Queue stability analysis in network coded wireless multicast.

In this dissertation queue stability in wireless multicast networks with packet erasure channels is studied. Our focus is on optimizing packet scheduling so as to maximize throughput. Specifically, new queuing strategies consisting of several sub-queues are introduced, where all newly arrived packets are first stored in the main sub-queue on a first-come-first-served basis. Using the receiver feedback, the transmitter combines packets from different sub-queues for transmission. Our objective is to maximize the input rate under the queue stability constraints. Two packet scheduling and encoding algorithms have been developed. First, the optimization problem is formulated as a linear programming (LP) problem, according to which a network coding based optimal packet scheduling scheme is obtained. Second, the Lyapunov optimization model is adopted and decision variables are defined to derive a network coding based packet scheduling algorithm, which has significantly less complexity and smaller queue backlog compared with the LP solution. Further, an extension of the proposed algorithm is derived to meet the requirements of time-critical data transmission, where each packet expires after a predefined deadline and then dropped from the system. To minimize the average transmission power, we further derive a scheduling policy that simultaneously minimizes both power and queue size, where the transmitter may choose to be idle to save energy consumption. Moreover, a redundancy in the schedules is inadvertently revealed by the algorithm. By detecting and removing the redundancy we further reduce the system complexity. Finally, the simulation results verify the effectiveness of our proposed algorithms over existing works

Scheduling and Power Control for Wireless Multicast Systems via Deep Reinforcement Learning

Multicasting in wireless systems is a natural way to exploit the redundancy in user requests in a Content Centric Network. Power control and optimal scheduling can significantly improve the wireless multicast network's performance under fading. However, the model based approaches for power control and scheduling studied earlier are not scalable to large state space or changing system dynamics. In this paper, we use deep reinforcement learning where we use function approximation of the Q-function via a deep neural network to obtain a power control policy that matches the optimal policy for a small network. We show that power control policy can be learnt for reasonably large systems via this approach. Further we use multi-timescale stochastic optimization to maintain the average power constraint. We demonstrate that a slight modification of the learning algorithm allows tracking of time varying system statistics. Finally, we extend the multi-timescale approach to simultaneously learn the optimal queueing strategy along with power control. We demonstrate scalability, tracking and cross layer optimization capabilities of our algorithms via simulations. The proposed multi-timescale approach can be used in general large state space dynamical systems with multiple objectives and constraints, and may be of independent interest.Comment: arXiv admin note: substantial text overlap with arXiv:1910.0530

Digital signal processing waveform aggregation and its experimental demonstration for next generation mobile fronthaul

L'abstract è presente nell'allegato / the abstract is in the attachmen

Demand-based optimization for adaptive multi-beam satellite communication systems

