Unitary root-MUSIC with a real-valued eigendecomposition: atheoretical and experimental performance study

A real-valued (unitary) formulation of the popular root-MUSIC direction-of-arrival (DOA) estimation technique is considered. This unitary root-MUSIC algorithm reduces the computational complexity in the eigenanalysis stage of root-MUSIC because it exploits the eigendecomposition of a real-valued covariance matrix. The asymptotic performance of unitary root-MUSIC is analyzed and compared with that of conventional root-MUSIC. The results of this comparison show identical asymptotic properties of both algorithms in the case of uncorrelated sources and a better performance of unitary root-MUSIC in scenarios with partially correlated or fully coherent sources. Additionally, our simulations and the results of sonar and ultrasonic real data processing demonstrate an improved threshold performance of unitary root-MUSIC relative to conventional root-MUSIC. It can be then recommended that, as a rule, the unitary root-MUSIC technique should be preferred by the user to the conventional root-MUSIC algorithm     

Advantages of nonuniform arrays using root-MUSIC

In this paper, we consider the Direction-Of-Arrival (DOA) estimation problem in the Nonuniform Linear Arrays (NLA) case, particularly the arrays with missing sensors. We show that the root-MUSIC algorithm can be directly applied to this case and that it can fully exploit the advantages of using an NLA instead of a Uniform Linear Array (ULA). Using theoretical analysis and simulations, we demonstrate that employing an NLA with the same number of sensors as the ULA, yields better performance. Moreover, reducing the number of sensors while keeping the same array aperture as the ULA slightly modifies the Mean Square Error (MSE). Therefore, thanks to the NLA, it is possible to maintain a good resolution while decreasing the number of sensors. We also show that root-MUSIC presents good performance and is one of the simplest high resolution methods for this type of arrays. Closed-form expressions of the estimator variance and the Cramer–Rao Bound (CRB) are derived in order to support our simulation results. In addition, the analytical expression of the CRB of the NLA to the CRB of the ULA ratio is calculated in order to show the advantages of the NLA.     

Moments-based approach to the performance analysis of equal gain diversity in Nakagami-m fading

In this letter, an alternative moments-based approach for the performance analysis of an L-branch predetection equal gain combiner (EGC) over independent or correlated Nakagami-m fading channels is presented. Exact closed-form expressions are derived for the moments of the EGC output signal-to-noise ratio (SNR), while the corresponding moment-generating function (MGF) is accurately approximated with the aid of Pade/spl acute/ approximants theory. Important performance criteria are studied; the average output SNR, which is expressed in closed form both for independent and correlative fading and for arbitrary system parameters, the average symbol-error probability for several coherent, noncoherent, and multilevel modulation schemes, and the outage probability, which are both accurately approximated using the well-known MGF approach. The proposed mathematical analysis is illustrated by various numerical results, and computer simulations have been performed to verify the validity and the accuracy of the theoretical approach.     

A unified approach to the performance analysis of digitalcommunication over generalized fading channels

Presented here is a unified approach to evaluating the error-rate performance of digital communication systems operating over a generalized fading channel. What enables the unification is the recognition of the desirable form for alternate representations of the Gaussian and Marcum Q-functions that are characteristic of error-probability expressions for coherent, differentially coherent, and noncoherent forms of detection. It is shown that in the largest majority of cases, these error-rate expressions can be put in the form of a single integral with finite limits and an integrand composed of elementary functions, thus readily enabling numerical evaluation     

A unified approach to the performance analysis of speed estimation techniques in mobile communication

Estimation of the mobile speed, or equivalently, the maximum Doppler frequency, is of importance in a variety of applications in wireless mobile communications. In this paper, a unified framework for the performance analysis of several major speed estimation techniques is presented, which allows a fair comparison between all the methods, analytically. Interestingly, it is proved that all these methods are equivalent, asymptotically, i.e., for large observation intervals. In addition, we have derived closed-from expressions for the bias and variance of a recently proposed covariance-based method. We have also introduced a new estimator which relies on the average number of maxima of the inphase component, and have calculated its variance, analytically. Our extensive performance analysis, supported by Monte Carlo simulations, have revealed that depending on the channel condition and the observation interval, one needs to use a crossing- or a covariance-based technique, to achieve the desired estimation accuracy over a large range of mobile speeds.     

