1,721,413 research outputs found
Multi stage Kalman filter (MSKF) based time-varying sparse channel estimation with fast convergence
Static Human Position Classification from Indoor mmWave Radio RSSI Measurements
With the rapid development of millimeter wave (mmWave) wireless systems, there is an increasing demand for joint communications and sensing solutions. Indoor human position estimation using wireless fidelity (WiFi) radios may be helpful to provide beyond communication applications such as e-Health, smart buildings, human tracking, etc. under sixth generation (6G) wireless systems. Moreover, WiFi sensing in-formation has the potential to improve communication itself. In the literature, the received signal strength indicator (RSSI)-based methods have been studied but with coarse results due to the usage of omnidirectional antennas. Recent WiFi sensing approaches employ vendor-specific channel state information (CSI) to obtain reliable indoor positioning. In this work, we propose a feed-forward neural network (FNN)-based indoor position estimation framework using RSSI measurements from indoor radio beamforming communication procedure. The acquired RSSI characteristic information from the exhaustive mmWave beam selection process serves as distinctive fingerprints to estimate indoor static human positions. We construct a dataset with obtained RSSI fingerprints for subject positions along LoS, nLoS, and the empty room environment. We obtain a position estimation model using FNN and the dataset. Our results show that the FNN-based framework predicts indoor static human positions using RSSI measurements at an Fl-score of 0.86 and accuracy of 0.95. Moreover, the model from such a framework is also robust to distinguish symmetric static positions with respect to the LoS link during mm Wave communication.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Multiterminal Source-Channel Coding
Cooperative communication is seen as a key concept to achieve ultra-reliable communication in upcoming fifth-generation mobile networks (5G). A promising cooperative communication concept is multiterminal source-channel coding, which attracted recent attention in the research community.
This thesis lays theoretical foundations for understanding the performance of multiterminal source-channel codes in a vast variety of cooperative communication networks. To this end, we decouple the multiterminal source-channel code into a multiterminal source code and multiple point-to-point channel codes. This way, we are able to adjust the multiterminal source code to any cooperative communication network without modification of the channel codes. We analyse the performance in terms of the outage probability in two steps: at first, we evaluate the instantaneous performance of the multiterminal source-channel codes for fixed channel realizations; and secondly, we average the instantaneous performance over the fading process. Based on the performance analysis, we evaluate the performance of multiterminal source-channel codes in three cooperative communication networks, namely relay, wireless sensor, and multi-connectivity networks. For all three networks, we identify the corresponding multiterminal source code and analyse its performance by the rate region for binary memoryless sources. Based on the rate region, we derive the outage probability for additive white Gaussian noise channels with quasi-static Rayleigh fading. We find results for the exact outage probability in integral form and closed-form solutions for the asymptotic outage probability at high signal-to-noise ratio.
The importance of our results is fourfold: (i) we give the ultimate performance limits of the cooperative communication networks under investigation; (ii) the optimality of practical schemes can be evaluated with respect to our results, (iii) our results are suitable for link-level abstraction which reduces complexity in network-level simulation; and (iv) our results demonstrate that all three cooperative communication networks are key technologies to enable 5G applications, such as device to device and machine to machine communications, internet of things, and internet of vehicles.
