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  • Conference paper
    Gebru ID, Evers C, Naylor PA, Horaud Ret al., 2017,

    Audio-visual tracking by density approximation in a sequential Bayesian filtering framework

    , HSCMA 2017, Publisher: IEEE, Pages: 71-75

    This paper proposes a novel audio-visual tracking approach that exploits constructively audio and visual modalities in order to estimate trajectories of multiple people in a joint state space. The tracking problem is modeled using a sequential Bayesian filtering framework. Within this framework, we propose to represent the posterior density with a Gaussian Mixture Model (GMM). To ensure that a GMM representation can be retained sequentially over time, the predictive density is approximated by a GMM using the Unscented Transform. While a density interpolation technique is introduced to obtain a continuous representation of the observation likelihood, which is also a GMM. Furthermore, to prevent the number of mixtures from growing exponentially over time, a density approximation based on the Expectation Maximization (EM) algorithm is applied, resulting in a compact GMM representation of the posterior density. Recordings using a camcorder and microphone array are used to evaluate the proposed approach, demonstrating significant improvements in tracking performance of the proposed audio-visual approach compared to two benchmark visual trackers.

  • Journal article
    Doire CSJ, Brookes DM, Naylor PA, 2017,

    Robust and efficient Bayesian adaptive psychometric function estimation

    , Journal of the Acoustical Society of America, Vol: 141, Pages: 2501-2512, ISSN: 0001-4966

    The efficient measurement of the threshold and slope of the psychometric function (PF) is an important objective in psychoacoustics. This paper proposes a procedure that combines a Bayesian estimate of the PF with either a look one-ahead or a look two-ahead method of selecting the next stimulus presentation. The procedure differs from previously proposed algorithms in two respects: (i) it does not require the range of possible PF parameters to be specified in advance and (ii) the sequence of probe signal-to-noise ratios optimizes the threshold and slope estimates at a performance level, ϕ, that can be chosen by the experimenter. Simulation results show that the proposed procedure is robust and that the estimates of both threshold and slope have a consistently low bias. Over a wide range of listener PF parameters, the root-mean-square errors after 50 trials were ∼1.2 dB in threshold and 0.14 in log-slope. It was found that the performance differences between the look one-ahead and look two-ahead methods were negligible and that an entropy-based criterion for selecting the next stimulus was preferred to a variance-based criterion.

  • Journal article
    Kamil Y, Manikas A, 2017,

    Multisource spatiotemporal tracking using sparse large aperture arrays

    , IEEE Transactions on Aerospace and Electronic Systems, Vol: 53, Pages: 837-853, ISSN: 0018-9251

    In this paper, a multisource tracking technique is proposed using a sparse large aperture array of passive sensors of known geometry. First, a novel spherical-spatiotemporal-state-space model is introduced incorporating target ranges, directions, and Doppler effects in conjunction with the array geometry. Subsequently, this array of sensors is integrated with an extended Kalman filter (EKF), defined as the arrayed EKF, to track the trajectory of multiple mobile sources. In addition, a recursive lower bound on the performance of the proposed tracking method is obtained based on the posterior Cramer-Rao bound. Computer simulation studies show that the proposed approach can track the locations of sources, as these move in space, with a very high accuracy.

  • Journal article
    Wang S, Urgaonkar R, He T, Chan K, Zafer M, Leung KKet al., 2017,

    Dynamic service placement for mobile micro-clouds with predicted future costs

    , IEEE Transactions on Parallel and Distributed Systems, Vol: 28, Pages: 1002-1016, ISSN: 1045-9219

    Mobile micro-clouds are promising for enabling performance-critical cloud applications. However, one challenge therein is the dynamics at the network edge. In this paper, we study how to place service instances to cope with these dynamics, where multiple users and service instances coexist in the system. Our goal is to find the optimal placement (configuration) of instances to minimize the average cost overtime, leveraging the ability of predicting future cost parameters with known accuracy. We first propose an offline algorithm that solves for the optimal configuration in a specific look-ahead time-window. Then, we propose an online approximation algorithm with polynomial time-complexity to find the placement in real-time whenever an instance arrives. We analytically show that the online algorithm is 0(1)-competitive for a broad family of cost functions. Afterwards, the impact of prediction errors is considered and a method for finding the optimal look-ahead window size is proposed, which minimizes an upper bound of the average actual cost. The effectiveness of the proposed approach is evaluated by simulations with both synthetic and real-world (San Francisco taxi) usermobility traces. The theoretical methodology used in this paper can potentially be applied to a larger class of dynamic resource allocation problems.

