进的估计精度。计算机仿真结果验证了所提算法的有效性。     

Acoustic emission source location in dispersive media

In this paper, the acoustic emission source (AE) is located by a non-iterative method using the time-of-arrival (TOA) of several events, received in an array of sensors arbitrary positioning in the 3D space. If at least two event velocities are different, a common property in dispersive propagation, and the array of sensors is not lying in a plane, a close-form estimation of the source–sensors distances, AE time and material constant is derived. Moreover, a direct estimation of the source position is achieved using the multidimensional scaling approach. In simulation experiments, the proposed method detects accurately the location of AE sources, reducing also the ambiguity introduced by noisy arrival times.     

一种高精度低复杂度波达方向估计新方法

提出了一种应用于移动自主网中节点定位的波达方向(Direction of Arrival,DOA)估计新方法,以满足移动自主网对节点定位机制的高精度和低复杂度的要求。利用牛顿法将延迟相加法和求根多重信号分类算法(Root-MUSIC)进行联合估计,定位过程分为2个阶段:采用延迟相加法进行实时粗略DOA估计;采用Root-MUSIC进行精准定位。将该方法实现于软件无线电(SDR)系统,综合了延迟相加法低复杂度和Root-MUSIC高估计精度的优点。Matlab仿真实验结果证明了该方法以较低的复杂度获得近似于单独采用Root-MUSIC所达到的高精度,解决了现有方法难以同时达到高精度和低复杂度的问题。     

脉冲噪声下基于中值离差相关熵的DOA估计方法

作为阵列信号处理的一个基本问题,波达方向估计在现代通信领域有着广泛的应用。常规估计方法通常基于高斯噪声假设。 而当阵列接收数据包含 Alpha 稳定分布脉冲噪声时算法将完全失效。针对 Alpha 稳定分布噪声下的波达方向估计问题,本文定义了一种改进的相关熵算子——中值离差相关熵,并从理论上证明了它的有界性。 以此为基础结合 MUSIC 算法提出了一种波达方向估计新方法。该方法不需要噪声先验知识,且在脉冲噪声环境中具有鲁棒性。仿真实验表明, 即使在短快拍、强脉冲噪声的恶劣环境下,本文方法依然具有良好的性能。      

基于高阶累积量的近场通信波达方向估计算法

通过对近场通信波达方向准确估计,提高目标信源的定位能力.传统方法中对近场源通信信源的波达方向估计采用多普勒估计方法,由于近场通信的空间信源为窄带信号,多普勒估计会导致DOA估计频谱失真.提出一种基于高阶累积量的近场通信波达方向估计算法.采用均匀间隔线列阵构建近场通信的信号模型,进行近场源目标特征构建,提取近场源通信信号的斜度和峰度等特征,采用高阶累积量特征提取方法,分别求得对应近场通信信源的方位角、频率和距离三维参数,使得每个信源的参数自动配对,提高了近场通信DOA波达方向估计的效率和精度,实现近场源通信信号的波达方向估计算法改进.仿真实验结果表明,采用该方法进行近场方法波达方向估计的精度较高,对信源方位的定位准确,性能优越于传统方法,在近场通信中具有较好的应用价值.     

A sample path property of matched-filter outputs with applications to detection and estimation

The stochastic process at the output of a matched filter, when the latter is excited by its proper signal in additive white noise, has a mean function proportional to its covariance function. Sample path properties of a Gaussian process with the mean proportional to the covariance, conditioned such that it assumes a given value at the instant of the peak in the mean, are independent of signal amplitude. Formal and rigorous proofs and a detection-theoretical interpretation of this result are presented. It is then applied to the calculation of the detection probability of a rectangular signal of unknown time of arrival and to bounding the threshold effect in the estimation of the time of arrival. A novel passage time result is derived in the Appendix.     

带优先权与不耐烦顾客排队模型的模拟仿真

考虑一个有两类顾客到达的单服务台的排队系统。两类顾客的到达过程均为泊松过程,第一类顾客较第二类顾客具有强占优先权,且第二类顾客由于第一类顾客的到达而变得不耐烦,其＂耐性时间＂服从负指数分布。两类顾客的服务时间服从相同参数的负指数分布,服务规则是强占优先服务,在高负荷条件下用Matlab编程对此排队系统进行模拟仿真,为处理此类排队问题提供了一个新方法。     

基于改进的循环互相关MUSIC算法的波达方向估计

给出了基于循环互相关运算的信号模型，根据该信号模型，运用改进的循环互相MUSIC算法得到了对具有循环平稳特性的空间源信号波达方向进行估计的有效方法——ICCC-MUSIC算法；定性的分析和仿真实验均表明该方法具有较好的抑制噪声和选择信号的能力，为利用天线阵列提取具有循环平稳特性的源信号提供了较好的实现方法。