Capacity Approaching Coding Strategies for Machine-to-Machine Communication in IoT Networks

Radio access technologies for mobile communications are characterized by multiple access (MA) strategies. Orthogonal MA techniques were a reasonable choice for achieving good performance with single user detection. With the tremendous growth in the number of mobile users and the new internet of things (IoT) shifting paradigm, it is expected that the monthly mobile data traffic worldwide will exceed 24.3 exabytes by 2019, over 100 billion IoT connections by 2025, and the financial impact of IoT on the global economy varies in the range of 3.9 to 11.1 trillion dollars by 2025. In light of the envisaged exponential growth and new trends, one promising solution to further enhance data rates without increasing the bandwidth is by increasing the spectral efficiency of the channel. Non-orthogonal MA techniques are potential candidates for future wireless communications. The two corner points on the boundary region of the MA channel are known to be achievable by single user decoding followed by successive decoding (SD). Other points can also be achieved using time sharing or rate splitting. On the other hand, machine-to-machine (M2M) communication which is an enabling technology for the IoT, enables massive multipurpose networked devices to exchange information among themselves with minor or no human intervention. This thesis consists of three main parts. In the first part, we propose new practical encoding and joint belief propagation (BP) decoding techniques for 2-user MA erasure channel (MAEC) that achieve any rate pair close to the boundary of the capacity region without using time sharing nor rate splitting. While at the encoders, the corresponding parity check matrices are randomly built from a half-rate LDPC matrix, the joint BP decoder employs the associated Tanner graphs of the parity check matrices to iteratively recover the erasures in the received combined codewords. Specifically, the joint decoder performs two steps in each decoding iteration: 1) simultaneously and independently runs the BP decoding process at each constituent sub-graph to recover some of the common erasures, 2) update the other sub-graph with newly recovered erasures and vice versa. When the number of erasures in the received combined codewords is less than or equal to the number of parity check constraints, the decoder may successfully decode both codewords, otherwise the decoder declares decoding failure. Furthermore, we calculate the probability of decoding failure and the outage capacity. Additionally, we show how the erasure probability evolves with the number of decoding iterations and the maximum tolerable loss. Simulations show that any rate pair close to the capacity boundary is achievable without using time sharing. In the second part, we propose a new cooperative joint network and rateless coding strategy for machine-type communication (MTC) devices in the multicast settings where three or more MTC devices dynamically form a cluster to disseminate messages between themselves. Specifically, in the basic cluster, three MTC devices transmit their respective messages simultaneously to the relay in the first phase. The relay broadcasts back the combined messages to all MTC devices within the basic cluster in the second phase. Given the fact that each MTC device can remove its own message, the received signal in the second phase is reduced to the combined messages coming from the other two MTC devices. Hence, this results in exploiting the interference caused by one message on the other and therefore improving the bandwidth efficiency. Furthermore, each group of three MTC devices in vicinity can form a basic cluster for exchanging messages, and the basic scheme extends to N MTC devices. Furthermore, we propose an efficient algorithm to disseminate messages among a large number of MTC devices. Moreover, we implement the proposed scheme employing practical Raptor codes with the use of two relaying schemes, namely amplify and forward (AF) and de-noise and forward (DNF). We show that with very little processing at the relay using DNF relaying scheme, performance can be further enhanced. We also show that the proposed scheme achieves a near optimal sum rate performance. In the third part, we present a comparative study of joint channel estimation and decoding of factor graph-based codes over flat fading channels and propose a simple channel approximation scheme that performs close to the optimal technique. Specifically, when channel state information (CSI) is not available at the receiver, a simpler approach is to estimate the channel state of a group of received symbols, then use the approximated value of the channel with the received signal to compute the log likelihood ratio. Simulation results show that the proposed scheme exhibits about 0.4 dB loss compared to the optimal solution when perfect CSI is available at the receiver

Understanding the characteristics of Internet traffic and designing an efficient RaptorQ-based data transport protocol for modern data centres

This thesis is the amalgamation of research on efficient data transport protocols for data centres and a comprehensive and systematic study of Internet traffic, which came as a result of the need to understand traffic patterns and workloads in modern computer networks. The first part of the thesis is on the development of efficient data transport pro- tocols for data centres. We study modern data transport protocols for data centres through large scale simulations using the OMNeT++ simulator. We developed and experimented with an OMNeT++ model of NDP. This has led to the identification of limitations of the state of the art and the formulation of research questions with respect to data transport protocols for modern data centres. The developed model includes an implementation of a Fat-tree topology and per-packet ECMP load bal- ancing. We discuss how we integrated the model with the INET Framework and validated it by running various experiments that test different model parameters and components. This work revealed limitations of NDP with respect to efficient one-to-many and many-to-one communication in data centres, which led to the de- velopment of SCDP, a novel and general-purpose data transport protocol for data centres that, in contrast to all other protocols proposed to date, natively supports one-to-many and many-to-one data communication, which is extremely common in modern data centres. SCDP does so without compromising on efficiency for short and long unicast flows. SCDP achieves this by integrating RaptorQ codes with receiver-driven data transport, in-network packet trimming and Multi-Level Feed- back Queuing (MLFQ); (1) RaptorQ codes enable efficient one-to-many and many- to-one data transport; (2) on top of RaptorQ codes, receiver- driven flow control, in combination with in-network packet trimming, enable efficient usage of network re- sources as well as multi-path transport and packet spraying for all transport modes. Incast and Outcast are eliminated; (3) the systematic nature of RaptorQ codes, in combination with MLFQ, enable fast, decoding-free completion of short flows. We extensively evaluated SCDP in a wide range of simulated scenarios with realistic data centre workloads. For one-to-many and many-to-one transport sessions, SCDP performs significantly better than NDP. For short and long unicast flows, SCDP performs equally well or better compared to NDP. In the second part of the thesis, we extensively study Internet traffic. Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally important but less studied problem. We study a large number of traffic traces from many different networks including academic, commercial and residential networks using state-of-the-art statistical techniques. We show that the log-normal distribution is a better fit than the Gaussian distribution. We also investigate a second, heavy- tailed distribution and show that its performance is better than Gaussian but worse than log-normal. We examine anomalous traces which are a poor fit for all tested distributions and show that this is often due to traffic outages or links that hit maximum capacity. Stationarity tests showed that the traffic is stationary at some range of aggregation times. We demonstrate the utility of the log-normal distribution in two contexts: predicting the proportion of time traffic will exceed a given level (for link capacity estimation) and predicting 95th percentile pricing. We also show the log-normal distribution is a better predictor than Gaussian orWeibull distributions

A protocol design paradigm for rateless fulcrum code

Establecer servicios Multicast eficientes en una red con dispositivos heterogéneos y bajo los efectos de un canal con efecto de borradura es una de las prioridades actuales en la teoría de la codificación, en particular en Network Coding (NC). Además, el creciente número de clientes con dispositivos móviles de gran capacidad de procesamiento y la prevalencia de tráfico no tolerante al retardo han provocado una demanda de esquemas Multicast sin realimentación en lo que respecta a la gestión de recursos distribuidos. Las plataformas de comunicación actuales carecen de un control de codificación gradual y dinámico basado en el tipo de datos que se transmiten a nivel de la capa de aplicación. Este trabajo propone un esquema de transmisión fiable y eficiente basado en una codificación hibrida compuesta por una codificación sistemática y codificación de red lineal aleatoria (RLNC) denominada codificación Fulcrum. Este esquema híbrido de codificación distribuida tipo Rateless permite implementar un sistema adaptativo de gestión de recursos para aumentar la probabilidad de descodificación durante la recepción de datos en cada nodo receptor de la información. En última instancia, el esquema propuesto se traduce en un mayor rendimiento de la red y en tiempos de transmisión (RTT) mucho más cortos mediante la implementación eficiente de una corrección de errores hacia delante (FEC).DoctoradoDoctor en Ingeniería de Sistemas y Computació

On spectrum allocation strategies in Cognitive Radio Networks

Due to the temporal and spatial underutilization of licensed spectrum bands, as well as the crowdedness of unlicensed bands, a new spectrum access paradigm has been recently proposed namely, Cognitive Radio (CR). CR enables users to adjust their transceivers\u27 frequencies depending on the availability of licensed frequency bands which are otherwise unused by their licensees, called Primary Users (PUs). Thus, unlicensed wireless users, called Secondary Users (SUs) can dynamically and opportunistically access unused licensed bands in order to improve their throughput and service reliability. Whenever the licensed users, or the PUs, become active, SUs must vacate their bands. This dissertation is concerned with the operation of Cognitive Radio Networks (CRNs), and deals with four important problems. First, a performance model to study heterogeneous channel access in CRNs is presented. In this model, there are two types of licensed channels, where one type has a larger bandwidth, and hence a higher service rate for SUs. Therefore, SUs prefer to use such channels, if available, over channels in the second type which have a lower service rate. SUs may also switch from the second to the first type of channels when they become available, even if their current channels are still available. We also model the SUs\u27 sensing process, and derive several SUs\u27 performance metrics including average waiting time. Numerical results show that our proposed operational model outperforms a baseline model that does not support prioritized access. Second, we introduce a low overhead scheme for the uplink channel allocation within a single cell of CRNs operating as Wireless Mesh Networks (CR-WMNs). The scheme does not rely on using a Common Control Channel (CCC). The proposed mechanism is based on the use of Physical Layer Network Coding (PNC), in which two (or three) Secondary Users (SUs) who are requesting uplink channel allocation are allowed to transmit synchronously over a randomly selected channel from a set of available channels, and without coordination. A Mesh Router (MR) which is listening to these transmissions, and is in charge of channel allocation, can detect up to 2 (or 3) requests, on the same channel due to the use of PNC, and replies back with a control packet which contains information about channel assignment. Our proposed mechanisms significantly outperform traditional schemes that rely on using one CCC, or do not use PNC, in terms of channel allocation overhead time. Third, we also propose to enable SUs to recover their packets which collide with PUs\u27 transmissions when a PU becomes active for two scenarios, based on the received phase shifts. When a collision occurs between an SU and a PU transmitters, the SU\u27s receiver considers the PU\u27s transmission as an interference, and hence, cancels its effect in order to recover its corresponding received packet\u27s signals. Recovering collided packets, instead of retransmitting them saves transmitters\u27 energy. Numerical results show that a high percentage of energy can be saved over the traditional scheme, in which our packets recovery mechanisms are not employed. Finally, we propose a novel multicast resilient routing approach to select primary and backup paths from an SU source to SUs destinations. Our approach employs a multilayer hyper-graph, in order to model the network, e.g., channels. The primary paths to destination SUs are selected to minimize the end-to-end delay which takes into consideration channels switching latency and transmission delay. To protect the multicast session, we find a backup path for primary path, if feasible, such that these two paths are shared risk hyper-edge disjoint, in order to prevent a concurrent failure for these two paths, when the corresponding PU for this hyper-edge becomes active. Our simulation results show that increasing the number of available channels, increase the number of feasible primary and backup paths, and the maximum path delay decreases almost linearly

Design and analysis of network coding schemes for efficient fronthaul offloading of fog-radio access networks

In the era of the Internet of Things (IoT), everything will be connected. Smart homes and cities, connected cars, smart agriculture, wearable technologies, smart healthcare, smart sport, and fitness are all becoming a reality. However, the current cloud architecture cannot manage the tremendous number of connected devices and skyrocketing data traffic while providing the speeds promised by 5G and beyond. Centralised cloud data centres are physically too far from where the data originate (edge of the network), inevitably leading to data transmission speeds that are too slow for delay-sensitive applications. Thus, researchers have proposed fog architecture as a solution to the ever-increasing number of connected devices and data traffic. The main idea of fog architecture is to bring content physically closer to end users, thus reducing data transmission times. This thesis considers a type of fog architecture in which smart end devices have storage and processing capabilities and can communicate and collaborate with each other. The major goal of this thesis is to develop methods of efficiently governing communication and collaboration between smart end devices so that their requests to upper network layers are minimised. This is achieved by incorporating principles from graph theory, network coding and machine learning to model the problem and design efficient network-coded scheduling algorithms to further enhance achieved performance. By maximising end users' self-sufficiency, the load on the system is decreased and its capacity increased. This will allow the central processing unit to manage more devices which is vital, given that more than 29 billion devices will connect to the infrastructure by 2023 \cite{Cisco1823}. Specifically, given that the limitations of the smart end devices and the system in general lead to various communication conflicts, a novel network coding graph is developed that takes into account all possible conflicts and enables the search for an efficient feasible solution. The thesis designs heuristic algorithms that search for the solution over the novel network coding graph, investigates the complexity of the proposed algorithms, and shows the offloading strategy's asymptotic optimality. Although the main aim of this work is to decrease the involvement of upper fog layers in serving smart end devices, it also takes into account how much energy end devices would use during collaborations. Unfortunately, a higher system capacity comes at the price of more energy spent by smart end devices; thus, service providers' interests and end users' interests are conflicting. Finally, this thesis investigates how multihop communication between end devices influences the offloading of upper fog layers. Smart end devices are equipped with machine learning capabilities that allow them to find efficient paths to their peers, further improving offloading. In conclusion, the work in this thesis shows that by smartly designing and scheduling communication between end devices, it is possible to significantly reduce the load on the system, increase its capacity and achieve fast transmissions between end devices, allowing them to run latency-critical applications

Network Coding Strategies for Satellite Communications

Network coding (NC) is an important technology that allows the network services to be optimal. The main advantage of NC is to reduce the necessity for re-transmissions of packets. Satellite Communications (SatComs) are one of the potential applications that can leverage on the benefits of NC due to their challenging fading environments and high round trip times. The motivation is to take the physical layer-awareness into consideration for adapting and hence extend the NC gains. Different rate and energy efficient adaptive NC schemes for time variant channels are proposed. We compare our proposed physical layer adaptive schemes to physical layer non-adaptive NC schemes for time variant channels. The adaptation of packet transmissions is on the basis of the corresponding time-dependent erasures, and allows proposed schemes to achieve significant gains in terms of throughput, delay and energy efficiency. The proposed schemes are robust for large and small size of packets. Although, the energy per bit is affected, a similar rate and energy gains can be arise. However, the performance gains are not motivated by the packet size, but through duty cycle silence of transfer packets. In this thesis, virtual schemes are also proposed to solve an open literature problem in the NC. The objective is to find a quasi-optimal number of coded packets to multicast to a group of independent wireless receivers suffer from a different channel conditions. In particular, we propose two virtual network that allows for the representation of a group of receivers as a multicast group to be visible as one receiver and single channel. Most of the schemes are applied to LEO/MEO/GEO satellite scenarios. They demonstrate remarkable gains compared to that strategy in which the adaptation depends only on one receiver point-to-point

Journal of Telecommunications and Information Technology, 2013, nr 1

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