  • Conference paper
    Rossi G, Leung KK, 2017,

    Optimised CSMA protocol to support efficient clustering for vehicular internetworking

    , IEEE Wireless Communications and Networking Conference (WCNC) 2017, Publisher: IEEE

    Vehicular ad-hoc networks (VANETs) that supportcommunication among vehicles can facilitate a wide range ofroad-safety applications. To deal with network fragmentationfor low vehicular density, clusters of neighbouring vehicles canbe formed. Clustering techniques also require timely commu-nications among vehicles. Despite the stringent performancerequirements for the safety and clustering applications, theIEEE 802.11p standard still employs the carrier sensing mediumaccess/collision avoidance (CSMA/CA) protocol that has a fixedcontention window (CW) range for backoff. This results insignificant inefficiency as vehicular density changes. This workinvestigates how the maximum CW size can be optimised toenhance performance based on vehicular density by exploitingthe equivalence between the CSMA/CA and Aloha performancemodels. Simulation shows a great reduction in transmission delayfor the proposed protocol when compared with the standardisedone. Thus, with the low latency, the new protocol is useful to thevehicle clustering and road-safety applications.

  • Journal article
    Xia Y, He Y, Wang K, Pei W, Blazic Z, Mandic DPet al., 2017,

    A Complex Least Squares Enhanced Smart DFT Technique for Power System Frequency Estimation

    , IEEE TRANSACTIONS ON POWER DELIVERY, Vol: 32, Pages: 1270-1278, ISSN: 0885-8977
  • Journal article
    Clerckx B, 2017,

    Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks with Multi-Antenna Base Stations

    , IEEE Transactions on Wireless Communications, Vol: 16, Pages: 2760-2775, ISSN: 1558-2248

    In order to improve the uplink performance offuture cellular networks, the idea to decouple the downlink (DL)and uplink (UL) association has recently been shown to providesignificant gain in terms of both coverage and rate performance.However, all the work is limited to SISO network. Therefore,to study the gain provided by the DL and UL decoupling inmulti-antenna base stations (BSs) setup, we study a two tierheterogeneous network consisting of multi-antenna BSs, andsingle antenna user equipments (UEs). We use maximal ratiocombining (MRC) as a linear receiver at the BSs and using toolsfrom stochastic geometry, we derive tractable expressions forboth signal to interference ratio (SIR) coverage probability andrate coverage probability. We observe that as the disparity inthe beamforming gain of both tiers increases, the gain in term ofSIR coverage probability provided by the decoupled associationover non-decoupled association decreases. We further observethat when there is asymmetry in the number of antennas of bothtier, then we need further biasing towards femto-tier on the topof decoupled association to balance the load and get optimal ratecoverage probability.

  • Journal article
    Ma Z, Dai W, Liu Y, Wang Xet al., 2017,

    Group Sparse Bayesian Learning Via Exact and Fast Marginal Likelihood Maximization

    , IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 65, Pages: 2741-2753, ISSN: 1053-587X
  • Conference paper
    Pinero G, Naylor PA, 2017,

    CHANNEL ESTIMATION FOR CROSSTALK CANCELLATION IN WlRELESS ACOUSTIC NETWORKS

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 586-590, ISSN: 1520-6149
  • Conference paper
    Javed HA, Cauchi B, Doclo S, Naylor PA, Goetze Set al., 2017,

    MEASURING, MODELLING AND PREDICTING PERCEIVED REVERBERATION

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 381-385, ISSN: 1520-6149
  • Conference paper
    Murray-Bruce J, Dragotti PL, 2017,

    Solving Inverse Source Problems for linear PDEs using Sparse Sensor Measurements

    , 50th Asilomar Conference on Signals, Systems, and Computers (ASILOMARSSC), Publisher: IEEE, Pages: 517-521, ISSN: 1058-6393

    Many physical phenomena across several applications can be described by partial differential equations (PDEs). In these applications, sensors collect sparse samples of the resulting phenomena with the aim of detecting its cause/source, using some intelligent data analysis tools on the samples. These problems are commonly referred to as inverse source problems. This work presents a novel framework for solving such inverse source problem for linear PDEs by drawing from certain recent results in modern sampling theory. Under the new framework, we study the well-known diffusion PDE and present numerical results that highlight the validity and robustness of the approach.

  • Conference paper
    Piovano E, Joudeh H, Clerckx B, 2017,

    Overloaded multiuser MISO transmission with imperfect CSIT

    , 50th Asilomar Conference on Signals, Systems and Computers, Publisher: IEEE

    A required feature for the next generation of wireless communication networks will be the capability to serve simultaneously a large number of devices with heterogeneous CSIT qualities and demands. In this paper, we consider the overloaded MISO BC with two groups of CSIT qualities. We propose a transmission scheme where degraded symbols are superimposed on top of spatially-multiplexed symbols. The developed strategy allows to serve all users in a non-orthogonal manner and the analysis shows an enhanced performance compared to existing schemes. Moreover, optimality in a DoF sense is shown.

