Design of a GF(64)-LDPC Decoder Based on the EMS Algorithm

International audienceThis paper presents the architecture, performance and implementation results of a serial GF(64)-LDPC decoder based on a reduced-complexity version of the Extended Min-Sum algorithm. The main contributions of this work correspond to the variable node processing, the codeword decision and the elementary check node processing. Post-synthesis area results show that the decoder area is less than 20% of a Virtex 4 FPGA for a decoding throughput of 2.95 Mbps. The implemented decoder presents performance at less than 0.7 dB from the Belief Propagation algorithm for different code lengths and rates. Moreover, the proposed architecture can be easily adapted to decode very high Galois Field orders, such as GF(4096) or higher, by slightly modifying a marginal part of the design

A new Architecture for High Speed, Low Latency NB-LDPC Check Node Processing

International audience—Non-binary low-density parity-check codes have superior communications performance compared to their binary counterparts. However, to be an option for future standards, efficient hardware architectures must be developed. State-of-the-art decoding algorithms lead to architectures suffering from low throughput and high latency. The check node function accounts for the largest part of the decoders overall complexity. In this paper a new hardware aware check node algorithm and its architecture is proposed. It has state-of-the-art communications performance while reducing the decoding complexity. The presented architecture has a 14 times higher area efficiency, increases the energy efficiency by factor 2.5 and reduces the latency by factor of 3.5 compared to a state-of-the-art architecture

Architectures for soft-decision decoding of non-binary codes

En esta tesis se estudia el dise¿no de decodificadores no-binarios para la correcci'on de errores en sistemas de comunicaci'on modernos de alta velocidad. El objetivo es proponer soluciones de baja complejidad para los algoritmos de decodificaci'on basados en los c'odigos de comprobaci'on de paridad de baja densidad no-binarios (NB-LDPC) y en los c'odigos Reed-Solomon, con la finalidad de implementar arquitecturas hardware eficientes. En la primera parte de la tesis se analizan los cuellos de botella existentes en los algoritmos y en las arquitecturas de decodificadores NB-LDPC y se proponen soluciones de baja complejidad y de alta velocidad basadas en el volteo de s'¿mbolos. En primer lugar, se estudian las soluciones basadas en actualizaci'on por inundaci 'on con el objetivo de obtener la mayor velocidad posible sin tener en cuenta la ganancia de codificaci'on. Se proponen dos decodificadores diferentes basados en clipping y t'ecnicas de bloqueo, sin embargo, la frecuencia m'axima est'a limitada debido a un exceso de cableado. Por este motivo, se exploran algunos m'etodos para reducir los problemas de rutado en c'odigos NB-LDPC. Como soluci'on se propone una arquitectura basada en difusi'on parcial para algoritmos de volteo de s'¿mbolos que mitiga la congesti'on por rutado. Como las soluciones de actualizaci 'on por inundaci'on de mayor velocidad son sub-'optimas desde el punto de vista de capacidad de correci'on, decidimos dise¿nar soluciones para la actualizaci'on serie, con el objetivo de alcanzar una mayor velocidad manteniendo la ganancia de codificaci'on de los algoritmos originales de volteo de s'¿mbolo. Se presentan dos algoritmos y arquitecturas de actualizaci'on serie, reduciendo el 'area y aumentando de la velocidad m'axima alcanzable. Por 'ultimo, se generalizan los algoritmos de volteo de s'¿mbolo y se muestra como algunos casos particulares puede lograr una ganancia de codificaci'on cercana a los algoritmos Min-sum y Min-max con una menor complejidad. Tambi'en se propone una arquitectura eficiente, que muestra que el 'area se reduce a la mitad en comparaci'on con una soluci'on de mapeo directo. En la segunda parte de la tesis, se comparan algoritmos de decodificaci'on Reed- Solomon basados en decisi'on blanda, concluyendo que el algoritmo de baja complejidad Chase (LCC) es la soluci'on m'as eficiente si la alta velocidad es el objetivo principal. Sin embargo, los esquemas LCC se basan en la interpolaci'on, que introduce algunas limitaciones hardware debido a su complejidad. Con el fin de reducir la complejidad sin modificar la capacidad de correcci'on, se propone un esquema de decisi'on blanda para LCC basado en algoritmos de decisi'on dura. Por 'ultimo se dise¿na una arquitectura eficiente para este nuevo esquemaGarcía Herrero, FM. (2013). Architectures for soft-decision decoding of non-binary codes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/33753TESISPremiad

