1,721,112 research outputs found
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Full text linkThe upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications, and cell-free communications – to name a few. Our vision for 6G is – a massively connected complex network capable of rapidly responding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state-of-the-art in the domains of ML (including deep learning), QC and QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network-infrastructure, network-edge, air interface, and user-end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed
Effect of primary user traffic on largest eigenvalue based spectrum sensing technique
Full text linkIn this paper, the effect of primary user (PU) traffic on the performance of largest eigenvalue based spectrum sensing technique (Roy's Largest Root Test (RLRT)) is investigated. A simple and realistic discrete time modeling of PU traffic is considered which is only based on the discrete time distribution of PU free and busy periods. Furthermore, in order to analyze the effect of PU traffic on the detection performance, analytical expressions for the probability density functions of the decision statistic are derived and validated by Monte-Carlo simulations. Numerical results demonstrate that the sensing performance of RLRT is no more monotonically increasing with the length of the sensing duration and also with SNR which contrasts with the common property of the spectrum sensing techniques under known PU traffic scenario. Furthermore, it is shown that the performance gain due to the multiple antennas in the sensing unit is significantly suppressed by the effect of the PU traffic when the frequency of the PU traffic transitions is highe
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Design and Optimization of Ultra-Reliable Low-Latency Communications in Beyond 5G Networks
Full text linkThe fifth generation (5G) and beyond wireless networks mark a pivotal shift in the realm of telecommunications. These advanced networks aim to provide an array of different services, fulfilling the diverse needs of modern-day connectivity. They are expected to provide services with high data rates, large connection density, ultra-low latency, and extraordinary reliability. To achieve these goals, there are three primary service categories in 5G and beyond networks: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). With eMBB, users can communicate with a substantial increase in data rates, enabling swift and high-bandwidth content consumption. On the other hand, mMTC sets the stage for the seamless integration of billions of devices into the network. However, it's URLLC that stands out as the linchpin of these networks, providing unprecedented levels of reliability and ultra-low latency, considering mission-critical applications and real-time responsiveness as the norm. This service is expected to open groundbreaking changes in fields such as healthcare, autonomous vehicles, industrial automation, and beyond. Given the above context, this dissertation focuses on designing effective communication protocols for different URLLC-related systems. In particular, the study delves into three key aspects: (1) Average block error rate (BLER) and minimum blocklength analysis for short-packet communications, a promising transmission method for URLLC; (2) Deep reinforcement learning (DRL)-based resource management strategy for uplink URLLC within the context of grant-free access, an advanced access technology for latency-sensitive dense networks; and (3) Joint optimization and DRL-based resource allocation for harmonious coexistence of diverse services such as eMBB, mMTC, and URLLC. Firstly, we study a promising transmission method for URLLC, namely short packet communications (SPC), to fulfill its stringent requirements. Specifically, we investigate SPC in downlink non-orthogonal multiple access (NOMA) systems using multiple-input multiple-output (MIMO) schemes. The main focus of this work is a comprehensive evaluation of system performance by analyzing the average block error rate (BLER) and minimizing the blocklength to reduce transmission latency. Our findings reveal that MIMO NOMA exhibits the capability to efficiently serve multiple users in a concurrent fashion while employing a lower blocklength in comparison with MIMO Orthogonal Multiple Access (OMA). These results effectively highlight the advantages of MIMO NOMA-based SPC, primarily in its ability to significantly reduce transmission latency. Secondly, we investigate the application of DRL techniques for designing highly efficient resource management solutions in grant-free NOMA (GF-NOMA) systems tailored to meet the stringent demands of URLLC. Our focus centers on maximizing network energy efficiency (EE) and ensuring the fulfillment of URLLC users' specific requirements. The outcomes of our simulations demonstrate that the methods we propose achieve better convergence properties, smaller signaling overhead, and larger network EE than other benchmark methods. Finally, our focus turns to the seamless combination of diverse services including eMBB, mMTC, and URLLC in NOMA-based systems. In this context, we develop an innovative resource management solution applying a joint optimization and cooperative multi-agent DRL approach. The primary goal of this strategy is to maximize network EE for the considered system while adhering to users' diverse demands. Our extensive simulations indicate that our proposed method provides superior performance regarding convergence property and system EE over other considered benchmark methods.R-AGR-3732 - C19/IS/13713801/5G-Sky (01/06/2020 - 31/05/2023) - OTTERSTEN Björ
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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