A graphic approach to performance analysis of multistage linear interference canceller in long-code CDMA systems

The signal-to-interference-plus-noise-ratio performance of the multistage linear parallel and successive interference cancellers (LPIC and LSIC) in a long-code code-division multiple-access system is analyzed using a graphical approach. The decision statistic is modeled as a Gaussian random variable, whose mean and variance can be expressed as functions of moments of R for the LPIC and L for the LSIC, respectively, where R is the correlation matrix of signature sequences and L is the strict lower triangular part of R. Since the complexity of calculating these moments increases rapidly with the growth of the stage index, a graphical representation of moments is developed to facilitate the computation. Propositions are presented to relate the moment calculation problem to several well-known problems in graph theory, i.e., the coloring, the graph decomposition, the biconnected component finding, and the Euler tour problems. It is shown that the derived analytic results match well with simulation results.     

Statistical approach to reduction of circuit performance variability

A statistical method is described for reducing the variance observed in the response of a circuit due to tolerances on circuit parameters.     

Network-theoretical approach to orotron analysis

For the use of oscillators in microwave networks, the knowledge of the behavior of the isolated oscillator is not sufficient. Of major interest is the interaction of the device with the external circuit, where questions about stability, modulation, injection locking, noise, etc. arise. If it is possible to describe the behavior of the active element in the frequency domain, the answers to the above mentioned questions can be found utilizing the standard methods of network theory. Recently the gyrotron oscillator has been described successfully in the frequency domain [1].     

Adaptive QoS parameters approach to modeling Internet performance

Due to the recent advances in Internet technologies and applications, the issue of Quality of Service (QoS) is more essential to Internet performance. In this paper, we address and discuss the influence factors and also finalize the QoS parameters for Internet performance. Then we present the simulation procedure for monitoring the performance evaluation and propose the algorithm for tuning the performance value. Based on simulation results and performance analysis, we can tune and adjust possible parameters' values and then refine the influence level of each QoS parameter. Finally, Internet performance can be enhanced and maintained through using the proposed approach over several sub‐networks. Hence, it increases the adaptability for implementing the QoS Internet. Copyright © 2002 John Wiley & Sons, Ltd.     

The state-variable approach to network analysis

The universality of the state-variable approach to network analysis is demonstrated in general discussions and specific examples. The method of formulation of the state equations for an arbitrary lumped, linear, finite, reciprocal, passive, time-invariant network is presented fully, while the relaxation of these restrictions is indicated in detail; i.e., the state-variable characterization of active, nonreciprocal, time-variable, and nonlinear networks is discussed. Finally, there is a brief guide of the current research where the state-variable analysis is brought to bear upon certain qualitative aspects of classical and nonclassical network behavior.     

A parallelism-based analytic approach to performance evaluationusing application programs

A brief overview of performance evaluation and benchmarking is presented. It is shown that traditional performance measurements recorded in these activities are really a direct measurement of the parallelism in software and hardware. A framework called the `Path to Performance' that identifies the agents and activities that change the parallelism as it moves from problem to solution is developed. It is shown where the various current application benchmarks apply probes on the Path and which agents are being measured. The traditional time-based performance measurements are recast into parallelism-based performance measurements to show that understanding performance implies understanding the parallelism. A simulation tool and methodology are described for measuring and comparing the executed parallelism on a single CRAY Y-MP CPU. Application of the methodology to several of the Perfect Benchmarks suggests that the benchmarking utility of these programs on the Y-MP may be questioned because they exercise the machine in the same way     

