Fourth Generation (4G) cellular technology Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) offers high data rate capabilities to mobile users; and, operators are trying to deliver a true mobile broadband experience over LTE networks. Mobile TV and Video on Demand (VoD) are expected to be the main revenue generators in the near future [36] and efficient video streaming over wireless is the key to enabling this. 3GPP recommends the use of H.264 baseline profiles for all video based services in Third Generation (3G) Universal Mobile Telecommunication System (UMTS) networks. However, LTE networks need to support mobile devices with different display resolution requirements like small resolution mobile phones and high resolution laptops. Scalable Video Coding (SVC) is required to achieve this goal. Feasibility study of SVC for LTE is one of the main agenda of 3GPP Release10. SVC enhances H.264 with a set of new profiles and encoding tools that may be used to produce scalable bit streams. Efficient adaptation methods for SVC video transmission over LTE networks are proposed in this thesis. Advantages of SVC over H.264 are analyzed using real time use cases of mobile video streaming. Further, we study the cross layer adaptation and scheduling schemes for delivering SVC video streams most efficiently to the users in LTE networks in unicast and multicast transmissions. We propose SVC based video streaming scheme for unicast and multicast transmissions in the downlink direction, with dynamic adaptations and a scheduling scheme based on channel quality information from users. Simulation results indicate improved video quality for more number of users in the coverage area and efficient spectrum usage with the proposed methods.

