References of "Ottersten, Björn 50002797"
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See detailA Multicast Approach for Constructive Interference Precoding in MISO Downlink Channel
Alodeh, Maha UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE International Symposium on Information Theory (ISIT) (2014)

This paper studies the concept of jointly utilizing the data information (DI) and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO ... [more ▼]

This paper studies the concept of jointly utilizing the data information (DI) and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO) downlink channel. In this direction, the interference among the simultaneous data streams is transformed to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmissions (MRT) based algorithm that jointly exploits DI and CSI to gain the benefits from these useful signals. In this context, a novel framework to minimize the power consumption is proposed by formalizing the duality between the constructive interference downlink channel and the multicast channels. The numerical results have shown that the proposed schemes outperform other state of the art techniques. [less ▲]

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See detailSurface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras
Aouada, Djamila UL; Al Ismaeil, Kassem UL; Kedir Idris, Kedija et al

in 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14) (2014)

We address the limitation of low resolution depth cameras in the context of face recognition. Considering a face as a surface in 3-D, we reformulate the recently proposed Upsampling for Precise ... [more ▼]

We address the limitation of low resolution depth cameras in the context of face recognition. Considering a face as a surface in 3-D, we reformulate the recently proposed Upsampling for Precise Super–Resolution algorithm as a new approach on three dimensional points. This reformulation allows an efficient implementation, and leads to a largely enhanced 3-D face reconstruction. Moreover, combined with a dedicated face detection and representation pipeline, the proposed method provides an improved face recognition system using low resolution depth cameras. We show experimentally that this system increases the face recognition rate as compared to directly using the low resolution raw data. [less ▲]

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See detailMulticast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications
Christopoulos, Dimitrios; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2014), 14(9), 4695--4707

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to ... [more ▼]

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards. [less ▲]

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See detailConvergence of the Huber Regression M-Estimate in the Presence of Dense Outliers
Tsakonas, Efthymios; Jaldén, Joakim; Sidiropoulos, Nicholas D. et al

in IEEE Signal Processing Letters (2014), 21(11), 1211-1214

We consider the problem of estimating a deterministic unknown vector which depends linearly on noisy measurements, additionally contaminated with (possibly unbounded) additive outliers. The measurement ... [more ▼]

We consider the problem of estimating a deterministic unknown vector which depends linearly on noisy measurements, additionally contaminated with (possibly unbounded) additive outliers. The measurement matrix of the model (i.e., the matrix involved in the linear transformation of the sought vector) is assumed known, and comprised of standard Gaussian i.i.d. entries. The outlier variables are assumed independent of the measurement matrix, deterministic or random with possibly unknown distribution. Under these assumptions we provide a simple proof that the minimizer of the Huber penalty function of the residuals converges to the true parameter vector with a root n-rate, even when outliers are dense, in the sense that there is a constant linear fraction of contaminated measurements which can be arbitrarily close to one. The constants influencing the rate of convergence are shown to explicitly depend on the outlier contamination level. [less ▲]

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See detailIndex assignment for multiple description repair in distributed storage systems
Kapetanovic, Dzevdan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in ICC 2014 (2014)

Distributed storage systems have been receiving increasing attention lately due to the developments in cloud and grid computing. Furthermore, a major part of the stored information comprises of multimedia ... [more ▼]

Distributed storage systems have been receiving increasing attention lately due to the developments in cloud and grid computing. Furthermore, a major part of the stored information comprises of multimedia, whose content can be communicated even with a lossy (non-perfect) reconstruction. In this context, Multiple Description Lattice Quantizers (MDLQ) can be employed to encode such sources for distributed storage and store them across distributed nodes. Their inherent properties yield that having access to all nodes gives perfect reconstruction of the source, while the reconstruction quality decreases gracefully with fewer available nodes. If a set of nodes fails, lossy repair techniques could be applied to reconstruct the failed nodes from the available ones. This problem has mostly been studied with the lossless (perfect) reconstruction assumption. In this work, a general model, Multiple Description Lattice Quantizer with Repairs (MDLQR), is introduced that encompasses the lossy repair problem for distributed storage applications. New performance measures and repair techniques are introduced for MDLQR, and a non-trivial identity is derived, which is related to other results in the literature. This enables us to find the optimal encoder for a certain repair technique used in the MDLQR. Furthermore, simulation results are used to evaluate the performance of the different repair techniques. © 2014 IEEE. [less ▲]