In addition, we evaluate the performance improvement of multiterminal source-channel codes over other (non-)cooperative communications concepts in terms of the transmit power reduction given a certain outage probability level. Moreover, we compare our theoretical results to simulated frame-error-rates of practical coding schemes. Our results manifest the superiority of multiterminal source-channel codes over other (non-)cooperative communications concepts
Concentrated signal extraction using consecutive mean excision algorithms
AbstractSpread spectrum communication systems may be affected by other types of signals called outliers. These coexisting signals are typically narrow (or concentrated) in the considered domain. This thesis considers two areas of outlier detection, namely the concentrated interference suppression (IS) and concentrated signal detection. The focus is on concentrated signal extraction using blind, iterative and low-complex consecutive mean excision (CME) -based algorithms that can be applied to both IS and detection. A summary of results obtained from studying the performance of the existing IS methods, namely the CME, the forward CME (FCME) and the transform selective IS algorithms (TSISA), is presented. Accurate threshold parameter values for the FCME algorithm are defined. These accurate values are able to control the false alarm rate. The signal detection capability of the CME algorithms is studied and analyzed. It is noticed that the CME algorithms are able to detect signals, but they are not able to estimate signal parameters such as the bandwidth. The presented generic shape-based analysis leads to the limits of detection in which the concentrated signals can be detected. These limits enable checking fast whether the signal is detectable or not without time consuming computer simulations. The performance of the TSISA method is evaluated. Simulation results demonstrate that the TSISA method is able to suppress several types of concentrated interfering signals with a reasonable computational complexity. Finally, new CME-based methods are proposed and evaluated. The proposed methods are the extended TSISA method for IS and the localization algorithm based on double-thresholding (LAD), LAD with normalized thresholds (LAD NT), LAD with adjacent cluster combining (LAD ACC) and two-dimensional (2-D) LAD methods for detection. The simulations indicate that the extended TSISA method has a good performance against several types of concentrated interfering signals. The narrowband signal detection capability of the LAD methods is studied. Numerical results show that the proposed LAD methods are able to detect and localize signals in their domain, and they are able to estimate the number of narrowband signals and their parameters, including, for example, bandwidths and signal-to-noise ratio (SNR) values. The simulations show that the LAD methods outperform the CME algorithms, and ACC and 2-D LAD methods outperform the original LAD method. The LAD methods are also proposed to be used for spectrum sensing purposes in cognitive radios. Academic dissertation to be presented with the assent of the Faculty of Technology of the University of Oulu for public defence in OP-sali (Auditorium L10), Linnanmaa, on 19 November 2010, at 12 noonAbstract
Spread spectrum communication systems may be affected by other types of signals called outliers. These coexisting signals are typically narrow (or concentrated) in the considered domain. This thesis considers two areas of outlier detection, namely the concentrated interference suppression (IS) and concentrated signal detection. The focus is on concentrated signal extraction using blind, iterative and low-complex consecutive mean excision (CME) -based algorithms that can be applied to both IS and detection.
A summary of results obtained from studying the performance of the existing IS methods, namely the CME, the forward CME (FCME) and the transform selective IS algorithms (TSISA), is presented. Accurate threshold parameter values for the FCME algorithm are defined. These accurate values are able to control the false alarm rate. The signal detection capability of the CME algorithms is studied and analyzed. It is noticed that the CME algorithms are able to detect signals, but they are not able to estimate signal parameters such as the bandwidth. The presented generic shape-based analysis leads to the limits of detection in which the concentrated signals can be detected. These limits enable checking fast whether the signal is detectable or not without time consuming computer simulations. The performance of the TSISA method is evaluated. Simulation results demonstrate that the TSISA method is able to suppress several types of concentrated interfering signals with a reasonable computational complexity.
Finally, new CME-based methods are proposed and evaluated. The proposed methods are the extended TSISA method for IS and the localization algorithm based on double-thresholding (LAD), LAD with normalized thresholds (LAD NT), LAD with adjacent cluster combining (LAD ACC) and two-dimensional (2-D) LAD methods for detection. The simulations indicate that the extended TSISA method has a good performance against several types of concentrated interfering signals. The narrowband signal detection capability of the LAD methods is studied. Numerical results show that the proposed LAD methods are able to detect and localize signals in their domain, and they are able to estimate the number of narrowband signals and their parameters, including, for example, bandwidths and signal-to-noise ratio (SNR) values. The simulations show that the LAD methods outperform the CME algorithms, and ACC and 2-D LAD methods outperform the original LAD method. The LAD methods are also proposed to be used for spectrum sensing purposes in cognitive radios
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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