La croissance rapide du trafic aérien et les besoins en nouveaux services notamment pour les passagers imposent l'introduction de nouveaux moyens de communication pour les avions avec une bande passante globale fortement accrue. Les satellites sont appelés à jouer un rôle important dans ce contexte, non seulement en complément des systèmes terrestres pour les services « cockpit » (services ATM, Air Traffic Management) mais aussi pour les services « cabine » (In-Flight Entertainment). L'objectif de la thèse est d'étudier l'architecture d'un système satellite supportant l'ensemble de ces services, en se focalisant sur l'architecture du terminal embarqué à bord des aéronefs. L'architecture retenue repose sur des liaisons DVB-S2/DVB-RCS normalisées par l'ETSI. Cette option permet d'utiliser efficacement l'importante bande passante disponible en bande Ka pour les services mobiles aéronautiques (allocation primaire) ou en bande Ku (allocation secondaire). Ces normes ont été conçues pour les applications multimédia (Broadband Satellite Multimedia). Le défi est alors d'utiliser de telles liaisons satellite pour des services aux caractéristiques et besoins fortement hétérogènes. Par ailleurs, l'utilisation de la bande Ka n'est pas concevable sans l'activation de techniques de lutte contre les affaiblissements (FMT – Fade Mitigation Techniques). L'utilisation d'une marge statique conduit à une perte importante de capacité. Les techniques FMT reposent sur une évaluation dynamique du bilan de liaison et permettent une modification de la forme d'onde. Le système utilise ainsi la forme d'onde la plus efficace spectralement pour chaque terminal et maximise la capacité globale du système. Par contre, chaque terminal observe une modification de la ressource allouée au fil du temps. L'objectif de la thèse est de concevoir une architecture au niveau terminal qui permette d'exploiter les liaisons DVB-S2/RCS afin de fournir les services passagers (Internet et téléphonie mobile de type GSM/UMTS) et un canal haute fiabilité pour les services aéronautiques. Deux approches ont été retenues. La première repose sur une application du modèle ETSI BSM (Broadband Satellite Multimedia) en couches séparant strictement les couches dépendantes satellite et les couches indépendantes satellite. Les simulations de cette architecture montrent que les liaisons ne peuvent être utilisées de façon efficace sans une interaction entre couches afin de tenir compte de l'évolution de la capacité disponible. La seconde approche consiste en la concentration de la gestion de la ressource et la gestion de la qualité de service dans la même couche protocolaire. L'idée de départ est d'utiliser la méthode d'encapsulation générique Generic Stream Encapsulation (GSE). GSE a été conçu pour la projection des paquets de couches supérieures à l'intérieur des trames DVB-S2. GSE tient compte de la taille variable des trames DVB-S2 et introduit une capacité de multiplexage entre différents flux (identification de fragments). Sur cette base, une gestion de l'accès est introduite pour gérer la liaison DVB-RCS au format MF-TDMA. Nous introduisons ainsi une utilisation conjointe de GSE, d'une politique de service différentiée et de flux de signalisation inter-couches (« cross-layer »). Les performances des deux approches sont étudiées à l'aide d'un modèle de simulation développé à l'aide du logiciel OPNET Modeler (simulations à événements discrets). Les résultats obtenus démontrent le meilleur comportement de la seconde architecture avec une meilleure utilisation de la ressource et des performances de transmission satisfaisant les objectifs. / The rapid growth of air traffic needs a new communication infrastructure with increased bandwidth, high speed services and applications to satisfy expected air-ground communication requirements. Satellite communication systems play a significant role in this context, not only as a complement to terrestrial systems for Air Traffic Management (ATM) by offering global coverage but also as a promising solution to enrich In-Flight Entertainment (IFE) for passengers. DVB-S2/RCS technology is an attractive proposition to provide the cost-effective broadband services for both ATM and IFE, mainly because a large radio bandwidth is primarily allocated to aeronautical mobile communications in Ka-band, where the open standards DVB are implemented. However, such system design with convergence of heterogeneous traffics involves two main challenges. Firstly, using Ka-band means the implementation of Fade Mitigation Techniques (FMT) in order to cope with deep fades caused by atmospheric attenuation. Otherwise, the waste of capacity would be excessively high in a constant link margin design. FMT adapt in real time the link budget to the propagation conditions, this adaptivity has an impact not only on physical layer but also on upper layers. An efficient ressource management strategy with dynamic bandwidth allocation is required in this case, especially in DVB-RCS return link where FMT are not natives. Secondly, the proposed system must be able to multiplex the trafic flows with highly different characteristics and Quality of Service (QoS) expectations into a single link, the corresponding capacity management and QoS support seem with higher complexity. In this paper, we present an adaptive system design using a single DVB-S2/RCS based satellite link to provide Internet access and mobile telephony (GSM/UMTS) for passengers and a high-reliability channel for ATM. Concerning the airborne terminal architecture, two approaches are investigated. The first one is in compliance with ETSI Broadband Satellite Multimedia (BSM) architecture and based on a layering paradigm. The conducted simulation experiments highlight the need of dynamic interactions and adaptations among the layers to achieve an overall performance optimization. We propose then an enhanced approach with the concentration of both resource allocation and QoS management at the same interface – adaptation layer. The idea comes from the success of the recent Generic Stream Encapsulation (GSE) protocol, which carries the network protocol packets over DVB-S2 forward link in a simple, flexible and efficient way, especially when used with Adaptive Coding and Modulation (ACM). Furthermore, GSE can be easily extended to use in our design for DVB-RCS return link thanks to a proper design of MF-TDMA structure in which the suitable FMT (ACM and Dynamic Rate Adaptation) are context-aware configured. With the combined use of GSE, service policy and the interactions between adaptation and access layers, incoming heterogeneous traffics can be dynamically scheduled, segmented and encapsulated at the same adaptation layer. Performance evaluation of two proposed approaches is derived by a network-level simulation model developed using OPNET. Results prove the enhanced approach outperforms the first one leading to better resource utilization and satisfactory performance.

In this thesis, we investigate two different system infrastructures in underlay cognitive radio network, in which two popular techniques, cross-layer design and cooperative communication, are considered, respectively. In particular, we introduce the Aggressive Adaptive Modulation and Coding (A-AMC) into the cross-layer design and achieve the optimal boundary points in closed form to choose the AMC and A-AMC transmission modes by taking into account the Channel State Information (CSI) from the secondary transmitter to both the primary receiver and the secondary receiver. What’s more, for the cooperative communication design, we consider three different relay selection schemes: Partial Relay Selection, Opportunistic Relay Selection and Threshold Relay Selection. The Probability Density Functions (PDFs) of the Signal-to- Noise Ratio (SNR) in each hop for different selection schemes are provided, and then the exact closed-form expressions for the end-to-end packet loss rate in the secondary link considering the cooperation of the Decode-and-Forward (DF) relay for different relay selection schemes are derived.