  • Conference paper
    Douglas SC, Mandic DP, 2017,

    SINGLE-CHANNEL WIENER FILTERING OF DETERMINISTIC SIGNALS IN STOCHASTIC NOISE USING THE PANORAMA

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4182-4186, ISSN: 1520-6149
  • Conference paper
    Stott AE, Kanna S, Mandic DP, Pike WTet al., 2017,

    AN ONLINE NIPALS ALGORITHM FOR PARTIAL LEAST SQUARES

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4177-4181, ISSN: 1520-6149
  • Conference paper
    Wei X, Dragotti PL, 2017,

    MODEL ORDER SELECTION FOR SAMPLING FRI SIGNALS

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4556-4560, ISSN: 1520-6149
  • Conference paper
    Talebi SP, Kanna S, Xia Y, Mandic DPet al., 2017,

    COST-EFFECTIVE DIFFUSION KALMAN FILTERING WITH IMPLICIT MEASUREMENT EXCHANGES

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4411-4415, ISSN: 1520-6149
  • Conference paper
    Huang J-J, Dragotti PL, 2017,

    PROSPARSE EXTENSION: PRONY'S BASED SPARSE PATTERN RECOVERY WITH EXTENDED DICTIONARIES

    , IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3819-3823, ISSN: 1520-6149
  • Conference paper
    Liu T, Stathaki T, 2017,

    Fast Head-Shoulder Proposal for Deformable Part Model based Pedestrian Detection

    , International Conference on Digital Signal Processing, Publisher: IEEE, Pages: 457-461, ISSN: 2165-3577

    In this paper we propose a fast head-shoulder detector as a means to facilitating faster pedestrian detection. The proposed approach is based on the observation that human head-shoulder regions share relatively robust features. The purpose is to address the problem of high computational speed of the deformable part model (DPM) detector by selecting candidate regions with higher likelihood to contain pedestrians. The proposed head-shoulder detector is based on the simple, yet effective normed gradient features. Head-shoulder detector outputs regions which are strong candidates for the presence of pedestrians and therefore, pedestrian detection processes are performed only within these regions, avoiding exhaustive sliding window search across the entire test image. Additionally, a two-pedestrian detector is applied to reinforce the detection accuracy especially in scenarios where pedestrians are close to each other. Our experiments on the INRIA dataset indicate that the proposed pedestrian detection method achieves comparable detection rate to the DPM detector, with improved speed of implementation.

  • Journal article
    Clerckx B, 2017,

    Communications and Signals Design for Wireless Power Transmission

    , IEEE Transactions on Communications, Vol: 65, Pages: 2264-2290, ISSN: 1558-0857

    Radiative wireless power transfer (WPT) is a promising technology to provide cost-effective and real-time power supplies to wireless devices. Although radiative WPT shares many similar characteristics with the extensively studied wireless information transfer or communication, they also differ significantly in terms of design objectives, transmitter/receiver architectures and hardware constraints, and so on. In this paper, we first give an overview on the various WPT technologies, the historical development of the radiative WPT technology and the main challenges in designing contemporary radiative WPT systems. Then, we focus on the state-of-the-art communication and signal processing techniques that can be applied to tackle these challenges. Topics discussed include energy harvester modeling, energy beamforming for WPT, channel acquisition, power region characterization in multi-user WPT, waveform design with linear and non-linear energy receiver model, safety and health issues of WPT, massive multiple-input multiple-output and millimeter wave enabled WPT, wireless charging control, and wireless power and communication systems co-design. We also point out directions that are promising for future research.

  • Journal article
    Stathaki P, Konstantinidis D, Argyriou V, Grammalidis Net al., 2017,

    Building detection using enhanced HOG-LBP features and region refinement processes

    , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol: 10, Pages: 888-905, ISSN: 1939-1404

    Building detection from two-dimensional high-resolution satellite images is a computer vision, photogrammetry, and remote sensing task that has arisen in the last decades with the advances in sensors technology and can be utilized in several applications that require the creation of urban maps or the study of urban changes. However, the variety of irrelevant objects that appear in an urban environment and resemble buildings, and the significant variations in the shape and generally the appearance of buildings render building detection a quite demanding task. As a result, automated methods that can robustly detect buildings in satellite images are necessary. To this end, we propose a building detection method that consists of two modules. The first module is a feature detector that extracts histograms of oriented gradients (HOG) and local binary patterns (LBP) from image regions. Using a novel approach, a support vector machine classifier is trained with the introduction of a special denoising distance measure for the computation of distances between HOG-LBP descriptors before their classification to the building or nonbuilding class. The second module consists of a set of region refinement processes that employs the output of the HOG-LBP detector in the form of detected rectangular image regions. Image segmentation is performed and a novel building recognition methodology is proposed to accurately identify building regions, while simultaneously discard false detections of the first module of the proposed method. We demonstrate that the proposed methodology can robustly detect buildings from satellite images and outperforms state-of-the-art building detection methods.

