Design of High Performance Low Latency Rateless Codes
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Theory and Modelling of Single-Electronic Systems
Theory and Modelling of Single-Electronic Systems Sharief Fadul Babikir October 1993 A Thesis presented to the University of Glasgow Department of Electronics and Electrical Engineering for the degree of Doctor of Philosophy © Sharief Fadul Babikir, 1993 ProQuest Number: 13833803 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a com plete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. uest ProQuest 13833803 Published by ProQuest LLC(2019). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States C ode Microform Edition © ProQuest LLC. ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106- 1346 GLASGOW university irm&RY _ 4S .1 "I3 G ( i ) Abstract In this thesis a theoretical study is made of the behaviour of single- electronic devices and systems. It is argued that the properties of single- electronic systems can be determined if the densities of the legal soliton states are known. The dynamics of the tunnelling electrons in such systems are modelled as a traffic process. An exact analytical technique based on the conventional Traffic Theory is formulated in the thesis. This new technique is compared with the traditional Monte-Carlo method and is shown to be superior, both in accuracy and speed. An algorithm that correctly and efficiently determines the set of active soliton states and the relationship between the states is also described. -
Fountain Codes
6.972 PRINCIPLES OF DIGITAL COMMUNICATION II Fountain Codes Gauri Joshi, Joong Bum Rhim, John Sun, Da Wang December 8, 2010 Contents 1 Digital Fountain Ideal3 2 Preliminaries 4 2.1 Binary Erasure Channel...................................4 2.2 Edge Degree Distributions..................................4 3 Tornado Codes 5 3.1 Code Construction......................................5 3.2 Optimal Degree Sequences..................................7 3.3 Practical Considerations...................................9 3.3.1 Matlab Implementation...............................9 4 LT Codes 9 4.1 Code Construction...................................... 10 4.1.1 Encoding Process................................... 10 4.1.2 Decoding Process................................... 10 4.2 Degree Distribution...................................... 11 4.2.1 The Ideal Soliton Distribution............................ 12 4.2.2 The Robust Soliton Distribution.......................... 13 4.3 Performance Analysis.................................... 14 4.3.1 Degree Distribution................................. 15 4.3.2 Density Evolution.................................. 15 4.4 Implementation........................................ 17 5 Raptor Codes 17 5.1 Code Construction...................................... 18 5.2 Error Analysis......................................... 19 5.3 Practical Considerations................................... 19 5.3.1 Finite-length Raptor Codes............................. 20 5.3.2 Systematic Raptor Codes.............................. 20 5.3.3 -
Network Coding Protocols with Delay and Energy Constraints
Maricica Nistor Network Coding Protocols with Delay and Energy Constraints MAP-tele Doctoral Programme em Telecommunications Departamento de Engenharia Eletrot´ecnica e de Computadores Faculdade de Engenharia da Universidade do Porto May 2014 Maricica Nistor Network Coding Protocols with Delay and Energy Constraints Tese submetida `aFaculdade de Engenharia da Universidade do Porto para obten¸c˜ao do grau de Doutor em Telecomunica¸c˜oes Orientadores: Professor Doutor Jo˜ao Barros, Universidade do Porto, Portugal Professor Doutor Daniel E. Lucani, Aalborg University, Denmark May 2014 2 Acknowledgements I would like to thank my advisor, Professor Jo˜ao Barros, for his support, en- couragement, and guidance throughout my PhD. I would also like to thank my co-advisor, Professor Daniel E. Lucani, for his help and patience, and the way he really made my life more enjoyable during these last years. I thank my colleagues from IT Porto for the good moments we spent to- gether and all research collaborators I worked with during my PhD. A special thank goes to my family for the unconditional support, trust, and because they never stop to believe in me. I would also like to thank my friends for the encouragements, advises, and for being always close to me. Finally, I would like to thank Luis Monteiro, for his love, patience, and support. I dedicate this work to Luis Monteiro! This work was partially funded by the Funda¸c˜ao Calouste Gulbenkian un- der grant 103905 and by Funda¸c˜ao para a Ciˆencia e Tecnologia (Portuguese Foundation for Science and Technology) under grant SFRH-BD-61953-2009. -
