1,720,958 research outputs found
Performance Modeling of Cognitive NOMA-aided IoT Networks with Energy Harvesting
No full textA research report submitted in fulfillment of the requirements for the Master of Science in Engineering, In the Faculty of Engineering and the Built Environment , School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, 2024In an attempt to address rocketed connectivity and bandwidth demands in 5G wireless networks, Non-Orthogonal Multiple Access (NOMA) and Cognitive Radio (CR) concepts have been proposed. The former addresses increased connectivity requirements by allowing multiple users in the same NOMA group to utilise the same channel resources. The latter enhances spectrum efficiency by intelligently al- lowing spectrum sharing between primary and secondary networks, if secondary to primary network interference is properly managed. To prolong connectivity/ser- vice life-time of battery capacity constrained Internet of Things (IoT) devices, Energy Harvesting (EH) technique has been identified as the technology that can enable such devices to harvest energy from ambient sources present in the envi- ronment. This research work is motivated by the observed surge in adoption of IoT devices around the globe. The resulting adoption has brought about the need to investigate performance of different IoT system models and hence, understand potential applicability and optimization options for different services. The focus of this dissertation is to model and analyse the performance of an EH Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) IoT network. To accomplish this, a simplified energy harvesting CR-NOMA IoT network is considered. The considered network consists of primary and secondary network components. The primary network contains Macro Base-Station (MBS) and Pri- mary Network users (PUs), while the secondary network is made up of Secondary Base-Station (SBS) and multiple CR-NOMA groups containing two Secondary Users (SUs) each. To analytically capture the stochastic nature of energy harvest- ing process and cater for residual energy from one transmission frame to the next, each SU’s energy level in the battery is discretized to represent the state of each SU during each transmission frame; with this, we derive a complete Markovian model for the considered system model using queueing theory and Markovian analysis. Two Markovian models are developed for the considered system model, with one assuming that the SUs are harvesting energy from the SBS (one energy source) and the other, adopting an assumption that energy is harvested from both the SBS and MBS (two energy sources). The considered system performance is analysed in terms of up-link system outage probability and mean capacity. To provide detailed insights, closed-form analytical expressions for up-link outage probability and mean capacity for each user in the CR-NOMA group are derived using the Markovian models as the ba- sis. Produced analytical results are confirmed through simulations using Matlab. Simulation results matched the analytical results, this confirmed the validity of the derived analytical expressions for SUs outage probability and mean capacity. ii Both performance metrics are studied and the impact of varying different network parameters on outage probability and mean capacity is investigated. For out- age probability, results are generated which demonstrate SUs outage performance as we vary Signal-to-Interference-plus-Noise Ratio (SINR), interference threshold, and battery power level. Similarly, mean capacity results are generated to illus- trate each SU mean capacity performance while varying their battery levels, this is done for different values of primary transmit power and interference threshold. Performance results observed as different parameters are varied for outage prob- ability and mean capacity align with the theoretical performance expected when those parameters are changed. The significance of this work lies in providing ana- lytical tools to assess the performance of the CR-NOMA IoT system with energy harvesting (EH). These tools enable easy computation of system performance in- dicators such as outage performance and mean capacity. Attempting the same assessment through simulation would be a cumbersome process.MM202
Channel assembling and resource allocation in multichannel spectrum sharing wireless networks
Get PDFSubmitted in fulfilment of the academic requirements for the degree of
Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and
Information Engineering, Faculty of Engineering and the Built Environment,
at the University of the Witwatersrand, Johannesburg, South Africa, 2017The continuous evolution of wireless communications technologies has increasingly imposed a
burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications
and services, the radio spectrum is getting saturated and becoming a limited resource. To a large
extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies,
rather than of the physical shortage of radio frequencies. The conventional static spectrum
allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive
radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum
access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use.
However, provisioning of reliable and robust communication with seamless operation in cognitive
radio networks (CRNs) is a challenging task. The underlying challenges include development of
non-intrusive dynamic resource allocation (DRA) and optimization techniques.
The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA
schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without
degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives
are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to
develop analytical models for quantifying performance of ChA schemes over fading channels in
overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay
architectures, subject to power control and interference mitigation; and finally, to extend the
adaptive ChA and DRA schemes for multiuser multichannel access CRNs.
Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through
extensive simulations and analytical models. Further, the cross validation has been performed
between simulations and analytical results to confirm the accuracy and preciseness of the novel
analytical models developed in this thesis. In general, the presented results demonstrate improved
performance of SU nodes in terms of capacity, collision probability, outage probability and forced
termination probability when employing the adaptive ChA and DRA in CRNs.CK201
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Task Offloading and Computation in Hybrid uRLLC and eMBB Cognitive Radio Enabled 5G Based Multiuser Edge Computing
No full textVariations on the Author
Get PDF“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
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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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