High Performance Decoder Architectures for Error Correction Codes

Due to the rapid development of the information industry, modern communication and storage systems require much higher data rates and reliability to server various demanding applications. However, these systems suffer from noises from the practical channels. Various error correction codes (ECCs), such as Reed-Solomon (RS) codes, convolutional codes, turbo codes, Low-Density Parity-Check (LDPC) codes and so on, have been adopted in lots of current standards. With the increasing data rate, the research of more advanced ECCs and the corresponding efficient decoders will never stop.Binary LDPC codes have been adopted in lots of modern communication and storage applications due their superior error performance and efficient hardware decoder implementations. Non-binary LDPC (NB-LDPC) codes are an important extension of traditional binary LDPC codes. Compared with its binary counterpart, NB-LDPC codes show better error performance under short to moderate block lengths and higher order modulations. Moreover, NB-LDPC codes have lower error floor than binary LDPC codes. In spite of the excellent error performance, it is hard for current communication and storage systems to adopt NB-LDPC codes due to complex decoding algorithms and decoder architectures. In terms of hardware implementation, current NB-LDPC decoders need much larger area and achieve much lower data throughput.Besides the recently proposed NB-LDPC codes, polar codes, discovered by Ar{\i}kan, appear as a very promising candidate for future communication and storage systems. Polar codes are considered as a major breakthrough in recent coding theory society. Polar codes are proved to be capacity achieving codes over binary input symmetric memoryless channels. Besides, polar codes can be decoded by the successive cancelation (SC) algorithm with of complexity of $\mathcal{O}(N\log_2 N)$, where $N$ is the block length. The main sticking point of polar codes to date is that their error performance under short to moderate block lengths is inferior compared with LDPC codes or turbo codes. The list decoding technique can be used to improve the error performance of SC algorithms at the cost higher computational and memory complexities. Besides, the hardware implementation of current SC based decoders suffer from long decoding latency which is unsuitable for modern high speed communications.ECCs also find their applications in improving the reliability of network coding. Random linear network coding is an efficient technique for disseminating information in networks, but it is highly susceptible to errors. K\ {o}tter-Kschischang (KK) codes and Mahdavifar-Vardy (MV) codes are two important families of subspace codes that provide error control in noncoherent random linear network coding. List decoding has been used to decode MV codes beyond half distance. Existing hardware implementations of the rank metric decoder for KK codes suffer from limited throughput, long latency and high area complexity. The interpolation-based list decoding algorithm for MV codes still has high computational complexity, and its feasibility for hardware implementations has not been investigated.In this exam, we present efficient decoding algorithms and hardware decoder architectures for NB-LDPC codes, polar codes, KK and MV codes. For NB-LDPC codes, an efficient shuffled decoder architecture is presented to reduce the number of average iterations and improve the throughput. Besides, a fully parallel decoder architecture for NB-LDPC codes with short or moderate block lengths is also presented. Our fully parallel decoder architecture achieves much higher throughput and area efficiency compared with the state-of-art NB-LDPC decoders. For polar codes, a memory efficient list decoder architecture is first presented. Based on our reduced latency list decoding algorithm for polar codes, a high throughput list decoder architecture is also presented. At last, we present efficient decoder architectures for both KK and MV codes

