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See detailUnified Framework for Secrecy Characteristics with Mixture of Gaussian (MoG) Distribution
Kong, Long UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Wireless Communications Letters (2020)

The mixture of Gaussian (MoG) distribution was proposed to model the wireless channels by implementing the completely unsupervised expectation-maximization (EM) learning algorithm. With the high ... [more ▼]

The mixture of Gaussian (MoG) distribution was proposed to model the wireless channels by implementing the completely unsupervised expectation-maximization (EM) learning algorithm. With the high convenience for density estimation applications, the focus of this letter is supposed to investigate the secrecy metrics, including secrecy outage probability (SOP), the lower bound of SOP, the probability of non-zero secrecy capacity (PNZ), and the average secrecy capacity (ASC) from the information-theoretic perspective. The above-mentioned metrics are derived with simple and unified closed-form expressions. The effectiveness of our obtained analytical expressions are successfully examined and compared with Monte-Carlo simulations. One can conclude that this letter provides a simple but effective closed-form secrecy analysis solution exploiting the MoG distribution. [less ▲]

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See detailSuccessive Convex Approximation for Transmit Power Minimization in SWIPT-Multicast Systems
Gautam, Sumit UL; Lagunas, Eva UL; Kisseleff, Steven UL et al

Scientific Conference (2020, June)

We propose a novel technique for total transmit power minimization and optimal precoder design in wireless multi-group (MG) multicasting (MC) systems. The considered framework consists of three different ... [more ▼]

We propose a novel technique for total transmit power minimization and optimal precoder design in wireless multi-group (MG) multicasting (MC) systems. The considered framework consists of three different systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures, energy harvesting (EH) only users with non-linear EH module, and users with joint ID and EH capabilities having separate units for the two operations, respectively. Each user is categorized under unique group(s), which can be of MC type specifically meant for ID users, and/or an energy group consisting of EH explicit users. The joint ID and EH users are a part of the (last) EH group as well as any one of the MC groups distinctly. In this regard, we formulate an optimization problem to minimize the total transmit power with optimal precoder designs for the three aforementioned scenarios, under constraints on minimum signal-to-interference-plus-noise ratio and harvested energy by the users with respective demands. The problem may be adapted to the well-known semi-definite program, which can be typically solved via relaxation of rank-1 constraint. However, the relaxation of this constraint may in some cases lead to performance degradation, which increases with the rank of the solution obtained from the relaxed problem. Hence, we develop a novel technique motivated by the feasible-point pursuit and successive convex approximation method in order to address the rank-related issue. The benefits of the proposed method are illustrated under various operating conditions and parameter values, with comparison between the three above-mentioned scenarios. [less ▲]

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See detailGOING DEEPER WITH NEURAL NETWORKS WITHOUT SKIP CONNECTIONS
Oyedotun, Oyebade UL; Shabayek, Abd El Rahman UL; Aouada, Djamila UL et al

in IEEE International Conference on Image Processing (ICIP 2020), Abu Dhabi, UAE, Oct 25–28, 2020 (2020, May 30)

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See detailBoosting SWIPT via Symbol-Level Precoding
Gautam, Sumit UL; Krivochiza, Jevgenij UL; Haqiqatnejad, Alireza UL et al

Scientific Conference (2020, May 29)

In this paper, we investigate a simultaneous wireless information and power transmission (SWIPT) system, wherein a single multi-antenna transmitter serves multiple single-antenna users which employ the ... [more ▼]

