ALBERT

Beschreibung: The H.264/AVC video coding standard introduces some improved tools in order to increase compression efficiency. Moreover, the multi-view extension of H.264/AVC, called H.264/MVC, adopts many of them. Among the new features, variable block-size motion estimation is one which contributes to high coding efficiency. Furthermore, it defines a different prediction structure that includes hierarchical bidirectional pictures, outperforming traditional Group of Pictures patterns in both scenarios: single-view and multi-view. However, these video coding techniques have high computational complexity. Several techniques have been proposed in the literature over the last few years which are aimed at accelerating the inter prediction process, but there are no works focusing on bidirectional prediction or hierarchical prediction. In this article, with the emergence of many-core processors or accelerators, a step forward is taken towards an implementation of an H.264/AVC and H.264/MVC inter prediction algorithm on a graphics processing unit. The results show a negligible rate distortion drop with a time reduction of up to 98% for the complete H.264/AVC encoder.

Beschreibung: Recordings of neural activity, such as EEG, are an inherent mixture of different ongoing brain processes as well as artefacts and are typically characterised by low signal-to-noise ratio. Moreover, EEG datasets are often inherently multidimensional, comprising information in time, along different channels, subjects, trials, etc. Additional information may be conveyed by expanding the signal into even more dimensions, e.g. incorporating spectral features applying wavelet transform. The underlying sources might show differences in each of these modes. Therefore, tensor-based blind source separation techniques which can extract the sources of interest from such multiway arrays, simultaneously exploiting the signal characteristics in all dimensions, have gained increasing interest. Canonical polyadic decomposition (CPD) has been successfully used to extract epileptic seizure activity from wavelet-transformed EEG data (Bioinformatics 23(13):i10-i18, 2007; NeuroImage 37:844-854, 2007), where each source is described by a rank-1 tensor, i.e. by the combination of one particular temporal, spectral and spatial signature. However, in certain scenarios, where the seizure pattern is nonstationary, such a trilinear signal model is insufficient. Here, we present the application of a recently introduced technique, called block term decomposition (BTD) to separate EEG tensors into rank-(Lr,Lr, 1) terms, allowing to model more variability in the data than what would be possible with CPD. In a simulation study, we investigate the robustness of BTD against noise and different choices of model parameters. Furthermore, we show various real EEG recordingswhere BTD outperforms CPD in capturing complex seizure characteristics.

Beschreibung: Unequal error protection (UEP) codes provide a selective level ofprotection for different blocks of the information message. Theeffectiveness of two sub-optimum soft-decision decoding algorithms,namely generalized Chase-2 and weighted erasure decoding, isevaluated in this study for each protection class of UEP blockcodes. The performances of both algorithms are compared to that ofthe maximum likelihood algorithm in order to evaluate theperformance loss of each protection class provided by less complexalgorithms as well as their complexities are evaluated according tothe number of arithmetic operations performed at each decoding step.Finally, numerical results and examples are provided which indicatethat a trade-off between performance and complexity for eachprotection class is obtained. The results of this study can be usedto select appropriate UEP coding and decoding schemes inapplications that demand low energy consumption.

Beschreibung: The use of reflected Global Navigation Satellite System (GNSS) signals for sensing the Earth has been growing rapidly in recent years. This technique is founded on the basic principle of detecting GNSS signals after they have been reflected off the Earth's surface and using them to determine the properties of the reflecting surface remotely. This is the so-called GNSS reflectometry (GNSS-R) technique. In this paper, a new application regarding the detection of metallic buried objects is analyzed and it is validated through several experimental campaigns. Although the penetration depth of GNSS signals into the ground is not optimal and depends on the soil moisture, GNSS signals can likely interact approximately with the first 10 cm of the ground and therefore can be reflected back by any metallic object buried on the first terrain layer. A very light and low-cost GNSS receiver prototype based on a software-defined radio approach was developed. This receiver can be used as a payload on board small drones or unmanned aerial systems to detect metallic objects (mines or other explosive devices). A signal processing tool based on an open-loop GNSS signal acquisition strategy was developed. The results of two experiments which show the possibility of using GNSS-R signals to detect buried metallic objects and to provide an estimate of their dimensions are discussed.

Beschreibung: This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filterbank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reductionactive constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing(OFDM), to an FBMC implementation as the main contribution.The four techniques introduced can be split up into two: linear programming optimizationACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming(LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach andprovide a theoretical upper bound on achievable performance for the overlapping ACE techniques.The overlapping ACE techniques on the other hand can handle symbol by symbol processing.Furthermore, as a result of FBMC properties, the proposed techniques do not require sideinformation transmission. The PAPR performance of the techniques is shown to match, or in somecases improve, on current PAPR techniques for FBMC. Initial analysis of the computationalcomplexity of the SGP techniques indicates that the complexity issues with PAPR reduction inFBMC implementations can be addressed.The out-of-band interference introduced by the techniques is investigated. As a result, it is shownthat the interference can be compensated for, whilst still maintaining decent PAPR performance.Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated toensure that the trade-off in terms of BER degradation is not too severe.As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are idealcandidates for practical implementation in systems employing the low-complexity polyphaseimplementation of FBMC modulators. The methods are shown to offer significant PAPR reductionand increase the feasibility of FBMC as a replacement modulation system for OFDM.

Beschreibung: In this paper, we consider the schedule-based network localization concept, which does not requiresynchronization among nodes and does not involve communication overhead. The concept makesuse of a common transmission sequence, which enables each node to perform self-localization andto localize the entire network, based on noisy propagation-time measurements. We formulate theschedule-based localization problem as an estimation problem in a Bayesian framework. This pro-vides robustness with respect to uncertainty in such system parameters as anchor locations and timingdevices. Moreover, we derive a sequential approximate maximum a posteriori (AMAP) estimator.The estimator is fully decentralized and copes with varying noise levels. By studying the fundamentalconstraints given by the considered measurement model, we provide a system design methodologywhich enables a scalable solution. Finally, we evaluate the performance of the proposed AMAPestimator by numerical simulations emulating an impulse-radio ultra-wideband (IR-UWB) wirelessnetwork.