We investigate diverse aspects of the performance of wireless networks, including throughput, delay and distributed complexity. <br />One of the main challenges for optimizing them arises from radio interference, an inherent factor in wireless networks.<br />Graph-based interference models represent a large class of interference models widely used for the study of wireless networks,<br />and suffer from the weakness of over-simplifying the interference caused by wireless signals in a local and binary way.<br />A more sophisticated interference model, the physical interference model, based on SINR constraints,<br />is considered more realistic but is more challenging to study (because of its non-linear form and non-local property).<br />In this dissertation, we study the connections between the two types of interference models -- graph-based and physical interference models --<br />and tackle a set of fundamental problems under the physical interference model;<br />previously, some of the problems were still open even under the graph-based interference model, and to those we have provided solutions under both types of interference models.<br /><br />The underlying interference models affect scheduling and power control -- essential building blocks in the operation of wireless networks -- that directly deal with the wireless medium; the physical interference model (compared to graph-based interference model) compounds the problem of efficient scheduling and power control by making it non-local and non-linear.<br />The system performance optimization and tradeoffs with respect to throughput and delay require a ``global\'\' view across<br />transport, network, media access control (MAC), physical layers (referred to as cross-layer optimization)<br />to take advantage of the control planes in different levels of the wireless network protocol stack.<br />This can be achieved by regulating traffic rates, finding traffic flow paths for end-to-end sessions,<br />controlling the access to the wireless medium (or channels),<br />assigning the transmission power, and handling signal reception under interference.<br /><br />The theme of the dissertation is<br />distributed algorithms and optimization of QoS objectives under the physical interference model.<br />We start by developing the first low-complexity distributed scheduling and power control algorithms for maximizing the efficiency ratio for different interference models;<br />we derive end-to-end per-flow delay upper-bounds for our scheduling algorithms and our delay upper-bounds are the first network-size-independent result known for multihop traffic.<br />Based on that, we design the first cross-layer multi-commodity optimization frameworks for delay-constrained throughput maximization by incorporating the routing and traffic control into the problem scope.<br />Scheduling and power control is also inherent to distributed computing of ``global problems\'\', e.g., the maximum independent set problems in terms of transmitting links and local broadcasts respectively, and the minimum spanning tree problems.<br />Under the physical interference model, we provide the first sub-linear time distributed solutions to the maximum independent set problems, and also solve the minimum spanning tree problems efficiently.<br />We develop new techniques and algorithms and exploit the availability of technologies (full-/half-duplex radios, fixed/software-defined power control) to further improve our algorithms.<br />%This fosters a deeper understanding of distributed scheduling from the network computing point of view.<br /><br /><br />We highlight our main technical contributions, which might be of independent interest to the design and analysis of optimization algorithms.<br />Our techniques involve the use of linear and mixed integer programs in delay-constrained throughput maximization. This demonstrates the combined use of different kinds of combinatorial optimization approaches for multi-criteria optimization.<br />We have developed techniques for queueing analysis under general stochastic traffic to analyze network throughput and delay properties.<br />We use randomized algorithms with rigorously analyzed performance guarantees to overcome the distributed nature of wireless data/control communications.<br />We factor in the availability of emerging radio technologies for performance improvements of our algorithms.<br />Some of our algorithmic techniques that would be of broader use in algorithms for the physical interference model include:<br />formal development of the distributed computing model in the SINR model, and reductions between models of different technological capabilities, the redefinition of interference sets in the setting of SINR constraints, and our techniques for distributed computation of rulings (informally, nodes or links which are well-separated covers).<br /> / Ph. D.

Ever since Marconi succeeded in his first demonstration on the possibility to communicate over the air overseas about a century ago, wireless communications have experienced dramatic improvements. Today's world sees the penetration of wireless communications into human life almost everywhere, from a simple remote control for TV to a cellular phone. With a better understanding of the adverse nature of the wireless propagation channels, engineers have been able to invent various clever techniques, i.e. Multiple Input Multiple Output (MIMO) technology, spread spectrum communications, Orthogonal Frequency Division Multiplexing (OFDM) to name a few, to achieve fast and reliable communications over each point-to-point link. Communications between multiple parties create networks. Limited Radio Frequency (RF) resources, e.g. transmit power, channel bandwidth, signaling time slots, etc., call for an optimal distribution of these resources among the users in the network. In this dissertation, two types of communication networks are of particular interest: cellular networks and mobile-relay-aided networks. For a symmetric cellular network, where a fixed communication infrastructure is assumed and each user has similar average Signal-to-Noise Ratio (SNR), we study the performance of a Maximum SNR (Max-SNR) scheduler, which schedules the strongest user for service, with the effects of channel estimation error, the Modulation and Coding Scheme (MCS), channel feedback delay, and Doppler shift all taken into account. The degradation of the throughput of a Max-SNR scheduler due to outdated channel knowledge for a system with large Doppler shift and asymmetric users is analyzed and mathematical derivations of the capacity of the system based upon an Auto-Regressive (AR) channel model are presented in the dissertation as well. Unlike the schedulers proposed in the literature, which instantaneously keep track of the strongest user, an optimal scheduler that operates on the properties of Doppler and the average SNR of each user is proposed. The high flexibility and easy deployment characteristics that Unmanned Aerial Vehicles (UAVs) possess endow them with the possibility to act as mobile relays to create secure and reliable communication links in severe environments. Unlike cellular communications, where the base stations are stationary, the mobility in a UAV-assisted network can be exploited to improve the quality of the communications. Herein, the deployment and optimal motion control problem for a mobile-relay-aided network is considered. A network protocol which achieves optimal throughput and maintains a certain Quality of Service (QoS) requirement is proposed from a cross-layer perspective. The handoff problem of the Access Point (AP) between various relays is studied and the effect of the mobility on the handoff algorithm is addressed.