In this paper, we investigate a simultaneous wireless information and power transmission (SWIPT) system, wherein a single multi-antenna transmitter serves multiple single-antenna users which employ the power-splitting (PS) receiver architecture. We formulate a Symbol-Level Precoding (SLP) based transmit power minimization problem dependent on the minimum signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) thresholds. We solve the corresponding non-negative convex quadratic optimization problem per time frame of transmitted symbols and study the benefits of proposed design under Zero-Forcing (ZF) Precoding, Direct Demand SLP (DD-SLP), and Squared-Root Demand SLP (RD-SLP) techniques. A static PS-ratio is fixed according to the SINR and EH demands to enable the segregation of intended received signals for information decoding (ID) and EH, respectively. Numerical results show the property conservation of SINR-enhancement via SLP at the ID unit while increasing the harvested energy at each of the end-users. [less ▲]

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See detailInformation Theoretic Approach for Waveform Design in Coexisting MIMO Radar and MIMO Communications
Alaeekerahroodi, Mohammad UL; Mysore Rama Rao, Bhavani Shankar UL; Mishra, Kumar Vijay et al

in Information Theoretic Approach for Waveform Design in Coexisting MIMO Radar and MIMO Communications (2020, May 14)

We investigate waveform design for coexistence between a multipleinput multiple-output (MIMO) radar and MIMO communications (MRMC), with a radar-centric criterion that leads to a minimal interference in ... [more ▼]

We investigate waveform design for coexistence between a multipleinput multiple-output (MIMO) radar and MIMO communications (MRMC), with a radar-centric criterion that leads to a minimal interference in the communications system. The communications use the traditional mode of operation in Long Term Evolution (LTE)/Advanced (FDD), where we formulate the design problem based on information-theoretic criterion with the discrete phase constraint at the design stage. The optimization problem, is nonconvex, multi-objective and multi-variable, where we propose an efficient algorithm based on the coordinate descent (CD) framework to simultaneously improve radar target detection performance and the communications rate. The numerical results indicate the effectiveness of the proposed algorithm in designing discrete phase set of sequences, potentially binary. [less ▲]

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See detailDeep Rainrate Estimation from Highly Attenuated Downlink Signals of Ground-Based Communications Satellite Terminals
Mishra, K. V.; R., B. S. M.; Ottersten, Björn UL

in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Deep Rainrate Estimation from Highly Attenuated Downlink Signals of Ground-Based Communications Satellite Terminals (2020, May 14)

While the use of weather radars to continuously monitor the spatiotemporal dynamics of precipitation has grown in recent years, these systems are expensive and sparsely deployed across the world. In this ... [more ▼]

While the use of weather radars to continuously monitor the spatiotemporal dynamics of precipitation has grown in recent years, these systems are expensive and sparsely deployed across the world. In this context, densely located ground-based terminals for interactive satellite services have the potential for dual-use as weather sensors because they measure rain-attenuated power of the downlink signal. Although in the millimeter-wave regime, the rain rate has almost a linear relationship with specific attenuation, lack of other weather radar observables at satellite terminals imposes a daunting task of extracting rainfall rate from these highly attenuated signals. We address this problem by designing a deep convolutional neural network (CNN) that learns the relationship between the signal attenuation and rainfall rate observed by weather radars and rain gauges at a given location. During the prediction stage, the CNN accepts downlink attenuation as input and classifies the rain intensity which is then used to apply an appropriate rainfall estimator. Our experiments with real data show that, despite severe attenuation, CNN-based downlink rainfall accumulations closely follow the nearest C-band German weather service Deutscher Wetterdienst (DWD) radar. [less ▲]

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See detail'Faster-than-Nyquist Signaling via Spatiotemporal Symbol-Level Precoding for Multi-User MISO Redundant Transmissions
Alves Martins, Wallace UL; Spano, Danilo UL; Chatzinotas, Symeon UL et al

in International Conference on Acoustics, Speech, and Signal Processing (ICASSP-2020), Barcelona 4-8 May 2020 (2020, May)

This paper tackles the problem of both multi-user and intersymbol interference stemming from co-channel users transmitting at a faster-than-Nyquist (FTN) rate in multi-antenna downlink transmissions. We ... [more ▼]