  • Journal article
    Li Z, Xia Y, Pei W, Wang K, Huang Y, Mandic DPet al., 2017,

    Noncircular Measurement and Mitigation of I/Q Imbalance for OFDM-Based WLAN Transmitters

    , IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 66, Pages: 383-393, ISSN: 0018-9456
  • Journal article
    Doire CSJ, Brookes DM, Naylor PA, Hicks CM, Betts D, Dmour MA, Jensen SHet al., 2017,

    Single-channel online enhancement of speech corrupted by reverberation and noise

    , IEEE/ACM Transactions on Audio, Speech and Language Processing, Vol: 25, Pages: 572-587, ISSN: 2329-9290

    This paper proposes an online single-channel speech enhancement method designed to improve the quality of speech degraded by reverberation and noise. Based on an autoregressive model for the reverberation power and on a hidden Markov model for clean speech production, a Bayesian filtering formulation of the problem is derived and online joint estimation of the acoustic parameters and mean speech, reverberation, and noise powers is obtained in mel-frequency bands. From these estimates, a real-valued spectral gain is derived and spectral enhancement is applied in the short-time Fourier transform (STFT) domain. The method yields state-of-the-art performance and greatly reduces the effects of reverberation and noise while improving speech quality and preserving speech intelligibility in challenging acoustic environments.

  • Conference paper
    Venieris E, Manikas A, 2017,

    Near-far field multipath spatial-temporal localisation

    , IEEE International Conference on Communications 2017, Publisher: Institute of Electrical and Electronics Engineers, ISSN: 0536-1486

    In this paper, a passive array processing algorithm isproposed for localising the near-far field multipaths of the desiredsignal in the presence of co-channel interference. By expressingthe unknown path delay as a function of the path’s range,the proposed spatiotemporal localisation algorithm estimates thelocations of all the multipath reflectors of the desired signalsource using a subspace-type cost function. The performance ofthe proposed algorithm is evaluated through computer simulationstudies.

  • Journal article
    Parada PP, Sharma D, van Waterschoot T, Naylor PAet al., 2017,

    Confidence Measures for Nonintrusive Estimation of Speech Clarity Index

    , JOURNAL OF THE AUDIO ENGINEERING SOCIETY, Vol: 65, Pages: 90-99, ISSN: 1549-4950
  • Conference paper
    Sridhar V, Manikas A, 2017,

    Target Tracking with a Flexible UAV Cluster Array

    , IEEE GLOBECOM 2016, Publisher: IEEE

    Unmanned aerial vehicle (UAV) cluster applications,for tasks such as target localisation and tracking, are required tocollect and utilise the data received on “flexible” sensor arrays,where the sensors, i.e. UAVs in this scenario, have time-variantpositions. In this paper, using a parametric channel model, a UAVcluster mobility model and a kinematic model of the targets, anextended Kalman based state space model is proposed that tracksthe unknown UAV positions and target parameters snapshot bysnapshot. Simulation studies illustrating the tracking capabilitiesof the proposed technique have been presented.

  • Journal article
    Wang S, Zafer M, Leung KK, 2017,

    Online placement of multi-component applications in edge computing environments

    , IEEE Access, Vol: 5, Pages: 2514-2533, ISSN: 2169-3536

    Mobile edge computing is a new cloud computingparadigm which makes use of small-sized edge-clouds to providereal-time services to users. These mobile edge-clouds (MECs)are located in close proximity to users, thus enabling users toseamlessly access applications running on MECs. Due to the coexistenceof the core (centralized) cloud, users, and one or multiplelayers of MECs, an important problem is to decide where (onwhich computational entity) to place different components of anapplication. This problem, known as the application or workloadplacement problem, is notoriously hard, and therefore, heuristicalgorithms without performance guarantees are generallyemployed in common practice, which may unknowingly sufferfrom poor performance as compared to the optimal solution.In this paper, we address the application placement problemand focus on developing algorithms with provable performancebounds. We model the user application as an application graphand the physical computing system as a physical graph, withresource demands/availabilities annotated on these graphs. Wefirst consider the placement of a linear application graph andpropose an algorithm for finding its optimal solution. Using thisresult, we then generalize the formulation and obtain onlineapproximation algorithms with polynomial-logarithmic (poly-log)competitive ratio for tree application graph placement.We jointlyconsider node and link assignment, and incorporate multipletypes of computational resources at nodes.