The SURE approach to reliability analysis

The SURE computer program, a reliability-analysis tool for ultrareliable computer-system architectures, provides an efficient means for computing reasonably accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, SURE automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values, thus directing SURE to perform a sensitivity analysis automatically. The program provides a rapid computational capability for semi-Markov models useful for describing the fault-handling behavior of fault-tolerant computer systems. The only modeling restriction imposed by the program is that the nonexponential recovery transitions must be fast in comparison to the mission time. The SURE reliability-analysis method uses a fast bounding theorem based on means and variances and yields upper and lower bounds on the probability of system failure. Techniques have been developed to enable SURE to solve models with loops and calculate the operational-state probabilities. The computation is extremely fast, and large state-spaces can be directly solved; a pruning technique enables SURE to process extremely large models     

An automated tissue preclassification approach for telepathology: implementation and performance analysis

Telepathology is generally defined as the use of telecommunications technologies in the practice of anatomic or surgical pathology. In the usual telepathology scenario, a remotely located pathologist views images of tissues samples in order to render a diagnosis of the biopsy. Some telepathology systems involve interactive remote control of a microscope-based imaging system which delivers diagnostic quality imagery to the remote pathologist. The usefulness of such interactive systems depends on minimizing the end-to-end delays involved in controlling the robotic microscope, manipulating the tissue sample, and acquiring and transmitting the high-resolution image. An approach to minimizing end-to-end delay involves adding "intelligence" to the image acquisition system so that it can gather, classify, rank, and transmit diagnostically useful images in a semiautonomous fashion. In this research, we develop image analysis and ranking techniques which can improve the end-to-end performance of a robotic telepathology imaging system. Our semiautonomous image collection system uses morphological techniques to extract seed points for suspicious regions, a novel region growing algorithm to segment the regions of interest, and heuristically motivated expert system ranking techniques to select diagnostically relevant "next-step" image acquisitions. Diagnostic relevance of our segmentation and ranking algorithms is established via subjective and objective testing of the system. In subjective testing, pathologists Agree or Strongly Agree that all segmented regions are diagnostically relevant with probability greater than 0.75. In objective testing, 84% of "next-step" images acquired by our algorithms coincide with the areas most likely to be chosen by a pathologist.     

A heterogeneous fault diagnosis approach to enhance performance of connected vehicles

Evolution of wireless access technology, availability of smart sensors, and reduction in the size of the set up of the communication system have engrossed many researchers toward vehicular ad hoc network (VANET). Vehicle-to-vehicle and vehicle-to-access-point communication in a vehicular environment facilitates the deployment of VANET for many different purposes. The success of any application implemented in a VANET relies on timely and accurate data dissemination across the nodes of the network. Implementation of any application is not going to be fruitful if the communication unit transmits incorrect sensor data due to the presence of a fault. This article focuses on the automatic detection of hard and soft faults for vehicular sensors and the classification of faults into permanent, intermittent, and transient faults using cloud-based VANET. For the cloud service, ThingSpeak cloud is used. At the RSU of the VANET, hard fault detection is performed, and for this purpose, a time-out strategy is proposed. The observation center, after receiving sensor status data over a vehicular cloud, does soft failure detection. The soft fault is identified by utilizing a comparative-based technique during soft fault diagnosis. Soft faults are categorized using two machine learning algorithms: Support vector machine and logistic regression. The effectiveness of the suggested work is assessed using performance metrics like fault detection accuracy, false alarm rate, false positive rate, precision, accuracy, recall, and F1 score.     

WLAN中TCP性能改进的跨层方案仿真

随着无线网络的迅速发展,如何改进TCP在无线网络中的传输性能这一课题,已经成为国内外研究的热点.文章分析了现有的几种典型的TCP改进方案,并在此基础上介绍一种新的跨层方案.通过在传输层和链路层之间引入ARQ Snoop代理,在链路层检测并重传ARQ分组的同时,协调WLAN MAC子层的ARQ机制与TCP的ARQ策略.     

一种提高哼唱匹配效果的新算法

在基于改进离散余弦变换的哼唱检索系统中，采用音高轮廓表示旋律，取原始歌曲中的一段为哼唱片段，使用字符串匹配法，分别在采样率为8kHz和44．1kHz的情况下进行匹配，分析了分帧起始位置对匹配效果的影响，并就此问题提出新算法。实验结果表明了该算法的有效性。