This paper tackles the problem of both multi-user and intersymbol interference stemming from co-channel users transmitting at a faster-than-Nyquist (FTN) rate in multi-antenna downlink transmissions. We propose a framework for redundant block-based symbol-level precoders enabling the trade-off between constructive and destructive multi-user and interblock interference (IBI) effects at the single-antenna user terminals. Redundant elements are added as guard interval to handle IBI destructive effects. It is shown that, within this framework, accelerating the transmissions via FTN signaling improves the error-free spectral efficiency, up to a certain acceleration factor beyond which the transmitted information cannot be perfectly recovered by linear filtering followed by sampling. Simulation results corroborate that the proposed spatiotemporal symbol-level precoding can change the amount of added redundancy from zero (full IBI) to half (IBI-free) the equivalent channel order, so as to achieve a target balance between spectral and energy efficiencies. [less ▲]

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See detailJoint Optimization for PS-based SWIPT Multiuser Systems with Non-linear Energy Harvesting
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Gautam, Sumit UL et al

in IEEE Wireless Communications and Networking Conference (WCNC), Seoul, 25-38 May 2020 (2020, May)

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) multiuser systems, in which a base station serves a set of users with both information and ... [more ▼]

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) multiuser systems, in which a base station serves a set of users with both information and energy simultaneously via a power splitting (PS) mechanism. To capture realistic scenarios, a nonlinear energy harvesting (EH) model is considered. In particular, we jointly design the PS factors and the beamforming vectors in order to maximize the total harvested energy, subjected to rate requirements and a total transmit power budget. To deal with the inherent non-convexity of the formulated problem, an iterative optimization algorithm is proposed based on the inner approximation method and semidefinite relaxation (SDR), whose convergence is theoretically guaranteed. Numerical results show that the proposed scheme significantly outperforms the baseline max-min based SWIPT multicast and fixed-power PS designs. [less ▲]

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See detailDeep Learning for Beam Hopping in Multibeam Satellite Systems
Lei, Lei UL; Lagunas, Eva UL; Yuan, Yaxiong UL et al

in IEEE 91st Vehicular Technology Conference (VTC2020-Spring) (2020, May)

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See detailTowards Power-Efficient Aerial Communicationsvia Dynamic Multi-UAV Cooperation
Xiang, Lin; Lei, Lei UL; Chatzinotas, Symeon UL et al

in IEEE Wireless Communications and Networking Conference (WCNC) 2020 (2020, May)

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See detail3D DEFORMATION SIGNATURE FOR DYNAMIC FACE RECOGNITION
Shabayek, Abd El Rahman UL; Aouada, Djamila UL; Cherenkova, Kseniya UL et al

in 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona 4-8 May 2020 (2020, May)

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See detailLearning-Assisted Eavesdropping and Symbol-Level Precoding Countermeasures for Downlink MU-MISO Systems
Mayouche, Abderrahmane UL; Spano, Danilo UL; Tsinos, Christos UL et al

in IEEE Open Journal of the Communications Society (2020), 1

In this work, we introduce a machine-learning (ML) based detection attack, where an eavesdropper (Eve) is able to learn the symbol detection function based on precoded pilots. With this ability, an Eve ... [more ▼]

In this work, we introduce a machine-learning (ML) based detection attack, where an eavesdropper (Eve) is able to learn the symbol detection function based on precoded pilots. With this ability, an Eve can correctly detect symbols with a high probability. To counteract this attack, we propose a novel symbol-level precoding (SLP) scheme that enhances physical-layer security (PLS) while guaranteeing a constructive interference effect at the intended users. Contrary to conventional SLP schemes, the proposed scheme is robust to the ML-based attack. In particular, the proposed scheme enhances security by designing Eve's received signal to lie at the boundaries of the detection regions. This distinct design causes Eve's detection decisions to be based almost purely on noise. The proposed countermeasure is then extended to account for multi-antennas at the Eve and also for multi-level modulation schemes. In the numerical results, we validate both the detection attack and the countermeasures and show that this gain in security can be achieved at the expense of only a small additional power consumption at the transmitter, and more importantly, these benefits are obtained without affecting the performance at the intended user. [less ▲]

