Electrical and Electronic Engineering - Research Publications

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    Dynamic scheduling algorithm for LTE uplink with smart-metering traffic
    Amarasekara, B ; Ranaweera, C ; Evans, R ; Nirmalathas, A (WILEY, 2017-10)
    Abstract Long‐term evolution (LTE) is a promising last mile access candidate technology for the smart‐metering communication architecture. However, when the mobile LTE network is used to support smart meters (SMs), the quality‐of‐service (QoS) requirements of the smart‐metering traffic as well as all the other typical mobile network traffic need to be ensured. This becomes problematic when the network users generate diverse traffic types that have different QoS requirements. Therefore, in this paper, we propose a dynamic bandwidth scheduling algorithm to ensure the required QoS of various traffic types arising from both SMs and mobile users. Our proposed dynamic bandwidth allocation algorithm integrates two schedulers that are designed for periodic and emergency SM traffic situations that have different SM traffic intensities and QoS requirements. Designing of two schedulers provides the advantages of leveraging the particular traffic characteristics of these two diverse operational situations and achieving the maximum use of resources to ensure QoS requirements. In addition, to alleviate potential problems created by simultaneous emergency SM traffic, we also propose a method that deploys a random delay for SM packet transmissions. We analyse the delay and packet drop ratio of diverse traffic types when both the LTE base station scheduler and the SMs deploy our proposed methods under either periodic or emergency SM traffic conditions in the smart grid. Our results show that our proposed mechanisms are capable of satisfying the QoS requirements of both mobile users and SMs under diverse traffic conditions.
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    Separation of Doppler radar-based respiratory signatures
    Lee, YS ; Pathirana, PN ; Evans, RJ ; Steinfort, CL (SPRINGER HEIDELBERG, 2016-08)
    Respiration detection using microwave Doppler radar has attracted significant interest primarily due to its unobtrusive form of measurement. With less preparation in comparison with attaching physical sensors on the body or wearing special clothing, Doppler radar for respiration detection and monitoring is particularly useful for long-term monitoring applications such as sleep studies (i.e. sleep apnoea, SIDS). However, motion artefacts and interference from multiple sources limit the widespread use and the scope of potential applications of this technique. Utilising the recent advances in independent component analysis (ICA) and multiple antenna configuration schemes, this work investigates the feasibility of decomposing respiratory signatures into each subject from the Doppler-based measurements. Experimental results demonstrated that FastICA is capable of separating two distinct respiratory signatures from two subjects adjacent to each other even in the presence of apnoea. In each test scenario, the separated respiratory patterns correlate closely to the reference respiration strap readings. The effectiveness of FastICA in dealing with the mixed Doppler radar respiration signals confirms its applicability in healthcare applications, especially in long-term home-based monitoring as it usually involves at least two people in the same environment (i.e. two people sleeping next to each other). Further, the use of FastICA to separate involuntary movements such as the arm swing from the respiratory signatures of a single subject was explored in a multiple antenna environment. The separated respiratory signal indeed demonstrated a high correlation with the measurements made by a respiratory strap used currently in clinical settings.
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    Stochastic S-system modeling of gene regulatory network
    Chowdhury, AR ; Chetty, M ; Evans, R (SPRINGER, 2015-10)
    Microarray gene expression data can provide insights into biological processes at a system-wide level and is commonly used for reverse engineering gene regulatory networks (GRN). Due to the amalgamation of noise from different sources, microarray expression profiles become inherently noisy leading to significant impact on the GRN reconstruction process. Microarray replicates (both biological and technical), generated to increase the reliability of data obtained under noisy conditions, have limited influence in enhancing the accuracy of reconstruction . Therefore, instead of the conventional GRN modeling approaches which are deterministic, stochastic techniques are becoming increasingly necessary for inferring GRN from noisy microarray data. In this paper, we propose a new stochastic GRN model by investigating incorporation of various standard noise measurements in the deterministic S-system model. Experimental evaluations performed for varying sizes of synthetic network, representing different stochastic processes, demonstrate the effect of noise on the accuracy of genetic network modeling and the significance of stochastic modeling for GRN reconstruction . The proposed stochastic model is subsequently applied to infer the regulations among genes in two real life networks: (1) the well-studied IRMA network, a real-life in-vivo synthetic network constructed within the Saccharomyces cerevisiae yeast, and (2) the SOS DNA repair network in Escherichia coli.
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    A Silk Fibroin Bio-Transient Solution Processable Memristor
    Yong, J ; Hassan, B ; Liang, Y ; Ganesan, K ; Rajasekharan, R ; Evans, R ; Egan, G ; Kavehei, O ; Li, J ; Chana, G ; Nasr, B ; Skafidas, E (NATURE PUBLISHING GROUP, 2017-11-07)
    Today's electronic devices are fabricated using highly toxic materials and processes which limits their applications in environmental sensing applications and mandates complex encapsulation methods in biological and medical applications. This paper proposes a fully resorbable high density bio-compatible and environmentally friendly solution processable memristive crossbar arrays using silk fibroin protein which demonstrated bipolar resistive switching ratio of 104 and possesses programmable device lifetime characteristics before the device gracefully bio-degrades, minimizing impact to environment or to the implanted host. Lactate dehydrogenase assays revealed no cytotoxicity on direct exposure to the fabricated device and support their environmentally friendly and biocompatible claims. Moreover, the correlation between the oxidation state of the cations and their tendency in forming conductive filaments with respect to different active electrode materials has been investigated. The experimental results and the numerical model based on electro-thermal effect shows a tight correspondence in predicting the memristive switching process with various combinations of electrodes which provides insight into the morphological changes of conductive filaments in the silk fibroin films.