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See detailStatistical Framework for Optimization in the Multi-User MIMO Uplink With ZF-DFE
Järmyr, Simon; Ottersten, Björn UL; Jorswieck, Eduard A.

in IEEE Transactions on Signal Processing (2014), 62(10), 2730-2745

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially ... [more ▼]

We consider performance optimization in the uplink of a multiuser multiantenna communication system. Each user multiplexes data onto several independently encoded data streams, which are spatially precoded and conveyed over a fading narrowband multiple-input multiple-output (MIMO) channel. All users' data streams are decoded successively at the receiving base station using zero-forcing decision feedback equalization (ZF-DFE). We target the joint optimization of a decoding order and linear precoders for all users based on long-term channel information. For a class of general MIMO channel models, including the separable-correlation and double-scattering models, we show that the choice of precoder for a certain user does not affect the performance of the others. This leads to a particularly straightforward characterization of general user utility regions as a polyblock, or a convex polytope if time-sharing is allowed. We formulate the decoding-ordering problem under transmit-correlated Rayleigh fading as a linear assignment problem, enabling the use of existing efficient algorithms. Combining decoding ordering with single-user precoder optimization by means of alternating optimization, we propose an efficient iterative scheme that is verified numerically to converge fast and perform close to optimally, successfully reaping the benefits of both precoding and ordering in the MIMO uplink. [less ▲]

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See detailImproving Credit Card Fraud Detection with Calibrated Probabilities
Correa Bahnsen, Alejandro UL; Stojanovic, Aleksandar UL; Aouada, Djamila UL et al

in Proceedings of the fourteenth SIAM International Conference on Data Mining, Philadelphia, Pennsylvania, USA, April 24-26, 2014. (2014)

Previous analysis has shown that applying Bayes minimum risk to detect credit card fraud leads to better results measured by monetary savings, as compared with traditional methodologies. Nevertheless ... [more ▼]

Previous analysis has shown that applying Bayes minimum risk to detect credit card fraud leads to better results measured by monetary savings, as compared with traditional methodologies. Nevertheless, this approach requires good probability estimates that not only separate well between positive and negative examples, but also assess the real probability of the event. Unfortunately, not all classification algorithms satisfy this restriction. In this paper, two different methods for calibrating probabilities are evaluated and analyzed in the context of credit card fraud detection, with the objective of finding the model that minimizes the real losses due to fraud. Even though under-sampling is often used in the context of classification with unbalanced datasets, it is shown that when probabilistic models are used to make decisions based on minimizing risk, using the full dataset provides significantly better results. In order to test the algorithms, a real dataset provided by a large European card processing company is used. It is shown that by calibrating the probabilities and then using Bayes minimum Risk the losses due to fraud are reduced. Furthermore, because of the good overall results, the aforementioned card processing company is currently incorporating the methodology proposed in this paper into their fraud detection system. Finally, the methodology has been tested on a different application, namely, direct marketing. [less ▲]

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See detailKinectDeform: Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects
Afzal, Hassan UL; Al Ismaeil, Kassem UL; Aouada, Djamila UL et al

in Second International Conference on 3D Vision (2014)

In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of scenes containing non-rigidly deforming objects. It provides an innovation to the existing class of ... [more ▼]

In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of scenes containing non-rigidly deforming objects. It provides an innovation to the existing class of algorithms which either target scenes with rigid objects only or allow for very limited non-rigid deformations or use pre-computed templates to track them. KinectDeform combines a fast non-rigid scene tracking algorithm based on octree data representation and hierarchical voxel associations with a recursive data filtering mechanism. We analyze its performance on both real and simulated data and show improved results in terms of smoothness and feature preserving 3D reconstructions with reduced noise. [less ▲]

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See detailCPU-based real-time surface and solid voxelization for incomplete point cloud
Garcia, Frederic D.; Ottersten, Björn UL

in Proceedings of the 22nd International Conference on Pattern Recognition (2014)

This paper presents a surface and solid voxelization approach for incomplete point cloud datasets. Voxelization stands for a discrete approximation of 3-D objects into a volumetric representation, a ... [more ▼]

