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See detailOn the Successful Delivery Probability of Full-Duplex-Enabled Mobile Edge Caching
Vu, Thang Xuan UL; Lei, Lei UL; Chatzinotas, Symeon UL et al

in IEEE Communications Letters (2019)

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See detailMachine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems
Vu, Thang Xuan UL; Lei, Lei UL; Chatzinotas, Symeon UL et al

in 2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) (2019, June)

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See detailUltrareliable SWIPT using Unscheduled Short Packet Transmissions
Kisseleff, Steven UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE International Conference on Communications (ICC), B5G-URLLC Workshop, Shanghai, May 2019 (2019, May 20)

Large communication networks, e.g. Internet of Things (IoT), are known to be vulnerable to the co-channel interference from simultaneous transmissions. In the recent time, this problem has been ... [more ▼]

Large communication networks, e.g. Internet of Things (IoT), are known to be vulnerable to the co-channel interference from simultaneous transmissions. In the recent time, this problem has been extensively studied in various contexts. Due to a potentially very long duty cycle, orthogonal multiple access techniques are not well suited for such schemes. Instead, random medium access (RMA) seems promising, since it guarantees a lower bound for the network throughput even in presence of an infinite number of simultaneous transmissions while reducing the average length of the duty cycle. Such an RMA scheme is based on transmission of short data packets with unknown scheduling. Of course, a reliable symbol detection for this type of communication is very challenging not only due to a large amount of interference from the adjacent nodes, but also because of the uncertainty related to the presence or absence of overlapping packets. Interestingly, with increasing number of network nodes also the amount of energy, which can be harvested from the received signal, increases. This is especially beneficial for powering of a relay device, which may utilize the energy for further information processing and retransmission. In this paper, we address the design of a simultaneous information and power transfer scheme based on unscheduled short packet transmissions for ultrareliable communication. [less ▲]

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See detailParallel coordinate descent algorithms for sparse phase retrieval
Yang, Yang UL; Pesavento, Marius; Eldar, Yonina C. et al

in Proc. 2019 IEEE International Conference on Acoustics, Speech and Signal (ICASSP) (2019, May)

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See detailVIEW-INVARIANT ACTION RECOGNITION FROM RGB DATA VIA 3D POSE ESTIMATION
Baptista, Renato UL; Ghorbel, Enjie UL; Papadopoulos, Konstantinos UL et al

in IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 12–17 May 2019 (2019, May)

In this paper, we propose a novel view-invariant action recognition method using a single monocular RGB camera. View-invariance remains a very challenging topic in 2D action recognition due to the lack of ... [more ▼]

In this paper, we propose a novel view-invariant action recognition method using a single monocular RGB camera. View-invariance remains a very challenging topic in 2D action recognition due to the lack of 3D information in RGB images. Most successful approaches make use of the concept of knowledge transfer by projecting 3D synthetic data to multiple viewpoints. Instead of relying on knowledge transfer, we propose to augment the RGB data by a third dimension by means of 3D skeleton estimation from 2D images using a CNN-based pose estimator. In order to ensure view-invariance, a pre-processing for alignment is applied followed by data expansion as a way for denoising. Finally, a Long-Short Term Memory (LSTM) architecture is used to model the temporal dependency between skeletons. The proposed network is trained to directly recognize actions from aligned 3D skeletons. The experiments performed on the challenging Northwestern-UCLA dataset show the superiority of our approach as compared to state-of-the-art ones. [less ▲]

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See detailInexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization
Yang, Yang UL; Pesavento, Marius; Luo, Zhi-Quan et al

E-print/Working paper (2019)

In this paper, we propose an inexact block coordinate descent algorithm for large-scale nonsmooth nonconvex optimization problems. At each iteration, a particular block variable is selected and updated by ... [more ▼]