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See detailEnergy- and Cost-Efficient Physical Layer Security in the Era of IoT: The Role of Interference
Wei, Z.; Masouros, C.; Liu, F. et al

in IEEE Communications Magazine (2020), 58(4), 81-87

IoT is emerging as the future evolution of the Internet, aiming to provide connectivity for everyone and everything. Since IoT is expected to carry important and private information, a high level of PHY ... [more ▼]

IoT is emerging as the future evolution of the Internet, aiming to provide connectivity for everyone and everything. Since IoT is expected to carry important and private information, a high level of PHY security is critical for wireless communications in IoT, as a complement for traditional security techniques that are employed at high layers. In this overview, we examine the recent interest in energy-efficient and cost-efficient PHY solutions for securing downlink IoT transmission through interference exploitation. This exciting line of research departs from conventional interference cancellation, and judiciously employs the inherent interference as a useful element for LUs while obstructing the eavesdropping of information. We first discuss the concept of CI, and then elaborate the fundamental CI signal design that employs the traditionally undesired interference as a constructive element to LUs while ensuring they are destructive to potential Eves. Subsequently, we illustrate several low-hardware-cost techniques to inherit the advantage of CI in an energy- and cost-efficient manner, from the perspective of HBF and DM. This family of techniques brings a disruptive vision of interference management for securing wireless communications with an eye on low-cost and hardware-constrained devices tailored for IoT systems. [less ▲]

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See detailProof of the Equivalency of MSE-Constrained and Rate-Constrained Power Optimization Approaches to Distributed Bi-Directional Beamforming
Rahimi, Razgar; Shahbazpanahi, Shahram UL; Ottersten, Björn UL

in IEEE Transactions on Signal and Information Processing over Networks (2020), 6

Considered in this article is an asynchronous single-carrier two-way relay network, where two transceivers aim to communicate through a set of amplify-and-forward (AF) relays. This network is asynchronous ... [more ▼]

Considered in this article is an asynchronous single-carrier two-way relay network, where two transceivers aim to communicate through a set of amplify-and-forward (AF) relays. This network is asynchronous in the sense that the signal transmitted by any of the two transceivers arrives the other transceiver through different relaying paths, with possibly different propagation delays, thereby materializing a multipath channel. At sufficiently high data rates, this multi-path end-to-end channel causes inter-symbol-interference (ISI) in the received signals. Considering such a network, this paper presents two contributions. The first contribution is the rigorous characterization of the region of the mean-squared errors (MSEs) of the symbol estimates at the two transceivers under a total power budget, and when linear block post-channel equalization is used at the receiver front-end of the two transceivers. The importance of this MSE region characterization resides in the fact that knowing this region allows for characterization the region of un-coded probabilities of error at the two transceivers. Also, this MSE region characterization paves the way towards presenting the second contribution in this paper. Indeed, in the second contribution, this article relies on this MSE region characterization to rigorously prove that an MSE-constrained total power minimization approach and a rate-constrained total power minimization approach to design transceiver power allocation and distributed beamforming are equivalent, if the MSE thresholds in the former approach and the rate thresholds in the latter approach are properly chosen. The equivalence of these two approaches implies that the un-coded MSE performance of the network can be inferred from the rate-constrained problem, and conversely, the coded rate performance of the network can be inferred from the MSE-constrained total power minimization problem. [less ▲]

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See detailRobust SINR-Constrained Symbol-Level Multiuser Precoding With Imperfect Channel Knowledge
Haqiqatnejad, Alireza UL; Kayhan, Farbod UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2020), 68(1), 1837-1852

In this paper, we address robust design of symbol-level precoding (SLP) for the downlink of multiuser multiple-input single-output wireless channels, when imperfect channel state information (CSI) is ... [more ▼]