This paper presents a surface and solid voxelization approach for incomplete point cloud datasets. Voxelization stands for a discrete approximation of 3-D objects into a volumetric representation, a process which is commonly employed in computer graphics and increasingly being used in computer vision. In contrast to surface voxelization, solid voxelization not only set those voxels related to the object surface but also those voxels considered to be inside the object. To that end, we first approximate the given point set, usually describing the external object surface, to an axis-aligned voxel grid. Then, we slice-wise construct a shell containing all surface voxels along each grid-axis pair. Finally, voxels inside the constructed shell are set. Solid voxelization results from the combination of all slices, resulting in a watertight and gap-free representation of the object. The experimental results show a high performance when voxelizing point cloud datasets, independently of the object's complexity, robust to noise, and handling large portions of data missing. © 2014 IEEE. [less ▲]

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See detailMultiobjective Signal Processing Optimization : The way to balance conflicting metrics in 5G systems
Bjornson, Emil; Jorswieck; Debbah et al

in IEEE Signal Processing Magazine (2014), 31(6), 14-23

The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved ... [more ▼]

The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a Wi-Fi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years [1], as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for fifth-generation (5G) networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency (EE), lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence of multiple objectives and tradeoffs between them. [less ▲]

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See detailFull frequency reuse multibeam satcoms: frame based precoding and user scheduling
Christopoulos, Dimitrios; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Submitted to IEEE Transactions on Wireless Communications, available (2014)

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See detailCoordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency
He, Shiwen; Huang, Yongming; Yang, Luxi et al

in IEEE Transactions on Signal Processing (2014), 62(3), 741-751

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser ... [more ▼]

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency. [less ▲]

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See detailModulation and Coding Classification for Adaptive Power Control in 5G Cognitive Communications
Tsakmalis, Anestis UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Proceedings of IEEE International Workshop on Signal Processing Advances in Wireless Communications 2014 (2014)

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See detailOptimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure [Lecture Notes]
Björnson, Emil; Bengtsson; Ottersten, Björn UL

in IEEE Signal Processing Magazine (2014), 31(4), 142-148

Transmit beamforming is a versatile technique for signal transmission from an array of antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the ... [more ▼]

Transmit beamforming is a versatile technique for signal transmission from an array of antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the intended user and reduce interference to nonintended users. A high signal power is achieved by transmitting the same data signal from all antennas but with different amplitudes and phases, such that the signal components add coherently at the user. Low interference is accomplished by making the signal components add destructively at nonintended users. This corresponds mathematically to designing beamforming vectors (that describe the amplitudes and phases) to have large inner products with the vectors describing the intended channels and small inner products with nonintended user channels. [less ▲]

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See detailAutomatic Modulation Classification for Adaptive Power Control in Cognitive Satellite Communications
Tsakmalis, Anestis UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Proceedings of 7th Advanced Satellite Multimedia Systems Conference (ASMS) and 13th Signal Processing for Space Communications Workshop (SPSC) 2014 (2014)

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See detailCompressive Sparsity Order Estimation for Wideband Cognitive Radio Receiver
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Signal Processing (2014)

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity ... [more ▼]

Compressive Sensing (CS) has been widely investigated in the Cognitive Radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity pattern. However, the sparsity order of the channel occupancy is time-varying and the sampling rate of the CS receiver needs to be adjusted based on its value in order to fully exploit the potential of CS-based techniques. In this context, investigating blind Sparsity Order Estimation (SOE) techniques is an open research issue. To address this, we study an eigenvalue-based compressive SOE technique using asymptotic Random Matrix Theory. We carry out detailed theoretical analysis for the signal plus noise case to derive the asymptotic eigenvalue probability distribution function (aepdf) of the measured signal’s covariance matrix for sparse signals. Subsequently, based on the derived aepdf expressions, we propose a technique to estimate the sparsity order of the wideband spectrum with compressive measurements using the maximum eigenvalue of the measured signal’s covariance matrix. The performance of the proposed technique is evaluated in terms of normalized SOE Error (SOEE). It is shown that the sparsity order of the wideband spectrum can be reliably estimated using the proposed technique for a variety of scenarios. [less ▲]

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See detailCognitive Interference Alignment for Spectral Coexistence
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Cognitive Radio and Networking for Heterogeneous Wireless Networks (2014)