In this paper, we propose an inexact block coordinate descent algorithm for large-scale nonsmooth nonconvex optimization problems. At each iteration, a particular block variable is selected and updated by solving the original optimization problem with respect to that block variable inexactly. More precisely, a local approximation of the original optimization problem is solved. The proposed algorithm has several attractive features, namely, i) high flexibility, as the approximation function only needs to be strictly convex and it does not have to be a global upper bound of the original function; ii) fast convergence, as the approximation function can be designed to exploit the problem structure at hand and the stepsize is calculated by the line search; iii) low complexity, as the approximation subproblems are much easier to solve and the line search scheme is carried out over a properly constructed differentiable function; iv) guaranteed convergence to a stationary point, even when the objective function does not have a Lipschitz continuous gradient. Interestingly, when the approximation subproblem is solved by a descent algorithm, convergence to a stationary point is still guaranteed even if the approximation subproblem is solved inexactly by terminating the descent algorithm after a finite number of iterations. These features make the proposed algorithm suitable for large-scale problems where the dimension exceeds the memory and/or the processing capability of the existing hardware. These features are also illustrated by several applications in signal processing and machine learning, for instance, network anomaly detection and phase retrieval. [less ▲]

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See detailA Calibrated Learning Approach to Distributed Power Allocation in Small Cell Networks
Zhang, Xinruo; Nakhai; Zheng, Gan UL et al

in ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2019, April 17)

This paper studies the problem of max-min fairness power allocation in distributed small cell networks operated under the same frequency bandwidth. We introduce a calibrated learning enhanced time ... [more ▼]

This paper studies the problem of max-min fairness power allocation in distributed small cell networks operated under the same frequency bandwidth. We introduce a calibrated learning enhanced time division multiple access scheme to optimize the transmit power decisions at the small base stations (SBSs) and achieve max-min user fairness in the long run. Provided that the SBSs are autonomous decision makers, the aim of the proposed algorithm is to allow SBSs to gradually improve their forecast of the possible transmit power levels of the other SBSs and react with the best response based on the predicted results at individual time slots. Simulation results validate that in terms of achieving max-min signal-to-interference-plus-noise ratio, the proposed distributed design outperforms two benchmark schemes and achieves a similar performance as compared to the optimal centralized design. [less ▲]

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See detailPricing Perspective for SWIPT in OFDM-based Multi-User Wireless Cooperative Systems
Gautam, Sumit UL; Lagunas, Eva UL; Vuppala, Satyanarayana UL et al

Scientific Conference (2019, April)

We propose a novel formulation for joint maximization of total weighted sum-spectral efficiency and weighted sum-harvested energy to study Simultaneous Wireless Information and Power Transfer (SWIPT) from ... [more ▼]

We propose a novel formulation for joint maximization of total weighted sum-spectral efficiency and weighted sum-harvested energy to study Simultaneous Wireless Information and Power Transfer (SWIPT) from a pricing perspective. Specifically, we consider that a transmit source communicates with multiple destinations using Orthogonal Frequency Division Multiplexing (OFDM) system within a dual-hop relay-assisted network, where the destination nodes are capable of jointly decoding information and harvesting energy from the same radio-frequency (RF) signal using either the time-switching (TS) or power-splitting (PS) based SWIPT receiver architectures. Computation of the optimal solution for the aforementioned problem is an extremely challenging task as joint optimization of several network resources introduce intractability at high numeric values of relays, destination nodes and OFDM sub-carriers. Therefore, we present a suitable algorithm with sub-optimal results and good performance to compute the performance of joint data processing and harvesting energy under fixed pricing methods by adjusting the respective weight factors, motivated by practical statistics. Furthermore, by exploiting the binary options of the weights, we show that the proposed formulation can be regulated purely as a sum-spectral efficiency maximization or solely as a sum-harvested energy maximization problem. Numerical results illustrate the benefits of the proposed design under several operating conditions and parameter values. [less ▲]

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See detailRelay Selection and Resource Allocation for SWIPT in Multi-User OFDMA Systems
Gautam, Sumit UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2019)

We investigate the resource allocation and relay selection in a two-hop relay-assisted multi-user Orthogonal Frequency Division Multiple Access (OFDMA) network, where the end-nodes support Simultaneous ... [more ▼]

