Joint source-channel-network coding in wireless mesh networks with temporal reuse

Technological innovation that empowers tiny low-cost transceivers to operate with a high degree of utilisation efficiency in multihop wireless mesh networks is contributed in this dissertation. Transmission scheduling and joint source-channel-network coding are two of the main aspects that are addressed. This work focuses on integrating recent enhancements such as wireless network coding and temporal reuse into a cross-layer optimisation framework, and to design a joint coding scheme that allows for space-optimal transceiver implementations. Link-assigned transmission schedules with timeslot reuse by multiple links in both the space and time domains are investigated for quasi-stationary multihop wireless mesh networks with both rate and power adaptivity. Specifically, predefined cross-layer optimised schedules with proportionally fair end-to-end flow rates and network coding capability are constructed for networks operating under the physical interference model with single-path minimum hop routing. Extending transmission rights in a link-assigned schedule allows for network coding and temporal reuse, which increases timeslot usage efficiency when a scheduled link experiences packet depletion. The schedules that suffer from packet depletion are characterised and a generic temporal reuse-aware achievable rate region is derived. Extensive computational experiments show improved schedule capacity, quality of service, power efficiency and benefit from opportunistic bidirectional network coding accrued with schedules optimised in the proposed temporal reuse-aware convex capacity region. The application of joint source-channel coding, based on fountain codes, in the broadcast timeslot of wireless two-way network coding is also investigated. A computationally efficient subroutine is contributed to the implementation of the fountain compressor, and an error analysis is done. Motivated to develop a true joint source-channel-network code that compresses, adds robustness against channel noise and network codes two packets on a single bipartite graph and iteratively decodes the intended packet on the same Tanner graph, an adaptation of the fountain compressor is presented. The proposed code is shown to outperform a separated joint source-channel and network code in high source entropy and high channel noise regions, in anticipated support of dense networks that employ intelligent signalling. AFRIKAANS : Tegnologiese innovasie wat klein lae-koste kommunikasie toestelle bemagtig om met ’n hoë mate van benuttings doeltreffendheid te werk word bygedra in hierdie proefskrif. Transmissie-skedulering en gesamentlike bron-kanaal-netwerk kodering is twee van die belangrike aspekte wat aangespreek word. Hierdie werk fokus op die integrasie van onlangse verbeteringe soos draadlose netwerk kodering en temporêre herwinning in ’n tussen-laag optimaliserings raamwerk, en om ’n gesamentlike kodering skema te ontwerp wat voorsiening maak vir spasie-optimale toestel implementerings. Skakel-toegekende transmissie skedules met tydgleuf herwinning deur veelvuldige skakels in beide die ruimte en tyd domeine word ondersoek vir kwasi-stilstaande, veelvuldige-sprong draadlose rooster netwerke met beide transmissie-spoed en krag aanpassings. Om spesifiek te wees, word vooraf bepaalde tussen-laag geoptimiseerde skedules met verhoudings-regverdige punt-tot-punt vloei tempo’s en netwerk kodering vermoë saamgestel vir netwerke wat bedryf word onder die fisiese inmengings-model met enkel-pad minimale sprong roetering. Die uitbreiding van transmissie-regte in ’n skakel-toegekende skedule maak voorsiening vir netwerk kodering en temporêre herwinning, wat tydgleuf gebruiks-doeltreffendheid verhoog wanneer ’n geskeduleerde skakel pakkie-uitputting ervaar. Die skedules wat ly aan pakkie-uitputting word gekenmerk en ’n generiese temporêre herwinnings-bewuste haalbare transmissie-spoed gebied word afgelei. Omvattende berekenings-eksperimente toon verbeterde skedulerings kapasiteit, diensgehalte, krag doeltreffendheid asook verbeterde voordeel wat getrek word uit opportunistiese tweerigting netwerk kodering met die skedules wat geoptimiseer word in die temporêre herwinnings-bewuste konvekse transmissie-spoed gebied. Die toepassing van gesamentlike bron-kanaal kodering, gebaseer op fontein kodes, in die uitsaai-tydgleuf van draadlose tweerigting netwerk kodering word ook ondersoek. ’n Berekenings-effektiewe subroetine word bygedra in die implementering van die fontein kompressor, en ’n foutanalise word gedoen. Gemotiveer om ’n ware gesamentlike bron-kanaal-netwerk kode te ontwikkel, wat robuustheid byvoeg teen kanaal geraas en twee pakkies netwerk kodeer op ’n enkele bipartiete grafiek en die beoogde pakkie iteratief dekodeer op dieselfde Tanner grafiek, word ’n aanpassing van die fontein kompressor aangebied. Dit word getoon dat die voorgestelde kode ’n geskeide gesamentlike bron-kanaal en netwerk kode in hoë bron-entropie en ho¨e kanaal-geraas gebiede oortref in verwagte ondersteuning van digte netwerke wat van intelligente sein-metodes gebruik maak.Dissertation (MEng)--University of Pretoria, 2011.Electrical, Electronic and Computer Engineeringunrestricte

Quality of service and channel-aware packet bundling for capacity improvement in cellular networks

Title from PDF of title page, viewed on May 26, 2011VitaIncludes bibliographical references (p. 76-84)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2011We study the problem of multiple packet bundling to improve spectral efficiency in cellular networks. The packet size of real-time data, such as VoIP, is often very small. However, the common use of time division multiplexing limits the number of VoIP users supported, because a packet has to wait until it receives a time slot, and if only one small VoIP packet is placed in a time slot, capacity is wasted. Packet bundling can alleviate such a problem by sharing a time slot among multiple users. A recent revision of cdma2000 1xEV-DO introduced the concept of the multi-user packet (MUP) in the downlink to overcome limitations on the number of time slots. However, the efficacy of packet bundling is not well understood, particularly in the presence of time varying channels. We propose a novel QoS and channel-aware packet bundling algorithm that takes advantage of adaptive modulation and coding. We show that optimal algorithms are NP complete and recommend heuristic approaches. We also show that channel utilization can be significantly increased by slightly delaying some real-time packets within their QoS requirements while bundling those packets with like channel conditions. We validate our study through extensive OPNET simulations with a complete EV-DO implementation.Introduction -- Related work -- Background on wireless systems -- Multiple packet bundling -- Evaluation -- Conclusion