  • Conference paper
    Fang Z, Manikas A, 2017,

    DOA and Range Estimation of Multiple Sources Under the Wideband Assumption

    , IEEE GLOBECOM 2016, Publisher: Institute of Electrical and Electronics Engineers (IEEE), ISSN: 0895-1195

    In this paper, two novel channel parameter estimationalgorithms are proposed under the “wideband assumption,”where a wavefront varies significantly when traversing throughthe sensors of the array. The first covariance-based approachutilizes the cross-covariance matrix between two subvectors of thereceived signal vector and the singular value decomposition to reconstructthe parameter-dependent signal subspace. Meanwhile,the second reference-based approach employs the rotation of thearray reference point so that the estimation techniques underthe “narrowband assumption” are readily applicable. Throughcomputer simulation studies, the two proposed approaches areshown to successfully estimate the channel parameters under thewideband assumption with outstanding accuracy in terms of theestimation root mean squared error

  • Conference paper
    Fang Z, Manikas A, 2017,

    Arrayed space optical communications: localization of the ground station

    , IEEE International Conference on Communications (ICC), Publisher: IEEE

    In this paper, a novel ground station localizationalgorithm is proposed for space optical communications using ar-ray processing and a set of celestial objects of known locations inthe global coordinate system. First, the ground station estimatesthe directions of this set of celestial objects relative to its localcoordinate system using the sunlight reflected by these celestialobjects. Then, the ranges of the celestial objects and the locationand orientation of the ground station are estimated by solvingsystems of nonlinear and linear equations. The performance ofthe proposed approach is assessed through computer simulationstudies. It is shown to estimate the location and orientation ofthe ground station successfully with excellent accuracy.

  • Conference paper
    Evers C, Rafaely B, Naylor PA, 2017,

    Speaker tracking in reverberant environments using multiple detections of arrival

    , HSCMA 2017, Publisher: IEEE

    Accurate estimation of the Direction of Arrival (DOA) of a soundsource is an important prerequisite for a wide range of acoustic sig-nal processing applications. However, in enclosed environments,early reflections and late reverberation often lead to localization er-rors. Recent work demonstrated that improved robustness againstreverberation can be achieved by clustering only the DOAs fromdirect-path bins in the short-term Fourier transform of a speech sig-nal of several seconds duration from a static talker. Nevertheless, formoving talkers, short blocks of at most several hundred millisecondsare required to capture the spatio-temporal variation of the sourcedirection. Processing of short blocks of data in reverberant envi-ronment can lead to clusters whose centroids correspond to spuri-ous DOAs away from the source direction. We therefore propose inthis paper a novel multi-detection source tracking approach that es-timates the smoothed trajectory of the source DOAs. Results for re-alistic room simulations validate the proposed approach and demon-strate significant improvements in estimation accuracy compared tosingle-detection tracking.

  • Journal article
    Clerckx B, Hao C, 2017,

    MISO networks with imperfect CSIT: a topological rate-splitting approach

    , IEEE Transactions on Communications, Vol: 65, Pages: 2164-2179, ISSN: 1558-0857

    Recently, the Degrees-of-Freedom (DoF) region ofmultiple-input-single-output (MISO) networks with imperfectchannel state information at the transmitter (CSIT) has at-tracted significant attention. An achievable scheme, knownas Rate-Splitting (RS), integrates common-message-multicastingand private-message-unicasting. In this paper, focusing on thegeneralK-cell MISO IC with an arbitrary CSIT quality of eachinterfering link, we firstly identify the DoF region achieved byRS. Secondly, we introduce a novel scheme, so called TopologicalRS (TRS), whose novelties compared to RS lie in a multi-layerstructure and in transmitting multiple common messages to bedecoded by groups of users rather than all users. The designof TRS is motivated by a novel interpretation of theK-cell ICwith imperfect CSIT as a weighted sum of a series of partiallyconnected networks. We show that the DoF region achievedby TRS yields the best known result so far, and we find themaximal sum DoF via hypergraph fractional packing. Lastly,for a realistic scenario where each user is connected to threedominant transmitters, we identify the sufficient condition whereTRS strictly outperforms conventional schemes, and show thatTRS is optimal for some CSIT qualities.

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