Satellite operators use multiple spot beams of high throughput satellite systems to provide internet services to broadband users. However, in recent years, new mobile broadband users with diverse demand requisites are growing, and satellite operators are obliged to provide services agreed in the Service Level Agreements(SLA) to remote rural locations, mid-air aeroplanes and mid-ocean ships. Furthermore, the expected demand is spatio-temporal which varies along the geographical location of the mobile users with time and hence, creating more dynamic, non uniformly distributed, and time sensitive demand profiles. However, the current satellite systems are only designed to perform similarly irrespective of the changes in demand profiles. Hence, a practical approach to meet such heterogeneous demand is to design adaptive systems by exploiting the advancements in recently developed technologies such as precoding, active antenna array, digital beamforming networks, digital transparent payload and onboard signal processing. Accordingly, in this work, we investigate and develop advanced demand-based resource optimization modules that fit future payload capabilities and satisfy the satellite operators’ interests. Furthermore, instead of boosting the satellite throughput (capacity maximization), the goal is to optimize the available resources such that the satellite offered capacity on the ground continuously matches the geographic distribution of the traffic demand and follows its variations in time. However, we can introduce adaptability at multiple levels of the transmission chain of the satellite system, either with long term flexibility (optimization over frequency, time, power, beam pattern and footprint) or short term flexibility (optimization over user scheduling). These techniques can be optimized as either standalone or in parallel or even jointly for maximum demand satisfaction. However, in the scope of this thesis, we have designed real time optimizations only for some of the radio resource schemes. Firstly, we explore beam densification, where by increasing the number of beams, we improve the antenna gain values at the high demand hot-spot regions. However, such increase in the number of beams also increase the interbeam interference and badly affects SINR performance. Hence, in the first part of Chapter 2 of this thesis, we focus on finding an optimal number of beams for given high demand hot-spot region of a demand distribution profile. Also, steering the beams towards high demand regions, further increase the demand satisfaction. However, the positioning of the beams need to be carefully planned. On one hand, closely placed beams result in poor SINR performance. On the other hand, beams that are placed far away will have poor antenna gain values for the users away from the beam centers. Hence, in the second part of Chapter 2, we focus on finding optimized beam positions for maximum demand satisfaction in high demand hot-spot regions. Also, we propose a dynamic frequency-color coding strategy for efficient spectrum and interference management in demand-driven adaptive systems. Another solution is the proposed so-called Adaptive Multi-beam Pattern and Footprint (AMPF) design, where we fix the number of beams and based on the demand profile, we configure adaptive beam shapes and sizes along with their positions. Such an approach shall distribute the total demand across all the beams more evenly avoiding overloaded or underused beams. Such optimization was attempted in Chapter 3 using cluster analysis. Furthermore, demand satisfaction at both beam and user level was achieved by carefully performing demand driven user scheduling. On one hand, scheduling most orthogonal users at the same time may yield better capacity but may not provide demand satisfaction. This is majorly because users with high demand need to be scheduled more often in comparison to users with low demand irrespective of channel orthogonality. On the other hand, scheduling users with high demand which are least orthogonal, create strong interbeam interference and affect precoding performance. Accordingly, two demand driven scheduling algorithms (Weighted Semi-orthogonal scheduling (WSOS) and Interference-aware demand-based user scheduling) are discussed in Chapter 4. Lastly, in Chapter 5, we verified the impact of parallel implementation of two different demand based optimization techniques such as AMPF design and WSOS user scheduling. Evidently, numerical results presented throughout this thesis validate the effectiveness of the proposed demand based optimization techniques in terms of demand matching performance compared to the conventional non-demand based approaches

Application of network coding in satellite broadcast and multiple access channels

