References of "Ottersten, Björn 50002797"
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See detailAn Asymptotically Efficient Weighted Least Squares Estimator for Co-Array-Based DoA Estimation
Sedighi, Saeid UL; Shankar, Bhavani UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2019)

Co-array-based Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable interest in array processing thanks to its capability of providing enhanced degrees ... [more ▼]

Co-array-based Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable interest in array processing thanks to its capability of providing enhanced degrees of freedom. Although the literature presents a variety of estimators in this context, none of them are proven to be statistically efficient. This work introduces a novel estimator for the co-array-based DoA estimation employing the Weighted Least Squares (WLS) method. An analytical expression for the large sample performance of the proposed estimator is derived. Then, an optimal weighting is obtained so that the asymptotic performance of the proposed WLS estimator coincides with the Cram\'{e}r-Rao Bound (CRB), thereby ensuring asymptotic statistical efficiency of resulting WLS estimator. This implies that the proposed WLS estimator has a significantly better performance compared to existing methods. Numerical simulations are provided to validate the analytical derivations and corroborate the improved performance. [less ▲]

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

in IEEE Transactions on Signal Processing (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 of a subsequence 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 of a subsequence 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 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 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 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 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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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 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)

Detailed reference viewed: 96 (20 UL)
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See detailDeploying Dynamic On-Board Signal Processing Schemes for Multibeam Satellite Systems
Joroughi, Vahid UL; Kibria, Mirza UL; Lagunas, Eva UL et al

in Deploying Dynamic On-Board Signal Processing Schemes for Multibeam Satellite Systems (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 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 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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See detailQoS-Constrained Sum-Harvested Energy Maximization in OFDMA-based Wireless Cooperative Networks
Gautam, Sumit UL; Lagunas, Eva UL; Vuppala, Satyanarayana UL et al

Scientific Conference (2018, December)

We investigate the performances of the time-switching (TS) and power-splitting (PS) based energy harvesting models in a two-hop relay assisted network where the end-users are capable of decoding ... [more ▼]

We investigate the performances of the time-switching (TS) and power-splitting (PS) based energy harvesting models in a two-hop relay assisted network where the end-users are capable of decoding information and harvesting energy concurrently. In particular, we consider joint resource allocation and relay selection to realize Simultaneous Wireless Transmission of Information and Energy (Wi-TIE) in a multi-carrier multi-user cooperative system where the relays employ the amplify-and-forward (AF) protocol. First, we formulate based on the TS and PS Wi-TIE architectures an optimization problem to maximize the sum of energy harvested at the end-users, taking into consideration each user's quality-of-service (QoS) requirement as well as power constraints at the transmit and relaying nodes. We then solve the formulated problem to optimize the users' Wi-TIE splitting factors along with relay-user coupling, sub-carrier-user assignment, sub-carrier pairing, and power allocation. Finally, we demonstrate the benefits of the proposed framework via numerical results. [less ▲]

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See detailSequential Resource Distribution Technique for Multi-User OFDM-SWIPT based Cooperative Networks
Gautam, Sumit UL; Lagunas, Eva UL; Chatzinotas, Symeon UL et al

Scientific Conference (2018, December)

In this paper, we investigate resource allocation and relay selection in a dual-hop orthogonal frequency division multiplexing (OFDM)-based multi-user network where amplify-and-forward (AF) enabled relays ... [more ▼]

In this paper, we investigate resource allocation and relay selection in a dual-hop orthogonal frequency division multiplexing (OFDM)-based multi-user network where amplify-and-forward (AF) enabled relays facilitate simultaneous wireless information and power transfer (SWIPT) to the end-users. In this context, we address an optimization problem to maximize the end-users’ sum-rate subjected to transmit power and harvested energy constraints. Furthermore, the problem is formulated for both time-switching (TS) and power-splitting (PS) SWIPT schemes.We aim at optimizing the users’ SWIPT splitting factors as well as sub-carrier–destination assignment, sub-carrier pairing, and relay–destination coupling metrics. This kind of joint evaluation is combinatorial in nature with non-linear structure involving mixed-integer programming. In this vein, we propose a sub-optimal low complex sequential resource distribution (SRD) method to solve the aforementioned problem. The performance of the proposed SRD technique is compared with a semi-random resource allocation and relay selection approach. Simulation results reveal the benefits of the proposed design under several parameter values with various operating conditions to illustrate the efficiency of SWIPT schemes for the proposed techniques. [less ▲]

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See detailPower and Load Optimization in Interference-Coupled Non-Orthogonal Multiple Access Networks
Lei, Lei UL; You, Lei; Yang, Yang UL et al

in IEEE Global Communications Conference (GLOBECOM) 2018 (2018, December)

Detailed reference viewed: 148 (21 UL)
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See detailClosed-Form Solution for Computationally Efficient Symbol-Level Precoding
Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL; Andrenacci, Stefano UL et al

Scientific Conference (2018, December)

We present a convex optimization based Symbol-Level Precoding (SLP) for sum power minimization and propose the low-latency closed-form algorithm to find a heuristic solution to the optimization problem ... [more ▼]

We present a convex optimization based Symbol-Level Precoding (SLP) for sum power minimization and propose the low-latency closed-form algorithm to find a heuristic solution to the optimization problem. The technique exploits constructive interference at the multi-user MIMO systems and minimizes the sum power of the transmitted precoded signal per each symbol slot. As a result, the received signals gain extra Signal-to-Noise Ratio (SNR), which leads to the improved data rate and energy efficiency. We benchmark the low-complexity algorithm for solving the optimization technique against the conventional Fast Non-Negative Least Squares algorithm (NNLS). The demonstrated design of the SLP technique combined with the proposed closed-form algorithm has low computational complexity and fast processing time, which is applicable in low-latency high-throughput satellite communication systems. [less ▲]

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See detailSuccessive convex approximation algorithms for sparse signal estimation with nonconvex regularizations
Yang, Yang UL; Pesavento, Marius; Chatzinotas, Symeon UL et al

in IEEE Journal of Selected Topics in Signal Processing (2018), 12(6), 1286-1302

Detailed reference viewed: 265 (38 UL)