An ECSO-Based Approach for Optimizing Degree Distribution of Short-Length LT Codes Peng Luo1*, Hui Fan1, Weiguang Shi2, Xiaoli Qi2, Yuhao Zhao1 and Xueqing Zhou1
Luo et al. EURASIP Journal on Wireless Communications and Networking (2019) 2019:76 https://doi.org/10.1186/s13638-019-1376-6 RESEARCH Open Access An ECSO-based approach for optimizing degree distribution of short-length LT codes Peng Luo1*, Hui Fan1, Weiguang Shi2, Xiaoli Qi2, Yuhao Zhao1 and Xueqing Zhou1 Abstract Degree distribution plays a great role in the performance of Luby transform codes. Typical degree distributions such as ideal soliton distribution and robust soliton distribution are easy to implement and widely used. Nevertheless, their adaptabilities are not always outstanding in various code lengths, especially in the case of short length. In this paper, our work is to optimize degree distributions for the short-length LT codes by using swarm intelligence algorithm, considering its conceptual simplicity, high efficiency, flexibility, and robustness. An optimization problem model based on sparse degree distributions is proposed in the first place. Then, a solution on the basis of an enhanced chicken swarm optimization algorithm, termed as ECSO, is designed for the problem. In ECSO, substitution of bottom individuals, revision of chicks’ update equation, and introduction of differential evolution are designed to enhance the ability of optimization. Simulation comparisons show that the proposed solution achieves much better performance than two other swarm intelligence-based solutions. Keywords: Fountain codes, LT code, Degree distribution, Differential evolution, Chicken swarm optimization 1 Introduction leading a wider scope of application, including deep space Power line communication (PLC) is regarded as a ser- communication [8], data distribution [9], wireless sensor ious candidate for the realization of smart grid networks networks [10], and cloud storage [11]. -
Incremental Redundancy, Fountain Codes and Advanced Topics
GRAPH CODES AND THEIR APPLICATIONS 2014 DRAFT Incremental Redundancy, Fountain Codes and Advanced Topics Suayb S. Arslan 141 Innovation Dr. Irvine, CA 92617 [email protected] “All men by nature desire knowledge." Aristotle Version 0.2 – July 2014 Revision History: • Jan. 2014, First version is released. • Feb. 2014, Uploaded on arXiv.org for public access. • Jul. 2014, Version 0.2 is released. – Table of Contents is added for easy reference. – Fixes few grammatical errors, changes the organization and extends the section of systematic fountain code constructions arXiv:1402.6016v2 [cs.IT] 14 Jul 2014 1 GRAPH CODES AND THEIR APPLICATIONS 2014 DRAFT CONTENTS 1 Abstract 3 2 Introduction 4 2.1 Notation ........................................ 4 2.2 ChannelModelandLinearCodes . ..... 5 2.3 IncrementalRedundancy . ..... 6 3 Linear Fountain Codes 8 3.1 High density Fountain codes: Maximum Likelihood Decoding .......... 11 3.2 Low Density Fountain codes: BP decoding and LT Codes . .......... 14 3.3 Asymptotical performance of LT codes under BP Decoding . ........... 20 3.4 Expected Ripple size and Degree Distribution Design . ............. 23 3.5 Systematic Constructions of LT codes . ......... 26 3.6 Generalizations/Extensions of LT codes: Unequal Error Protection . 27 4 Concatenated Linear Fountain Codes 29 4.1 Asymptotically good degree distributions . ............ 30 4.2 Precoding ....................................... 32 4.2.1 TornadoCodesasPrecodes . 33 4.2.2 LDPCCodesasPrecodes . 34 4.2.3 HammingCodesasPrecodes . 36 4.2.4 Repeat and Accumulate Codes as Precodes . ...... 38 4.3 Concatenated Fountain Code Failure Probability . ............ 38 4.4 Systematic Constructions of Concantenated Fountain Codes ........... 40 5 Advanced Topics 45 5.1 Connectionstotherandomgraphtheory . ........ 46 5.2 InactivationDecoding . ...... 49 5.3 Standardized Fountain Codes for Data Streaming .