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See detailJoint Scheduling and Precoding for Frame-Based Multigroup Multicasting in Satellite Communications
Bandi, Ashok UL; Shankar, Bhavani UL; Chatzinotas, Symeon UL et al

Scientific Conference (2019, December 09)

Recent satellite standards enforce the coding of multiple users’ data in a frame. This transmission strategy mimics the well-known physical layer multigroup multicasting (MGMC). However, typical beam ... [more ▼]

Recent satellite standards enforce the coding of multiple users’ data in a frame. This transmission strategy mimics the well-known physical layer multigroup multicasting (MGMC). However, typical beam coverage with a large number of users and limited frame length lead to the scheduling of only a few users. Moreover, in emerging aggressive frequency reuse systems, scheduling is coupled with precoding. This is addressed in this work, through the joint design of scheduling and precoding for frame-based MGMC satellite systems. This aim is formulated as the maximization of the sum-rate under per beam power constraint and minimum SINR requirement of scheduled users. Further, a framework is proposed to transform the non-smooth SR objective with integer scheduling and nonconvex SINR constraints as a difference-of-convex problem that facilitates the joint update of scheduling and precoding. Therein, an efficient convex-concave procedure based algorithm is proposed. Finally, the gains (up to 50%) obtained by the jointed design over state-of-the-art methods is shown through Monte-Carlo simulations. [less ▲]

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See detailWireless Multi-group Multicast Precoding with Selective RF Energy Harvesting
Gautam, Sumit UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

Scientific Conference (2019, September 05)

We present a novel framework for multi-group multicast precoding in the presence of three types of wireless users which are distributed among various multicast groups. A multi-antenna transmitter conveys ... [more ▼]

We present a novel framework for multi-group multicast precoding in the presence of three types of wireless users which are distributed among various multicast groups. A multi-antenna transmitter conveys information and/or energy to the groups of corresponding receivers using more than one multicast streams. The information specific users have conventional receiver architectures to process data, energy harvesting users collect energy using the non-linear energy harvesting module and each of the joint information decoding and energy harvesting capable user is assumed to employ the separated architecture with disparate non-linear energy harvesting and conventional information decoding units. In this context, we formulate and analyze the problem of total transmit power minimization for optimal precoder design subjected to minimum signal-to-interference-and-noise ratio and harvested energy demands at the respective users under three different scenarios. This problem is solved via semi-definite relaxation and the advantages of employing separate information and energy precoders are shown over joint and per-user information and energy precoder designs. Simulation results illustrate the benefits of proposed framework under several operating conditions and parameter values. [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 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 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 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 detailTwo-stage RGB-based Action Detection using Augmented 3D Poses
Papadopoulos, Konstantinos UL; Ghorbel, Enjie UL; Baptista, Renato UL et al

in 18th International Conference on Computer Analysis of Images and Patterns SALERNO, 3-5 SEPTEMBER, 2019 (2019)

In this paper, a novel approach for action detection from RGB sequences is proposed. This concept takes advantage of the recent development of CNNs to estimate 3D human poses from a monocular camera. To ... [more ▼]

In this paper, a novel approach for action detection from RGB sequences is proposed. This concept takes advantage of the recent development of CNNs to estimate 3D human poses from a monocular camera. To show the validity of our method, we propose a 3D skeleton-based two-stage action detection approach. For localizing actions in unsegmented sequences, Relative Joint Position (RJP) and Histogram Of Displacements (HOD) are used as inputs to a k-nearest neighbor binary classifier in order to define action segments. Afterwards, to recognize the localized action proposals, a compact Long Short-Term Memory (LSTM) network with a de-noising expansion unit is employed. Compared to previous RGB-based methods, our approach offers robustness to radial motion, view-invariance and low computational complexity. Results on the Online Action Detection dataset show that our method outperforms earlier RGB-based approaches. [less ▲]

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See detailMargin-based Active Online Learning Techniques for Cooperative Spectrum Sharing in CR Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM), Poznan, Poland, June 2019 (2019)

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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 detailSatellite Links Integrated in 5G SDN-enabled Backhaul Networks: An Iterative Joint Power and Flow Assignment
Lagunas, Eva UL; Lei, Lei UL; Chatzinotas, Symeon UL et al

in European Signal Processing Conference (EUSIPCO), A Coruna, Spain, Sept. 2019 (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 detailEnergy efficiency optimization in MIMO interference channels: A successive pseudoconvex approximation approach
Yang, Yang UL; Pesavento, Marius; Chatzinotas, Symeon UL et al

in IEEE Transactions on Signal Processing (2019)

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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 detailSymbol-Level Precoding for Low Complexity Transmitter Architectures in Large-Scale Antenna Array Systems
Domouchtsidis, Stavros; Tsinos, Christos UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications ( Early Access ) (2018)

In this paper we consider three transmitter designs for symbol-level-precoding (SLP), a technique that mitigates multiuser interference (MUI) in multiuser systems by designing the transmitted signals ... [more ▼]

In this paper we consider three transmitter designs for symbol-level-precoding (SLP), a technique that mitigates multiuser interference (MUI) in multiuser systems by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital Radio Frequency (RF) chains. The first proposed architecture referred as, Antenna Selection SLP, minimizes the MUI by activating a subset of the available antennas and thus, reducing the number of required RF chains to the number of active antennas. In the other two architectures, which we refer to as RF domain SLP, the processing happens entirely in the RF domain, thus eliminating the need for multiple fully digital RF chains altogether. Instead, analog phase shifters directly modulate the signals on the transmit antennas. The precoding design for all the considered cases is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Simulations provide insights on the power efficiency of the proposed schemes and the improvements over the fully digital counterparts. [less ▲]

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