We investigate the resource allocation and relay selection in a two-hop relay-assisted multi-user Orthogonal Frequency Division Multiple Access (OFDMA) network, where the end-nodes support Simultaneous Wireless Information and Power Transfer (SWIPT) employing a Power Splitting (PS) technique. Our goal is to optimize the end-nodes’ power splitting ratios as well as the relay, carrier and power assignment so that the sum-rate of the system is maximized subject to harvested energy and transmitted power constraints. Such joint optimization with mixed integer non-linear programming structure is combinatorial in nature. Due to the complexity of this problem, we propose to solve its dual problem which guarantees asymptotic optimality and less execution time compared to a highly-complex exhaustive search approach. Furthermore, we also present a heuristic method to solve this problem with lower computational complexity. Simulation results reveal that the proposed algorithms provide significant performance gains compared to a semi-random resource allocation and relay selection approach and close to the optimal solution when the number of OFDMA sub-carriers is sufficiently large. [less ▲]

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See detailRobust Design of Power Minimizing Symbol-Level Precoder under Channel Uncertainty
Haqiqatnejad, Alireza UL; Kayhan, Farbod UL; Ottersten, Björn UL

in IEEE Global Communications Conference (GLOBECOM), Abu Dhabi 9-13 December 2018 (2019, February 21)

In this paper, we investigate the downlink transmission of a multiuser multiple-input single-output (MISO) channel under a symbol-level precoding (SLP) scheme, having imperfect channel knowledge at the ... [more ▼]

In this paper, we investigate the downlink transmission of a multiuser multiple-input single-output (MISO) channel under a symbol-level precoding (SLP) scheme, having imperfect channel knowledge at the transmitter. In defining the SLP design problem, a general category of constructive interference regions (CIR) called distance preserving CIR (DPCIR) is adopted. In particular, we are interested in a robust SLP design minimizing the total transmit power subject to individual quality-of-service (QoS) requirements. We consider two common models for the channel uncertainty region, namely, spherical (norm-bounded) and stochastic. For the spherical uncertainty model, a worst-case robust precoder is proposed, while for the stochastically known uncertainties, we derive a convex optimization problem with probabilistic constraints. We simulate the performance of the proposed robust approaches, and compare them with the existing methods. Through the simulation results, we also show that there is an essential trade-off between the two robust approaches. [less ▲]

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See detailTime-Switching based Simultaneous Wireless Transmission of Information and Energy (Wi-TIE) for Relaying Systems with Caching Architecture
Gautam, Sumit UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in Duong, Trung; Chu, Xiaoli; Suraweera, Himal (Eds.) Ultra-Dense Networks for 5G and Beyond - Modelling, Analysis, and Applications (2019)

In this chapter, we investigate the performance of a time-switching (TS) based energy harvesting model for cache-assisted simultaneous wireless transmission of information and energy (Wi-TIE). In the ... [more ▼]

In this chapter, we investigate the performance of a time-switching (TS) based energy harvesting model for cache-assisted simultaneous wireless transmission of information and energy (Wi-TIE). In the considered system, a relay which is equipped with both caching and energy harvesting capabilities helps a source to convey information to a destination. Based on the time-splitting mechanism, we analyze the effect of caching on the system performance in terms of stored energy at the relay and the relay-destination link throughput. In particular, two optimization problems are formulated to maximize the energy stored at the relay and the relay-destination throughput. By using KKT method, closed-form solution are obtained for both the problems. Finally, the performance of the proposed design under various operating conditions and parameter values is illustrated using numerical results. [less ▲]

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See detailA View-invariant Framework for Fast Skeleton-based Action Recognition Using a Single RGB Camera
Ghorbel, Enjie UL; Papadopoulos, Konstantinos UL; Baptista, Renato UL et al

in 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Prague, 25-27 February 2018 (2019, February)

View-invariant action recognition using a single RGB camera represents a very challenging topic due to the lack of 3D information in RGB images. Lately, the recent advances in deep learning made it ... [more ▼]

View-invariant action recognition using a single RGB camera represents a very challenging topic due to the lack of 3D information in RGB images. Lately, the recent advances in deep learning made it possible to extract a 3D skeleton from a single RGB image. Taking advantage of this impressive progress, we propose a simple framework for fast and view-invariant action recognition using a single RGB camera. The proposed pipeline can be seen as the association of two key steps. The first step is the estimation of a 3D skeleton from a single RGB image using a CNN-based pose estimator such as VNect. The second one aims at computing view-invariant skeleton-based features based on the estimated 3D skeletons. Experiments are conducted on two well-known benchmarks, namely, IXMAS and Northwestern-UCLA datasets. The obtained results prove the validity of our concept, which suggests a new way to address the challenge of RGB-based view-invariant action recognition. [less ▲]