In this paper, we address robust design of symbol-level precoding (SLP) for the downlink of multiuser multiple-input single-output wireless channels, when imperfect channel state information (CSI) is available at the transmitter. In particular, we consider a well known model for the CSI imperfection, namely, stochastic Gaussian-distributed uncertainty. Our design objective is to minimize the total (per-symbol) transmission power subject to constructive interference (CI) constraints as well as the users’ quality-of-service requirements in terms of signal-to-interference-plus-noise ratio. Assuming stochastic channel uncertainties, we first define probabilistic CI constraints in order to achieve robustness to statistically known CSI errors. Since these probabilistic constraints are difficult to handle, we resort to their convex approximations in the form of tractable (deterministic) robust constraints. Three convex approximations are obtained based on different conservatism levels, among which one is introduced as a benchmark for comparison. We show that each of our proposed approximations is tighter than the other under specific robustness settings, while both of them always outperform the benchmark. Using the proposed CI constraints, we formulate the robust SLP optimization problem as a second-order cone program. Extensive simulation results are provided to validate our analytic discussions and to make comparisons with conventional block-level robust precoding schemes. We show that the robust design of symbol-level precoder leads to an improved performance in terms of energy efficiency at the cost of increasing the computational complexity by an order of the number of users in the large system limit, compared to its non-robust counterpart. [less ▲]

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See detailA RAN Resource Slicing Mechanism for Multiplexing of eMBB and URLLC Services in OFDMA based 5G Wireless Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in IEEE Access (2020)

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two ... [more ▼]

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two services on the same wireless infrastructure leads to a challenging resource allocation problem due to their heterogeneous specifications. To address this problem, slicing has emerged as an architecture that enables a logical network with specific radio access functionality to each of the supported services on the same network infrastructure. The allocation of radio resources to each slice according to their requirements is a fundamental part of the network slicing that is usually executed at the radio access network (RAN). In this work, we formulate the RAN resource allocation problem as a sum-rate maximization problem subject to the orthogonality constraint (i.e., service isolation), latency-related constraint and minimum rate constraint while maintaining the reliability constraint with the incorporation of adaptive modulation and coding (AMC). However, the formulated problem is not mathematically tractable due to the presence of a step-wise function associated with the AMC and a binary assignment variable. Therefore, to solve the proposed optimization problem, first, we relax the mathematical intractability of AMC by using an approximation of the non-linear AMC achievable throughput, and next, the binary constraint is relaxed to a box constraint by using the penalized reformulation of the problem. The result of the above two-step procedure provides a close-to-optimal solution to the original optimization problem. Furthermore, to ease the complexity of the optimization-based scheduling algorithm, a low-complexity heuristic scheduling scheme is proposed for the efficient multiplexing of URLLC and eMBB services. Finally, the effectiveness of the proposed optimization and heuristic schemes is illustrated through extensive numerical simulations. [less ▲]

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See detailStructured Compression of Deep Neural Networks with Debiased Elastic Group LASSO
Oyedotun, Oyebade UL; Aouada, Djamila UL; Ottersten, Björn UL

in IEEE 2020 Winter Conference on Applications of Computer Vision (WACV 20), Aspen, Colorado, US, March 2–5, 2020 (2020, March 01)

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See detailHybrid Analog-Digital Transceiver Designs for Multi-User MIMO mmWave Cognitive Radio Systems
Tsinos, Christos UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Cognitive Communications and Networking (2020)

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See detailVertex Feature Encoding and Hierarchical Temporal Modeling in a Spatio-Temporal Graph Convolutional Network for Action Recognition
Papadopoulos, Konstantinos UL; Ghorbel, Enjie UL; Aouada, Djamila UL et al

in International Conference on Pattern Recognition, Milan 10-15 January 2021 (2020)

Detailed reference viewed: 117 (24 UL)