VLSI algorithms and architectures for non-binary-LDPC decoding

Tesis por compendio[EN] This thesis studies the design of low-complexity soft-decision Non-Binary Low-Density Parity-Check (NB-LDPC) decoding algorithms and their corresponding hardware architectures suitable for decoding high-rate codes at high throughput (hundreds of Mbps and Gbps). In the first part of the thesis the main aspects concerning to the NB-LDPC codes are analyzed, including a study of the main bottlenecks of conventional softdecision decoding algorithms (Q-ary Sum of Products (QSPA), Extended Min-Sum (EMS), Min-Max and Trellis-Extended Min-Sum (T-EMS)) and their corresponding hardware architectures. Despite the limitations of T-EMS algorithm (high complexity in the Check Node (CN) processor, wiring congestion due to the high number of exchanged messages between processors and the inability to implement decoders over high-order Galois fields due to the high decoder complexity), it was selected as starting point for this thesis due to its capability to reach high-throughput. Taking into account the identified limitations of the T-EMS algorithm, the second part of the thesis includes six papers with the results of the research made in order to mitigate the T-EMS disadvantages, offering solutions that reduce the area, the latency and increase the throughput compared to previous proposals from literature without sacrificing coding gain. Specifically, five low-complexity decoding algorithms are proposed, which introduce simplifications in different parts of the decoding process. Besides, five complete decoder architectures are designed and implemented on a 90nm Complementary Metal-Oxide-Semiconductor (CMOS) technology. The results show an achievement in throughput higher than 1Gbps and an area less than 10 mm2. The increase in throughput is 120% and the reduction in area is 53% compared to previous implementations of T-EMS, for the (837,726) NB-LDPC code over GF(32). The proposed decoders reduce the CN area, latency, wiring between CN and Variable Node (VN) processor and the number of storage elements required in the decoder. Considering that these proposals improve both area and speed, the efficiency parameter (Mbps / Million NAND gates) is increased in almost five times compared to other proposals from literature. The improvements in terms of area allow us to implement NB-LDPC decoders over high-order fields which had not been possible until now due to the highcomplexity of decoders previously proposed in literature. Therefore, we present the first post-place and route report for high-rate codes over high-order fields higher than Galois Field (GF)(32). For example, for the (1536,1344) NB-LDPC code over GF(64) the throughput is 1259Mbps occupying an area of 28.90 mm2. On the other hand, a decoder architecture is implemented on a Field Programmable Gate Array (FPGA) device achieving 630 Mbps for the high-rate (2304,2048) NB-LDPC code over GF(16). To the best knowledge of the author, these results constitute the highest ones presented in literature for similar codes and implemented on the same technologies.[ES] En esta tesis se aborda el estudio del diseño de algoritmos de baja complejidad para la decodificación de códigos de comprobación de paridad de baja densidad no binarios (NB-LDPC) y sus correspondientes arquitecturas apropiadas para decodificar códigos de alta tasa a altas velocidades (cientos de Mbps y Gbps). En la primera parte de la tesis los principales aspectos concernientes a los códigos NB-LDPC son analizados, incluyendo un estudio de los principales cuellos de botella presentes en los algoritmos de decodificación convencionales basados en decisión blanda (QSPA, EMS, Min-Max y T-EMS) y sus correspondientes arquitecturas hardware. A pesar de las limitaciones del algoritmo T-EMS (alta complejidad en el procesador del nodo de chequeo de paridad (CN), congestión en el rutado debido al intercambio de mensajes entre procesadores y la incapacidad de implementar decodificadores para campos de Galois de orden elevado debido a la elevada complejidad), éste fue seleccionado como punto de partida para esta tesis debido a su capacidad para alcanzar altas velocidades. Tomando en cuenta las limitaciones identificadas en el algoritmo T-EMS, la segunda parte de la tesis incluye seis artículos con los resultados de la investigación realizada con la finalidad de mitigar las desventajas del algoritmo T-EMS, ofreciendo soluciones que reducen el área, la latencia e incrementando la velocidad comparado con propuestas previas de la literatura sin sacrificar la ganancia de codificación. Especificamente, cinco algoritmos de decodificación de baja complejidad han sido propuestos, introduciendo simplificaciones en diferentes partes del proceso de decodificación. Además, arquitecturas completas de decodificadores han sido diseñadas e implementadas en una tecnologia CMOS de 90nm consiguiéndose una velocidad mayor a 1Gbps con un área menor a 10 