Scheduling in Large Scale MIMO Downlink Systems

This dissertation deals with the problem of scheduling in wireless MIMO (Multiple-Input Multiple-Output) downlink systems. The focus is on the large-scale systems when the number of subscribers is large. In part one, the problem of user selection in MIMO Broadcast channel is studied. An efficient user selection algorithm is proposed and is shown to achieve the sum-rate capacity of the system asymptotically (in terms of the number of users), while requiring (i)~low-complexity precoding scheme of zero-forcing beam-forming at the base station, (ii)~low amount of feedback from the users to the base station, (iii)~low complexity of search. Part two studies the problem of MIMO broadcast channel with partial Channel State Information (CSI) at the transmitter. The necessary and sufficient conditions for the amount of CSI at the transmitter (which is provided to via feedback links from the receivers) in order to achieve the sum-rate capacity of the system are derived. The analysis is performed in various singnal to noise ratio regimes. In part three, the problem of sum-rate maximization in a broadcast channel with large number of users, when each user has a stringent delay constraint, is studied. In this part, a new definition of fairness, called short-term fairness is introduced. A scheduling algorithm is proposed that achieves: (i) Maximum sum-rate throughput and (ii) Maximum short-term fairness of the system, simultaneously, while satisfying the delay constraint for each individual user with probability one. In part four, the sum-rate capacity of MIMO broadcast channel, when the channels are Rician fading, is derived in various scenarios in terms of the value of the Rician factor and the distribution of the specular components of the channel

Information dissemination in mobile networks

This thesis proposes some solutions to relieve, using Wi-Fi wireless networks, the data consumption of cellular networks using cooperation between nodes, studies how to make a good deployment of access points to optimize the dissemination of contents, analyzes some mechanisms to reduce the nodes' power consumption during data dissemination in opportunistic networks, as well as explores some of the risks that arise in these networks. Among the applications that are being discussed for data off-loading from cellular networks, we can find Information Dissemination in Mobile Networks. In particular, for this thesis, the Mobile Networks will consist of Vehicular Ad-hoc Networks and Pedestrian Ad-Hoc Networks. In both scenarios we will find applications with the purpose of vehicle-to-vehicle or pedestrian-to-pedestrian Information dissemination, as well as vehicle-to-infrastructure or pedestrian-to-infrastructure Information dissemination. We will see how both scenarios (vehicular and pedestrian) share many characteristics, while on the other hand some differences make them unique, and therefore requiring of specific solutions. For example, large car batteries relegate power saving techniques to a second place, while power-saving techniques and its effects to network performance is a really relevant issue in Pedestrian networks. While Cellular Networks offer geographically full-coverage, in opportunistic Wi-Fi wireless solutions the short-range non-fullcoverage paradigm as well as the high mobility of the nodes requires different network abstractions like opportunistic networking, Disruptive/Delay Tolerant Networks (DTN) and Network Coding to analyze them. And as a particular application of Dissemination in Mobile Networks, we will study the malware spread in Mobile Networks. Even though it relies on similar spreading mechanisms, we will see how it entails a different perspective on Dissemination

Heterogeneous Cellular Networks: From Resource Allocation To User Association

Heterogeneous networking paradigm addresses the ever growing need for capacity and coverage in wireless networks by deploying numerous low power base stations overlaying the existing macro cellular coverage. Heterogeneous cellular networks encompass many deployment scenarios, with different backhauling techniques (wired versus wireless backhauling), different transmission coordination mechanisms and resource allocation schemes, different types of links operating at different bands and air-interface technologies, and different user association schemes. Studying these deployment scenarios and configurations, and understanding the interplay between different processes is challenging. In the first part of the thesis, we present a flow-based optimization framework that allows us to obtain the throughput performance of a heterogeneous network when the network processes are optimized jointly. This is done under a given system ``snapshot'', where the system parameters like the channel gains and the number of users are fixed and assumed known. Our framework allows us to configure the network parameters to allocate optimal throughputs to these flows in a fair manner. This is an offline-static model and thus is intended to be used at the engineering and planning phase to compare many potential configurations and decide which ones to study further. Using the above-mentioned formulation, we have been able to study a large set of deployment scenarios and different choices of resource allocation, transmission coordination, and user association schemes. This has allowed us to provide a number of important engineering insights on the throughput performance of different scenarios and their configurations. The second part of our thesis focuses on understanding the impact of backhaul infrastructure's capacity limitation on the radio resource management algorithms like user scheduling and user association. Most existing studies assume an ideal backhaul. This assumption, however, needs to be revisited as backhaul considerations are critical in heterogeneous networks due to the economic considerations. In this study, we formulate a global $\alpha$-fair user scheduling problem under backhaul limitations, and show how this limitation has a fundamental impact on user scheduling. Using results from convex optimization, we characterize the solution of optimal backhaul-aware user scheduling and show that simple heuristics can be used to obtain good throughput performance with relatively low complexity/overhead. We also study the related problem of user association under backhaul-limitations. This study is a departure from our ``snapshot'' approach. We discuss several important design considerations for an online user association scheme. We present a relatively simple backhaul-unaware user association scheme and show that it is very efficient as long as the network has fine-tuned the resource allocation

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters