Fountain codes have recently gained wide attention in the communications research community due to their capacity-approaching performance and rateless properties that allow them to seamlessly adapt to unknown channel statistics. This thesis of fers two key contributions. For the first, we consider the problem of low complexity decoding of Luby Transform (LT) and Raptor codes, which are classes of Fountain codes. We introduce a decoding method which has a significantly reduced compu tational load compared to the commonly used alternative of message-reset decoding with a flooding schedule. This method combines the recently proposed technique of informed dynamic scheduling combined with incremental decoding. Simulation re sults for the example of the binary symmetric channel show complexity reductions (in terms of the total required number of decoding iterations) by 87% compared to conventional message-passing decoding and 54% compared to a recently proposed incremental decoding scheme for Raptor codes. Having proposed our novel decoding method, we then focus on applying rateless codes to free-space optical (FSO) transmission systems. FSO systems enable high speed communication with relatively small deployment costs. However, FSO systems suffer a critical disadvantage, namely susceptibility to fog, smoke, and similar con ditions. A possible solution to this dilemma is the use of hybrid systems employing FSO and radio frequency (RF) transmission. As for the second contribution of this thesis, we propose the application of rateless coding for such hybrid FSO/RF sys tems. The advantages of our approach are (i) the full utilization of available FSO and RF channel resources at any time and (ii) very little feedback from the receiver. In order to substantiate these claims, we establish the pertinent capacity limits for hybrid FSO/RF transmission and present simulation results for transmission with off-the-shelf Raptor codes, which achieve realized rates close to these limits under a wide range of channel conditions.

Fountain codes have recently gained wide attention in the communications research community due to their capacity-approaching performance and rateless properties that allow them to seamlessly adapt to unknown channel statistics. This thesis of fers two key contributions. For the first, we consider the problem of low complexity decoding of Luby Transform (LT) and Raptor codes, which are classes of Fountain codes. We introduce a decoding method which has a significantly reduced compu tational load compared to the commonly used alternative of message-reset decoding with a flooding schedule. This method combines the recently proposed technique of informed dynamic scheduling combined with incremental decoding. Simulation re sults for the example of the binary symmetric channel show complexity reductions (in terms of the total required number of decoding iterations) by 87% compared to conventional message-passing decoding and 54% compared to a recently proposed incremental decoding scheme for Raptor codes. Having proposed our novel decoding method, we then focus on applying rateless codes to free-space optical (FSO) transmission systems. FSO systems enable high speed communication with relatively small deployment costs. However, FSO systems suffer a critical disadvantage, namely susceptibility to fog, smoke, and similar con ditions. A possible solution to this dilemma is the use of hybrid systems employing FSO and radio frequency (RF) transmission. As for the second contribution of this thesis, we propose the application of rateless coding for such hybrid FSO/RF sys tems. The advantages of our approach are (i) the full utilization of available FSO and RF channel resources at any time and (ii) very little feedback from the receiver. In order to substantiate these claims, we establish the pertinent capacity limits for hybrid FSO/RF transmission and present simulation results for transmission with off-the-shelf Raptor codes, which achieve realized rates close to these limits under a wide range of channel conditions.

Multimedia services have become one of the major demands in wireless systems. As a result of growing demands for media services, traffic in wireless networks are increasing. Hence, optimization of multimedia delivery systems to efficiently consume the valuable transmission resources in wireless networks has gained a lot of interest. Raptor codes, with linear encoding and decoding time complexity are one branch of fountain codes (also known as rateless codes) which have found their ways in many recent communication standards as application layer forward error correcting (FEC) codes. Various attempts have been made in order to adapt these codes to wireless channels with their time varying nature. When multimedia delivery is targeted, some other issues such as delay should also be considered. Moreover, in multicast solutions, the system has to address demands of multiple clients. In this thesis, we investigate some optimization scenarios for wireless multimedia multicast systems wherein clients with heterogeneous channels and media quality demands subscribe to a video program. The video program is assumed as a multilayer source with possible spatial, temporal and fidelity layers. The point of optimization under various systems is to provide the clients of different quality constraints with their demanded services while imposing the minimum network/client cost (e.g. delay, power consumption, outage probability) or maximize the provided utility to the clients while considering their heterogeneous capabilities. To achieve these tasks, we study outage probability which serves as a measure to quantify the reliability of a service in a client's side. Packetized rateless multimedia multicast (PRMM) with few optimization criteria regarding the experienced delay in clients are studied and analytical solutions are obtained. A new optimization framework for rateless multimedia multicast is proposed in which, the provided utility to heterogeneous clients are maximized with respect to the clients channel and their quality demands. Application of this optimization in a rateless multimedia multicast system wherein the utility is defined based on perceptual quality experience of clients is also investigated. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-12-23 14:11:26.378

Fountain codes have recently gained wide attention in the communications research community due to their capacity-approaching performance and rateless properties that allow them to seamlessly adapt to unknown channel statistics. This thesis of fers two key contributions. For the first, we consider the problem of low complexity decoding of Luby Transform (LT) and Raptor codes, which are classes of Fountain codes. We introduce a decoding method which has a significantly reduced compu tational load compared to the commonly used alternative of message-reset decoding with a flooding schedule. This method combines the recently proposed technique of informed dynamic scheduling combined with incremental decoding. Simulation re sults for the example of the binary symmetric channel show complexity reductions (in terms of the total required number of decoding iterations) by 87% compared to conventional message-passing decoding and 54% compared to a recently proposed incremental decoding scheme for Raptor codes. Having proposed our novel decoding method, we then focus on applying rateless codes to free-space optical (FSO) transmission systems. FSO systems enable high speed communication with relatively small deployment costs. However, FSO systems suffer a critical disadvantage, namely susceptibility to fog, smoke, and similar con ditions. A possible solution to this dilemma is the use of hybrid systems employing FSO and radio frequency (RF) transmission. As for the second contribution of this thesis, we propose the application of rateless coding for such hybrid FSO/RF sys tems. The advantages of our approach are (i) the full utilization of available FSO and RF channel resources at any time and (ii) very little feedback from the receiver. In order to substantiate these claims, we establish the pertinent capacity limits for hybrid FSO/RF transmission and present simulation results for transmission with off-the-shelf Raptor codes, which achieve realized rates close to these limits under a wide range of channel conditions. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Rateless codes, also known as fountain codes, are a class of erasure error-control codes that are particularly well suited for broadcast/multicast systems. Raptor codes, as a particularly successful implementation of digital fountain codes, have been used as the application layer forward error correction (FEC) codes in the third generation partnership program (3GPP) Multimedia Broadcast and Multicast Services (MBMS) standard. However, the application of rateless codes to wireless multimedia broadcast/multicast communications has yet to overcome two major challenges: first, wireless multimedia communications usually has stringent delay requirements. In addition, multimedia multicast has to overcome heterogeneity. To meet these challenges, we propose a rateless code design that takes the layered nature of source traffic as well as the varying quality of transmission channels into account. A convex optimization framework for the application of unequal error protection (UEP) rateless codes to synchronous and asynchronous multimedia multicast to heterogeneous users is proposed. A second thread of the thesis addresses the noisy, bursty and time- varying nature of wireless communication channels that challenge the assumption of erasure channels often used for the wired internet. In order to meet this challenge, the optimal combination of application-layer rateless code and physical layer FEC code rates in time-varying fading channels is investigated. The performance of rateless codes in hybrid error-erasure channels with memory is then studied, and a cross-layer decoding method is proposed to improve decoding performance and complexity. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2011-06-12 16:26:36.136

In wireless networks, communication links may be subject to random fatal impacts: for example, sensor networks under sudden power losses or cognitive radio networks with unpredictable primary user spectrum occupancy. Under such circumstances, it is critical to quantify how fast and reliably the information can be collected over attacked links. For a single point-to-point channel subject to a random attack, named as a dying channel, we model it as a block-fading (BF) channel with a finite and random channel length. First, we study the outage probability when the coding length K is fixed and uniform power allocation is assumed. Furthermore, we discuss the optimization over K and the power allocation vector PK to minimize the outage probability. In addition, we extend the single point to-point dying channel case to the parallel multi-channel case where each sub-channel is a dying channel, and investigate the corresponding asymptotic behavior of the overall outage probability with two different attack models: the independent-attack case and the m-dependent-attack case. It can be shown that the overall outage probability diminishes to zero for both cases as the number of sub-channels increases if the rate per unit cost is less than a certain threshold. The outage exponents are also studied to reveal how fast the outage probability improves over the number of sub-channels. Besides the information-theoretical results, we also study a practical coding scheme for the dying binary erasure channel (DBEC), which is a binary erasure channel (BEC) subject to a random fatal failure. We consider the rateless codes and optimize the degree distribution to maximize the average recovery probability. In particular, we first study the upper bound of the average recovery probability, based on which we define the objective function as the gap between the upper bound and the average recovery probability achieved by a particular degree distribution. We then seek the optimal degree distribution by minimizing the objective function. A simple and heuristic approach is also proposed to provide a suboptimal but good degree distribution.

The ability to transfer data reliably and with low delay over an unreliable service is intrinsic to a number of emerging technologies, including digital video broadcasting, over-the-air software updates, public/private cloud storage, and, recently, wireless vehicular networks. In particular, modern vehicles incorporate tens of sensors to provide vital sensor information to electronic control units (ECUs). In the current architecture, vehicle sensors are connected to ECUs via physical wires, which increase the cost, weight and maintenance effort of the car, especially as the number of electronic components keeps increasing. To mitigate the issues with physical wires, wireless sensor networks (WSN) have been contemplated for replacing the current wires with wireless links, making modern cars cheaper, lighter, and more efficient. However, the ability to reliably communicate with the ECUs is complicated by the dynamic channel properties that the car experiences as it travels through areas with different radio interference patterns, such as urban versus highway driving, or even different road quality, which may physically perturb the wireless sensors. This thesis develops a suite of reliable and efficient communication schemes built upon feedback-based rateless codes, and with a target application of vehicular networks. In particular, we first investigate the feasibility of multi-hop networking for intra-car WSN, and illustrate the potential gains of using the Collection Tree Protocol (CTP), the current state of the art in multi-hop data aggregation. Our results demonstrate, for example, that the packet delivery rate of a node using a single-hop topology protocol can be below 80% in practical scenarios, whereas CTP improves reliability performance beyond 95% across all nodes while simultaneously reducing radio energy consumption. Next, in order to migrate from a wired intra-car network to a wireless system, we consider an intermediate step to deploy a hybrid communication structure, wherein wired and wireless networks coexist. Towards this goal, we design a hybrid link scheduling algorithm that guarantees reliability and robustness under harsh vehicular environments. We further enhance the hybrid link scheduler with the rateless codes such that information leakage to an eavesdropper is almost zero for finite block lengths. In addition to reliability, one key requirement for coded communication schemes is to achieve a fast decoding rate. This feature is vital in a wide spectrum of communication systems, including multimedia and streaming applications (possibly inside vehicles) with real-time playback requirements, and delay-sensitive services, where the receiver needs to recover some data symbols before the recovery of entire frame. To address this issue, we develop feedback-based rateless codes with dynamically-adjusted nonuniform symbol selection distributions. Our simulation results, backed by analysis, show that feedback information paired with a nonuniform distribution significantly improves the decoding rate compared with the state of the art algorithms. We further demonstrate that amount of feedback sent can be tuned to the specific transmission properties of a given feedback channel.

Wireless Sensor Networks (WSNs) that use tiny wireless devices capable of communicating, processing, and sensing promise to have applications in virtually all fields. Smart homes and smart cities are just few of the examples that WSNs can enable. Despite their potential, WSNs suffer from reliability and energy limitations. In this study, we address the problem of designing Distributed Data Storage Systems (DDSSs) for WSNs using decentralized erasure codes. A unique aspect of WSNs is that their data is inherently decentralized. This calls for a decentralized mechanism for encoding and decoding. We propose a distributed data storage framework to increase data survivability in WSNs. The framework utilizes Decentralized Erasure Codes for Data Survivability (DEC-DS) which allow for determining the amount of redundancy required in both hardware and data to allow sensed data to survive failures in the network. To address the energy limitations, we show two approaches to implement the proposed solution in an energy efficient manner. The two approaches employ Random Linear Network Coding (RLNC) to exploit coding opportunities in order to save energy and in turn prolong network life. A routing based scheme, called DEC Encode-and-Forward (DEC-EaF), applies to networks with routing capability, while the second, DEC Encode-and-Disseminate (DEC-EaD), uses a variation of random walk to build the target code in a decentralized fashion. We also introduce a new decentralized approach to implement Luby Transform (LT)-Codes based DDSSs. The scheme is called Decentralized Robust Soliton Storage (DRSS) and it operates in a decentralized fashion and requires no coordination between sensor nodes. The schemes are tested through extensive simulations to evaluate their performance. We also compare the proposed schemes to similar schemes in the literature. The comparison considers energy efficiency as well as coding related aspects. Using the proposed schemes can greatly improve the reliability of WSNs especially under harsh working conditions. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-09-30 22:43:04.509

Luby Transform Codes were the first class of universal erasure codes introduced to fully realize the concept of scalable and fault‐tolerant distribution of data over computer networks, also called Digital Fountain. Later Raptor codes, a generalization of the LT codes were introduced to trade off complexity with performance. In this work, we show that an even broader class of codes exists that are near optimal for the erasure channel and that the Raptor codes form a special case. More precisely, Raptorlike codes can be designed based on an iterative (joint) decoding schedule wherein information is transferred between the LT decoder and an outer decoder in an iterative manner. The design of these codes can be formulated as a LP problem using EXIT Charts and density evolution. In our work, we show the existence of codes, other than the Raptor codes, that perform as good as the existing ones. We extend this framework of joint decoding of the component codes to the additive white Gaussian noise channels and introduce the design of Rateless codes for these channels. Under this setting, for asymptotic lengths, it is possible to design codes that work for a class of channels defined by the signal‐to‐noise ratio. In our work, we show that good profiles can be designed using density evolution and Gaussian approximation. EXIT charts prove to be an intuitive tool and aid in formulating the code design problem as a LP problem. EXIT charts are not exact because of the inherent approximations. Therefore, we use density evolution to analyze the performance of these codes. In the Gaussian case, we show that for asymptotic lengths, a range of designs of Rateless codes exists to choose from based on the required complexity and the overhead. Moreover, under this framework, we can design incrementally redundant schemes for already existing outer codes to make the communication system more robust to channel noise variations.

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