mm2, aumentando la velocidad en 120% y reduciendo el área en 53% comparado con previas implementaciones del algoritmo T-EMS para el código (837,726) implementado sobre campo de Galois GF(32). Las arquitecturas propuestas reducen el área del CN, latencia, número de mensajes intercambiados entre el nodo de comprobación de paridad (CN) y el nodo variable (VN) y el número de elementos de almacenamiento en el decodificador. Considerando que estas propuestas mejoran tanto el área comola velocidad, el parámetro de eficiencia (Mbps / Millones de puertas NAND) se ha incrementado en casi cinco veces comparado con otras propuestas de la literatura. Las mejoras en términos de área nos ha permitido implementar decodificadores NBLDPC sobre campos de Galois de orden elevado, lo cual no habia sido posible hasta ahora debido a la alta complejidad de los decodificadores anteriormente propuestos en la literatura. Por lo tanto, en esta tesis se presentan los primeros resultados incluyendo el emplazamiento y rutado para códigos de alta tasa sobre campos finitos de orden mayor a GF(32). Por ejemplo, para el código (1536,1344) sobre GF(64) la velocidad es 1259 Mbps ocupando un área de 28.90 mm2. Por otro lado, una arquitectura de decodificador ha sido implementada en un dispositivo FPGA consiguiendo 660 Mbps de velocidad para el código de alta tasa (2304,2048) sobre GF(16). Estos resultados constituyen, según el mejor conocimiento del autor, los mayores presentados en la literatura para códigos similares implementados para las mismas tecnologías.[CA] En esta tesi s'aborda l'estudi del disseny d'algoritmes de baixa complexitat per a la descodificació de codis de comprovació de paritat de baixa densitat no binaris (NB-LDPC), i les seues corresponents arquitectures per a descodificar codis d'alta taxa a altes velocitats (centenars de Mbps i Gbps). En la primera part de la tesi els principals aspectes concernent als codis NBLDPC són analitzats, incloent un estudi dels principals colls de botella presents en els algoritmes de descodificació convencionals basats en decisió blana (QSPA, EMS, Min-Max i T-EMS) i les seues corresponents arquitectures. A pesar de les limitacions de l'algoritme T-EMS (alta complexitat en el processador del node de revisió de paritat (CN), congestió en el rutat a causa de l'intercanvi de missatges entre processadors i la incapacitat d'implementar descodificadors per a camps de Galois d'orde elevat a causa de l'elevada complexitat), este va ser seleccionat com a punt de partida per a esta tesi degut a la seua capacitat per a aconseguir altes velocitats. Tenint en compte les limitacions identificades en l'algoritme T-EMS, la segona part de la tesi inclou sis articles amb els resultats de la investigació realitzada amb la finalitat de mitigar els desavantatges de l'algoritme T-EMS, oferint solucions que redueixen l'àrea, la latència i incrementant la velocitat comparat amb propostes prèvies de la literatura sense sacrificar el guany de codificació. Específicament, s'han proposat cinc algoritmes de descodificació de baixa complexitat, introduint simplificacions en diferents parts del procés de descodificació. A més, s'han dissenyat arquitectures completes de descodificadors i s'han implementat en una tecnologia CMOS de 90nm aconseguint-se una velocitat major a 1Gbps amb una àrea menor a 10 mm2, augmentant la velocitat en 120% i reduint l'àrea en 53% comparat amb prèvies implementacions de l'algoritme T-EMS per al codi (837,726) implementat sobre camp de Galois GF(32). Les arquitectures proposades redueixen l'àrea del CN, la latència, el nombre de missatges intercanviats entre el node de comprovació de paritat (CN) i el node variable (VN) i el nombre d'elements d'emmagatzemament en el descodificador. Considerant que estes propostes milloren tant l'àrea com la velocitat, el paràmetre d'eficiència (Mbps / Milions deportes NAND) s'ha incrementat en quasi cinc vegades comparat amb altres propostes de la literatura. Les millores en termes d'àrea ens ha permès implementar descodificadors NBLDPC sobre camps de Galois d'orde elevat, la qual cosa no havia sigut possible fins ara a causa de l'alta complexitat dels descodificadors anteriorment proposats en la literatura. Per tant, nosaltres presentem els primers reports després de l'emplaçament i rutat per a codis d'alta taxa sobre camps finits d'orde major a GF(32). Per exemple, per al codi (1536,1344) sobre GF(64) la velocitat és 1259 Mbps ocupant una àrea de 28.90 mm2. D'altra banda, una arquitectura de descodificador ha sigut implementada en un dispositiu FPGA aconseguint 660 Mbps de velocitat per al codi d'alta taxa (2304,2048) sobre GF(16). Estos resultats constitueixen, per al millor coneixement de l'autor, els millors presentats en la literatura per a codis semblants implementats per a les mateixes tecnologies.Lacruz Jucht, JO. (2016). VLSI algorithms and architectures for non-binary-LDPC decoding [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/73266TESISCompendi