Interference Alignment (IA) has been widely recognized as a promising interference mitigation technique since it can achieve the optimal degrees of freedom in certain interference limited channels. In the ... [more ▼]

Interference Alignment (IA) has been widely recognized as a promising interference mitigation technique since it can achieve the optimal degrees of freedom in certain interference limited channels. In the context of Cognitive Radio (CR) networks, this technique allows the coexistence of two heterogeneous wireless systems in an underlay cognitive mode. The main concept behind this technique is the alignment of the interference on a signal subspace in such a way that it can be filtered out at the non-intended receiver by sacrificing some signal dimensions. This chapter starts with an overview of IA principle, Degree of Freedom (DoF) concept, and the classification of existing IA techniques. Furthermore, this chapter includes a discussion about IA applications in CR networks.Moreover, a generic system model is presented for allowing the coexistence of two heterogeneous networks using IA approach while relevant precoding and filtering processes are described. In addition, two important practical applications of the IA technique are presented along with the numerical results for underlay spectral coexistence of (i) femtocell-macrocell systems, and (ii) monobeam-multibeam satellite systems. More specifically, an uplink IA scheme is investigated in order to mitigate the interference of femtocell User Terminals (UTs) towards the macrocell Base Station (BS) in the spatial domain and the interference of multibeam satellite terminals towards the monobeam satellite in the frequency domain. [less ▲]

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See detailRGB-D Multi-View System Calibration for Full 3D Scene Reconstruction
Afzal, Hassan UL; Aouada, Djamila UL; Fofi, David et al

in 22nd International Conference on Pattern Recognition (ICPR'14) (2014)

One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We ... [more ▼]

One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially. [less ▲]

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See detailInterference Mitigating Satellite Broadcast Receiver using Reduced Complexity List-Based Detection in Correlated Noise
Abu-Shaban, Zohair; Mehrpouyan, Hani; Ottersten, Björn UL et al

in arXiv preprint arXiv:1404.6544 (2014)

The recent commercial trends towards using smaller dish antennas for satellite receivers, and the growing density of broadcasting satellites, necessitate the application of robust adjacent satellite ... [more ▼]

The recent commercial trends towards using smaller dish antennas for satellite receivers, and the growing density of broadcasting satellites, necessitate the application of robust adjacent satellite interference (ASI) cancellation schemes. This orbital density growth along with the wider beamwidth of a smaller dish have imposed an overloaded scenario at the satellite receiver, where the number of transmitting satellites exceeds the number of receiving elements at the dish antenna. To ensure successful operation in this practical scenario, we propose a satellite receiver that enhances signal detection from the desired satellite by mitigating the interference from neighboring satellites. Towards this objective, we propose a reduced complexity list-based group-wise search detection (RC-LGSD) receiver under the assumption of spatially correlated additive noise. To further enhance detection performance, the proposed satellite receiver utilizes a newly designed whitening filter to remove the spatial correlation amongst the noise parameters, while also applying a preprocessor that maximizes the signal-to-interference-plus-noise ratio (SINR). Extensive simulations under practical scenarios show that the proposed receiver enhances the performance of satellite broadcast systems in the presence of ASI compared to existing methods [less ▲]

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See detailPerformance of the Multibeam Satellite Return Link With Correlated Rain Attenuation
Arnau, J.; Christopoulos, Dimitrios UL; Chatzinotas, Symeon UL et al

in Wireless Communications, IEEE Transactions on (2014), 13(11), 6286-6299

Rain attenuation is among the major impairments for satellite systems operating in the K-band and above. In this paper, we investigate the impact of spatially correlated rain attenuation on the ... [more ▼]

Rain attenuation is among the major impairments for satellite systems operating in the K-band and above. In this paper, we investigate the impact of spatially correlated rain attenuation on the performance of a multibeam satellite return link. For a comprehensive assessment, an analytical model for the antenna pattern that generates the beams is also proposed. We focus on the outage capacity of the link and obtain analytical approximations at high and low signal-to-noise ratio. The derived approximations provide insights into the effect of key system parameters such as the interuser distance, the satellite beam radius, or the rain intensity, and simulation results show that it fits tightly with the Monte Carlo results. Additionally, the derived expressions can be easily particularized for the single-user case, providing some novel insights. [less ▲]

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