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    Dynamics of Ebola epidemics in West Africa 2014.
    Evans, RJ ; Mammadov, M (F1000 Research Ltd, 2014)
    This paper investigates the dynamics of Ebola virus transmission in West Africa during 2014. The reproduction numbers for the total period of epidemic and for different consequent time intervals are estimated based on a simple linear model. It contains one major parameter - the average infectious period that defines the dynamics of epidemics. Numerical implementations are carried out on data collected from three countries Guinea, Sierra Leone and Liberia as well as the total data collected worldwide. Predictions are provided by considering different scenarios involving the average times of infectiousness for the next few months and the end of the current epidemic is estimated according to each scenario.
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    A tight binding and (k)over-right-arrow . (p)over-right-arrow study of monolayer stanene
    Jiang, L ; Marconcini, P ; Hossian, MS ; Qiu, W ; Evans, R ; Macucci, M ; Skafidas, E (NATURE PORTFOLIO, 2017-09-21)
    Stanene is a single layer of tin atoms which has been discovered as an emerging material for quantum spin Hall related applications. In this paper, we present an accurate tight-binding model for single layer stanene near the Fermi level. We parameterized the onsite and hopping energies for the nearest, second nearest, and third nearest neighbor tight-binding method, both without and with spin orbital coupling. We derived the analytical solution for the [Formula: see text]and [Formula: see text] points and numerically investigated the buckling effect on the material electronic properties. In these points of the reciprocal space, we also discuss a corresponding [Formula: see text] description, obtaining the value of the [Formula: see text] parameters both analytically from the tight-binding ones, and numerically, fitting the ab-initio dispersion relations. Our models provide a foundation for large scale atomistic device transport calculations.
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    An Information Analysis of Iterative Algorithms for Network Utility Maximization and Strategic Games
    Alpcan, T ; Nekouei, E ; Nair, GN ; Evans, RJ (IEEE, 2019)
    A variety of resource allocation problems on networked systems, for example, those in cyber-physical systems or Internet-of-things applications, require distributed solution methods. Modern distributed algorithms usually require bandwidth-limited digital communication between the system and its users, who are often modeled as independent decision makers with individual preferences. This paper presents a quantitative information flow and knowledge gain analysis of decentralized iterative algorithms with bounded trajectories in the context of convex network utility maximization problems and strategic games with a unique Nash equilibrium solution. First, a novel generic framework is introduced to quantify knowledge gain in network resource allocation problems using entropy by taking into account priors in the solution space. Second, a general result is presented on the interplay between quantization of information and distributed algorithm performance both for linear and sublinear convergence. Third, information flow in distributed algorithms is studied and a lower bound is derived on the total amount of information exchanged for convergence under uniform quantization. The well-known primal-dual decomposition algorithm is used as an example to illustrate the results. Finally, convergence guarantees for distributed algorithms with estimation are investigated. This paper establishes specific links between information concepts and iterative algorithms in addition to building a foundation for integrating learning schemes into distributed optimization.
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    Impact of quantized inter-agent communications on game-theoretic and distributed optimization algorithms
    Nekouei, E ; Alpcan, T ; Evans, RJ ; Başar, T (Springer, 2018-01-01)
    Quantized inter-agent communications in game-theoretic and distributed optimization algorithms generate uncertainty that affects the asymptotic and transient behavior of such algorithms. This chapter uses the information-theoretic notion of differential entropy power to establish universal bounds on the maximum exponential convergence rates of primal-dual and gradient-based Nash seeking algorithms under quantized communications. These bounds depend on the inter-agent data rate and the local behavior of the agents’ objective functions, and are independent of the quantizer structure. The presented results provide trade-offs between the speed of exponential convergence, the agents’ objective functions, the communication bit rates, and the number of agents and constraints. For the proposed Nash seeking algorithm, the transient performance is studied and an upper bound on the average time required to settle inside a specified ball around the Nash equilibrium is derived under uniform quantization. Furthermore, an upper bound on the probability that the agents’ actions lie outside this ball is established. This bound decays double exponentially with time.
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    Lower Bounds on the Best-Case Complexity of Solving a Class of Non-cooperative Games
    Nekouei, E ; Alpcan, T ; Nair, GN ; Evans, RJ (Elsevier, 2016)
    This paper studies the complexity of solving the class G of all N-player non-cooperative games with continuous action spaces that admit at least one Nash equilibrium (NE). We consider a distributed Nash seeking setting where agents communicate with a set of system nodes (SNs), over noisy communication channels, to obtain the required information for updating their actions. The complexity of solving games in the class G is defined as the minimum number of iterations required to find a NE of any game in G with ε accuracy. Using information-theoretic inequalities, we derive a lower bound on the complexity of solving the game class G that depends on the Kolmogorov 2ε-capacity of the constraint set and the total capacity of the communication channels. We also derive a lower bound on the complexity of solving games in G which depends on the volume and surface area of the constraint set.
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    Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences
    Skaria, S ; Al-Hourani, A ; Evans, RJ ; Sithamparanathan, K ; Parampalli, U (MDPI AG, 2019-10-15)
    The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.