Reduced-complexity Non-Binary LDPC decoder for high-order Galois fields based on Trellis Min-Max algorithm

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Non-binary LDPC codes outperform its binary counterparts in different scenarios. However, they require a considerable increase in complexity, especially in the check-node processor, for high-order Galois fields higher than GF(16). To overcome this drawback, we propose an approximation for the Trellis Min-Max algorithm which allows us to reduce the number of exchanged messages between check node and variable node compared to previous proposals from literature. On the other hand, we reduce the complexity in the check-node processor, keeping the parallel computation of messages. We implemented a layered scheduled decoder, based on this algorithm, in a 90nm CMOS technology for the (837,723) NB-LDPC code over GF(32) and the (1536,1344) over GF(64), achieving an area saving of 16% and 36% for the check-node and 10% and 12% for the whole decoder, respectively. The throughput is 1.07 Gbps and 1.26 Gbps, which outperforms the state-of-the-art of high-rate decoders with high GF order from literature.This work was supported in part by the Spanish Ministerio de Ciencia e Innovacion under Grant TEC2011-27916 and Grant TEC2012-38558-C02-02 and in part by Generalitat Valenciana under Grant GV/2014/011.Lacruz, JO.; García Herrero, FM.; Canet Subiela, MJ.; Valls Coquillat, J. (2016). Reduced-complexity Non-Binary LDPC decoder for high-order Galois fields based on Trellis Min-Max algorithm. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 1-11. https://doi.org/10.1109/TVLSI.2016.2514484S11

Energy-Efficient Decoders of Near-Capacity Channel Codes.

Channel coding has become essential in state-of-the-art communication and storage systems for ensuring reliable transmission and storage of information. Their goal is to achieve high transmission reliability while keeping the transmit energy consumption low by taking advantage of the coding gain provided by these codes. The lowest total system energy is achieved with a decoder that provides both good coding gain and high energy-efficiency. This thesis demonstrates the VLSI implementation of near-capacity channel decoders using the LDPC, nonbinary LDPC (NB-LDPC) and polar codes with an emphasis of reducing the decode energy. LDPC code is a widely used channel code due to its excellent error-correcting performance. However, memory dominates the power of high-throughput LDPC decoders. Therefore, these memories are replaced with a novel non-refresh embedded DRAM (eDRAM) taking advantage of the deterministic memory access pattern and short access window of the decoding algorithm to trade off retention time for faster access speed. The resulting LDPC decoder with integrated eDRAMs achieves state-of-the-art area- and energy-efficiency. NB-LDPC code achieves better error-correcting performance than LDPC code at the cost of higher decoding complexity. However, the factor graph is simplified, permitting a fully parallel architecture with low wiring overhead. To reduce the dynamic power of the decoder, a fine-grained dynamic clock gating technique is applied based on node-level convergence. This technique greatly reduces dynamic power allowing the decoder to achieve high energy-efficiency while achieving high throughput. The recently invented polar code has a similar error-correcting performance to LDPC code of comparable block length. However, the easy reconfigurability of code rate as well as block length makes it desirable in numerous applications where LDPC is not competitive. In addition, the regular structure and simple processing enables a highly efficient decoder in terms of area and power. Using the belief propagation algorithm with architectural and memory improvements, a polar decoder is demonstrated achieving high throughput and high energy- and area-efficiency. The demonstrated energy-efficient decoders have advanced the state-of-the-art. The decoders will allow the continued reduction of decode energy for the latest communication and storage applications. The developed techniques are widely applicable to designing low-power DSP processors.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108731/1/parkyoun_1.pd