Satellite broadcasting and relaying capabilities enable mobile broadcast systems over wide geographical areas, which opens large market possibilities for handheld, vehicular and fixed user terminals. The geostationary (GEO) satellite orbit is highly suited for such applications, as it spares the need for satellite terminals to track the movement of the spacecraft, with important savings in terms of complexity and cost. The large radius of the GEO orbit (more than 40000 km) has two main drawbacks. One is the large free space loss experienced by a signal traveling to or from the satellite, which limits the signal-to-noise ratio (SNR) margins in the link budget with respect to terrestrial systems. The second drawback of the GEO orbit is the large propagation delay (about 250 msec) that limits the use of feedback in both the forward (satellite to satellite terminal) and the reverse (satellite terminal to satellite) link. The limited margin protection causes loss of service availability in environments where there is no direct line of sight to the satellite, such as urban areas. The large propagation delay on its turn, together with the large terminal population size usually served by a GEO satellite, limit the use of feedback, which is at the basis of error-control. In the reverse link, especially in the case of fixed terminals, packet losses are mainly due to collisions, that severely limit the access to satellite services in case a random access scheme is adopted. The need for improvements and further understanding of these setups lead to the development of our work. In this dissertation we study the application of network coding to counteract the above mentioned channel impairments in satellite systems. The idea of using network coding stems from the fact that it allows to efficiently exploit the diversity, either temporal or spatial, present in the system. In the following we outline the original contributions included in each of the chapters of the dissertation. Chapter 3. This chapter deals with channel impairments in the forward link, and specifically with the problem of missing coverage in Urban environments for land mobile satellite (LMS) networks. By applying the Max-flow Min-cut theorem we derive a lower bound on the maximum coverage that can be achieved through cooperation. Inspired by this result, we propose a practical scheme, keeping in mind the compatibility with the DVB-SH standard. We developed a simulator in Matlab/C++ based on the physical layer abstraction and used it to test the performance gain of our scheme with a benchmark relaying scheme that does allow coding at packet level. Chapter 4. The second chapter of contributions is devoted to the information theoretical study of real-time streaming transmissions over fading channels with channel state information at the transmitter only. We introduce this new channel model and propose several transmission schemes, one of which is proved to be asymptotically optimal in terms of throughput. We also provide an upper bound on the achievable throughput for the proposed channel model and compare it numerically with the proposed schemes over a Rayleigh fading channel. Chapter 5. Chapter 5 is devoted to the study of throughput and delay in non-real-time streaming transmission over block fading channels. We derive bounds on the throughput and the delay for this channel and propose different coding techniques based on time-sharing. For each of them we carry out an analytical study of the performance. Finally, we compare numerically the performance of the proposed schemes over a Rayleigh fading channel. Chapter 6. In the last technical chapter we propose a collision resolution method for the return link based on physical layer network coding over extended Galois field (EGF). The proposed scheme extracts information from the colliding signals and achieves important gains with respect to Slotted ALOHA systems as well as with respect to other collision resolution schemes.Una de les característiques mes importants de les plataformes de comunicacions per satèl.lit és la seva capacitat de retransmetre senyals rebuts a un gran número de terminals. Això es fonamental en contextes com la difusió a terminals mòbils o la comunicació entre màquines. Al mateix temps, la disponibilitat d’un canal de retorn permet la creació de sistemes de comunicacions per satèl.lit interactius que, en principi, poden arribar a qualsevol punt del planeta. Els satèl.lits Geoestacionaris son particularment adequats per a complir amb aquesta tasca. Aquest tipus de satèl.lits manté una posició fixa respecte a la Terra, estalviant als terminals terrestres la necessitat de seguir el seu moviment en el cel. Per altra banda, la gran distància que separa la Terra dels satèl.lits Geoestacionaris introdueix grans retrassos en les comunicacions que, afegit al gran número de terminals en servei, limita l’ús de tècniques de retransmissió basades en acknowledgments en cas de pèrdua de paquets. Per tal de sol.lucionar el problema de la pèrdua de paquets, les tècniques més utilitzades son el desplegament de repetidors terrestres, anomenats gap fillers, l’ús de codis de protecció a nivell de paquet i mecanismes proactius de resolució de col.lisions en el canal de retorn. En aquesta tesi s’analitzen i s’estudien sol.lucions a problemes en la comunicació per satèl.lit tant en el canal de baixada com el de pujada. En concret, es consideren tres escenaris diferents. El primer escenari es la transmissió a grans poblacions de terminals mòbils en enorns urbans, que es veuen particularment afectats per la pèrdua de paquets degut a l’obstrucció, per part dels edificis, de la línia de visió amb el satèl.lit. La sol.lució que considerem consisteix en la utilització de la cooperació entre terminals. Una vegada obtinguda una mesura del guany que es pot assolir mitjançant cooperació en un model bàsic de xarxa, a través del teorema Max-flow Min-cut, proposem un esquema de cooperació compatible amb estàndards de comunicació existents. El segon escenari que considerem es la transmissió de vídeo, un tipus de tràfic particularment sensible a la pèrdua de paquets i retards endògens als sistemes de comunicació per satèl.lit. Considerem els casos de transmissió en temps real i en diferit, des de la perspectiva de teoria de la informació, i estudiem diferents tècniques de codificació analítica i numèrica. Un dels resultats principals obtinguts es l’extensió del límit assolible de la capacitat ergòdica del canal en cas que el transmissor rebi les dades de manera gradual, enlloc de rebre-les totes a l’inici de la transmissió. El tercer escenari que considerem es l’accés aleatori al satèl.lit. Desenvolupem un esquema de recuperació dels paquets perduts basat en la codificació de xarxa a nivell físic i en extensions a camps de Galois, amb resultats molt prometedors en termes de rendiment. També estudiem aspectes relacionats amb la implementació pràctica d’aquest esquema

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Data Acquisition Applications

Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

Demystifying Internet of Things Security

Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms