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Multiterminal source coding: sum-rate loss, code designs, and applications to video sensor networksYang, Yang 15 May 2009 (has links)
Driven by a host of emerging applications (e.g., sensor networks and wireless video),
distributed source coding (i.e., Slepian-Wolf coding, Wyner-Ziv coding and various other
forms of multiterminal source coding), has recently become a very active research area.
This dissertation focuses on multiterminal (MT) source coding problem, and consists
of three parts. The first part studies the sum-rate loss of an important special case
of quadratic Gaussian multi-terminal source coding, where all sources are positively symmetric
and all target distortions are equal. We first give the minimum sum-rate for joint
encoding of Gaussian sources in the symmetric case, and then show that the supremum of
the sum-rate loss due to distributed encoding in this case is 1
2 log2
5
4 = 0:161 b/s when L = 2
and increases in the order of
º
L
2 log2 e b/s as the number of terminals L goes to infinity.
The supremum sum-rate loss of 0:161 b/s in the symmetric case equals to that in general
quadratic Gaussian two-terminal source coding without the symmetric assumption. It is
conjectured that this equality holds for any number of terminals.
In the second part, we present two practical MT coding schemes under the framework
of Slepian-Wolf coded quantization (SWCQ) for both direct and indirect MT problems.
The first, asymmetric SWCQ scheme relies on quantization and Wyner-Ziv coding, and it
is implemented via source splitting to achieve any point on the sum-rate bound. In the second,
conceptually simpler scheme, symmetric SWCQ, the two quantized sources are compressed
using symmetric Slepian-Wolf coding via a channel code partitioning technique that is capable of achieving any point on the Slepian-Wolf sum-rate bound. Our practical
designs employ trellis-coded quantization and turbo/LDPC codes for both asymmetric and
symmetric Slepian-Wolf coding. Simulation results show a gap of only 0.139-0.194 bit per
sample away from the sum-rate bound for both direct and indirect MT coding problems.
The third part applies the above two MT coding schemes to two practical sources, i.e.,
stereo video sequences to save the sum rate over independent coding of both sequences.
Experiments with both schemes on stereo video sequences using H.264, LDPC codes for
Slepian-Wolf coding of the motion vectors, and scalar quantization in conjunction with
LDPC codes for Wyner-Ziv coding of the residual coefficients give slightly smaller sum
rate than separate H.264 coding of both sequences at the same video quality.
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Optimisation multicritères de la qualité de service dans les réseaux de capteurs multimédia sans fil / Multicriteria optimization of the quality of service in the wireless multimedia sensor networksAlaoui Fdili, Othmane 10 June 2015 (has links)
Les progrès réalisés en systèmes micro-électro-mécaniques couplés avec leur convergence vers les systèmes de communication sans fil, ont permis l'émergence des réseaux de capteurs sans fil (RCSF). Les contraintes de ces réseaux font que tous les efforts soient fournis pour proposer des solutions économes en énergie. Avec les récents développements des technologies CMOS, des capteurs d'images à faible coût ont été développés. En conséquence, un nouveau dérivé des RCSF, qui sont les Réseaux de Capteurs Vidéo Sans Fil (RCVSF), a été proposé. La particularité des données vidéo ainsi que les contraintes inhérentes aux nœuds ont introduit de nouveaux défis. Dans cette thèse, nous proposons deux solutions basées sur l'approche inter-couches pour la livraison de la vidéo sur les RCVSF. La première solution propose un nouveau schéma de compression vidéo adaptatif, efficace en énergie et basé sur la norme de compression vidéo H.264/AVC. Le flux vidéo est ensuite géré par une version améliorée du protocole MMSPEED que nous proposons et notons EQBSA-MMSPEED. Les résultats des simulations montrent que la durée de vie du réseau est étendue de 33%, tout en améliorant la qualité du flux vidéo reçu de 12%. Dans la deuxième solution, nous enrichissons le schéma de compression de modèles mathématiques pour prévoir la consommation d'énergie et la distorsion de l'image lors des phases d'encodage et de transmission. Le flux vidéo est géré par un nouveau protocole de routage efficace en énergie et à fiabilité améliorée noté ERMM. Comparée à une approche basique, cette solution réalise une extension de la durée de vie du réseau de 15%, tout en améliorant la qualité du flux vidéo reçu de 35%. / Thanks to the valuable advances in Micro Electro-Mechanical Systems coupled with their convergence to wireless communication systems, the Wireless Sensor Networks (WSN). In the WSN context, all the efforts are made in order to propose energy-efficient solutions. With the recent developments in CMOS technology, low-cost imaging sensors have been developed. As a result, a new derivative of the WSN, which is the Wireless Video Sensor Network (WVSN), has been proposed. The particularities of the video data as well as the inherent constraints of the nodes have introduced new challenges. In this thesis, we propose two cross-layer based solutions for video delivery over the WVSN. The first solution proposes a new energy efficient and adaptive video compression scheme dedicated to the WVSNs, based on the H.264/AVC video compression standard. The video stream is then handled by an enhanced version of MMSPEED protocol, that we propose and note EQBSA-MMSPEED. Performance evaluation shows that the lifetime of the network is extended by 33%, while improving the video quality of the received stream by 12%. In the second solution, we enrich our compression scheme with mathematical models to predict the energy consumption and the video distortion during the encoding and the transmission phases. The video stream is then handled by a novel energy efficient and improved reliability routing protocol, that we note ERMM. Compared to a basic approach, this solution is extending the network lifetime by 15%, while improving the quality of the received video stream by 35%.
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