The novelty of this dissertation is the optimization and acceleration of deep neural networks aimed at real-time predictions with minimal energy consumption. It consists of cross-layer optimization, output directed dynamic quantization, and opportunistic near-data computation for deep neural network acceleration. On two datasets (CIFAR-10 and CIFAR-100), the proposed deep neural network optimization and acceleration frameworks are tested using a variety of Convolutional neural networks (e.g., LeNet-5, VGG-16, GoogLeNet, DenseNet, ResNet). Experimental results are promising when compared to other state-of-the-art deep neural network acceleration efforts in the literature.

In recent years, the development of a large variety of mobile computing devices has led to wide scale deployment and use of wireless ad hoc and sensor networks. Wireless Sensor Networks consist of battery powered, tiny and cheap "motes", having sensing and wireless communication capabilities. Although wireless motes have limited battery power, communication and computation capabilities, the range of their application is vast. In the first part of the dissertation, we have addressed the specific application of Biomedical Sensor Networks. To solve the problem of data routing in these networks, we have proposed the Adaptive Least Temperature Routing (ALTR) algorithm that reduces the average temperature rise of the nodes in the in-vivo network while routing data efficiently. For delay sensitive biomedical applications, we proposed the Hotspot Preventing Routing (HPR) algorithm which avoids the formation of hotspots (regions having very high temperature) in the network. HPR forwards the packets using the shortest path, bypassing the regions of high temperature and thus significantly reduces the average packet delivery delay, making it suitable for real-time applications of in-vivo networks. We also proposed another routing algorithm suitable for being used in a network of id-less biomedical sensor nodes, namely Routing Algorithm for networks of homogeneous and Id-less biomedical sensor Nodes (RAIN). Finally we developed Biocomm, a cross-layer MAC and Routing protocol co-design for Biomedical Sensor Networks, which optimizes the overall performance of an in-vivo network through cross-layer interactions. We performed extensive simulations to show that the proposed Biocomm protocol performs much better than the other existing MAC and Routing protocols in terms of preventing the formation of hotspots, reducing energy consumption of nodes and preventing network congestion when used in an in-vivo network. In the second part of the dissertation, we have addressed the problems of habitat-monitoring sensor networks, broadcast algorithms for sensor networks and the congestion problem in sensor networks as well as one non-sensor network application, namely, on-chip communication networks. Specifically, we have proposed a variation of HPR algorithm, called Hotspot Preventing Adaptive Routing (HPAR) algorithm, for efficient data routing in Networks On-Chip catering to their specific hotspot prevention issues. A protocol similar to ALTR has been shown to perform well in a sensor network deployed for habitat monitoring. We developed a reliable, low overhead broadcast algorithm for sensor networks namely Topology Adaptive Gossip (TAG) algorithm. To reduce the congestion problem in Wireless Sensor Networks, we proposed a tunable cross-layer Congestion Reducing Medium Access Control (CRMAC) protocol that utilizes buffer status information from the Network layer to give prioritized medium access to congested nodes in the MAC layer and thus preventing congestion and packet drops. CRMAC can also be easily tuned to satisfy different application-specific performance requirements. With the help of extensive simulation results we have shown how CRMAC can be adapted to perform well in different applications of Sensor Network like Emergency Situation that requires a high network throughput and low packet delivery latency or Long-term Monitoring application requiring energy conservation.

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