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See detailSlicing based Resource Allocation for Multiplexing of eMBB and URLLC Services in 5G Wireless Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in Slicing based Resource Allocation for Multiplexing of eMBB and URLLC Services in 5G Wireless Networks (2019)

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See detailLinear Precoding Design for Cache-aided Full-duplex Networks
Vu, Thang Xuan UL; Vu, Trinh Anh; Lei, Lei UL et al

in 2019 IEEE Wireless Communications and Networking Conference (WCNC) (2019)

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See detailPower and Flow Assignment for 5G Integrated Terrestrial-Satellite Backhaul Networks
Lagunas, Eva UL; Lei, Lei UL; Chatzinotas, Symeon UL et al

in IEEE Wireless Communications and Networking Conference, Marrakech, Morocco, April 2019 (2019)

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See detailDemonstrator of Precoding Technique for a Multi-Beams Satellite System
Maturo, Nicola UL; Merlano Duncan, Juan Carlos UL; Krivochiza, Jevgenij UL et al

in 2019 8th International Workshop on Tracking, Telemetry and Command Systems for Space Applications (TTC) (2019)

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See detailLocalized Trajectories for 2D and 3D Action Recognition
Papadopoulos, Konstantinos UL; Demisse, Girum UL; Ghorbel, Enjie UL et al

in Sensors (2019)

The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to noise and background motion ... [more ▼]

The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to noise and background motion, many generated trajectories are irrelevant to the actual human activity and can potentially lead to performance degradation. In this paper, we propose Localized Trajectories as an improved version of Dense Trajectories where motion trajectories are clustered around human body joints provided by RGB-D cameras and then encoded by local Bag-of-Words. As a result, the Localized Trajectories concept provides an advanced discriminative representation of actions. Moreover, we generalize Localized Trajectories to 3D by using the depth modality. One of the main advantages of 3D Localized Trajectories is that they describe radial displacements that are perpendicular to the image plane. Extensive experiments and analysis were carried out on five different datasets. [less ▲]

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See detailFPGA Acceleration for Computationally Efficient Symbol-Level Precoding in Multi-User Multi-Antenna Communication Systems
Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL; Andrenacci, Stefano UL et al

in IEEE Access (2019)

In this paper, we demonstrate an FPGA accelerated design of the computationally efficient Symbol-Level Precoding (SLP) for high-throughput communication systems. The SLP technique recalculates optimal ... [more ▼]

In this paper, we demonstrate an FPGA accelerated design of the computationally efficient Symbol-Level Precoding (SLP) for high-throughput communication systems. The SLP technique recalculates optimal beam-forming vectors by solving a non-negative least squares (NNLS) problem per every set of transmitted symbols. It exploits the advantages of constructive inter-user interference to minimize the total transmitted power and increase service availability. The benefits of using SLP come with a substantially increased computational load at a gateway. The FPGA design enables the SLP technique to perform in realtime operation mode and provide a high symbol throughput for multiple receive terminals. We define the SLP technique in a closed-form algorithmic expression and translate it to Hardware Description Language (HDL) and build an optimized HDL core for an FPGA. We evaluate the FPGA resource occupation, which is required for high throughput multiple-input-multiple-output (MIMO) systems with sizeable dimensions. We describe the algorithmic code, the I/O ports mapping and the functional behavior of the HDL core. We deploy the IP core to an actual FPGA unit and benchmark the energy efficiency performance of SLP. The synthetic tests demonstrate a fair energy efficiency improvement of the proposed closed-form algorithm, also compared to the best results obtained through MATLAB numerical simulations. [less ▲]

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See detailEnergy Efficient Design for Coded Caching Delivery Phase
Vu, Thang Xuan UL; Lei, Lei UL; Chatzinotas, Symeon UL et al

in 2019 IEEE International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom) (2019)

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