연판정 오류정정을 위한 낮은 복잡도의 블록 터보부호 복호화 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 성원용.As the throughput needed for communication systems and storage devices increases, high-performance forward error correction (FEC), especially soft-decision (SD) based technique, becomes essential. In particular, block turbo codes (BTCs) and low-density parity check (LDPC) codes are considered as candidate FEC codes for the next generation systems, such as beyond-100Gbps optical networks and under-20nm NAND flash memory devices, which require capacity-approaching performance and very low error floor. The BTCs have definite strengths in diversity and encoding complexity because they generally employ a two-dimensional structure, which enables sub-frame level decoding for the row or column code-words. This sub-frame level decoding gives a strong advantage for parallel processing. The BTC decoding throughput can be improved by applying a low-complexity algorithm to the small level decoding or by running multiple sub-frame decoding modules simultaneously. In this dissertation, we develop high-throughput BTC decoding software that pursuits these advantages. The first part of this dissertation is devoted to finding efficient test patterns in the Chase-Pyndiah algorithm. Although the complexity of this algorithm linearly increases according to the number of the test patterns, it naively considers all possible patterns containing least reliable positions. As a result, consideration of one more position nearly doubles the complexity. To solve this issue, we first introduce a new position selection criterion that excludes some of the selected ones having a relatively large reliability. This technique excludes the selection of sufficiently reliable positions, which greatly reduces the complexity. Secondly, we propose a pattern selection scheme considering the error coverage. We define the error coverage factor that represents the influence on the error-correcting performance and compute it by analyzing error events. Based on the computed factor, we select the patterns with the greedy algorithm. By using these methods, we can flexibly balance the complexity and the performance. The second part of this dissertation is developing low-complexity soft-output processing methods needed for BTC decoding. In the Chase-Pyndiah algorithm, the soft-output is updated in two different ways according to whether competing code-words exist on the updating positions or not. If the competing code-words exist, the Euclidean distance between the soft-input signal and the code-words that are generated from the test patterns is used. However, the cost of distance computation is very high and linearly increases with the sub-frame length. We identify computationally redundant positions and optimize the computing process by ignoring them. If the competing ones do not exist, the reliability factor that should be pre-determined by an extensive search is demanded. To avoid this, we propose adaptive determination methods, which provides even better error-correcting performance. In addition, we investigate the Pyndiah's soft-output computation and find its drawbacks that appear during the approximation process. To remove the drawbacks, we replace the updating method of the positions that are expected to be seriously damaged by the approximation with the reliability factor-based one, which is much simpler, even though they have the competing words. This dissertation also develops a graphics processing unit (GPU) based BTC decoding program. In order to hide the latency of arithmetic and memory access operations, this software applies the kernel structure that processes multiple BTC-words and allocates multiple sub-frames to each thread-block. Global memory access optimization and data compression, which demands less shared memory space, are also employed. For efficient mapping of the Chase-Pyndiah algorithm onto GPUs, we propose parallel processing schemes employing efficient reduction algorithms and provide step-by-step parallel algorithms for the algebraic decoding. The last part of this dissertation is devoted to summarizing the developed decoding method and comparing it with the decoding of the LDPC convolutional code (CC), which is currently reported as the most powerful candidate for the 100Gbps optical network. We first investigate the complexity reduction and the error rate performance improvement of the developed method. Then, we analyze the complexity of the LDPC-CC decoding and compare it with the developed BTC decoding for the 20% overhead codes. This dissertation is intended to develop high-throughput SD decoding software by introducing complexity reduction techniques for the Chase-Pyndiah algorithm and efficient parallel processing methods, and to emphasize the competitiveness of the BTC. The proposed decoding methods and parallel processing algorithms verified in the GPU-based systems are also applicable to hardware-based ones. By implementing hardware-based decoders that employ the developed methods in this dissertation, significant improvements on the throughputs and the energy efficiency can be obtained. Moreover, thanks to the wide rate coverage of the BTC, the developed techniques can be applied to many high-throughput error correction applications, such as the next-generation optical network and storage device systems.Chapter 1 Introduction 1 1.1 Turbo Codes 1 1.2 Applications of Turbo Codes 4 1.3 Outline of the Dissertation 5 Chapter 2 Encoding and Iterative Decoding of Block Turbo Codes 7 2.1 Introduction 7 2.2 Encoding Procedure of Shortened-Extended BTCs 9 2.3 Scheduling Methods for Iterative Decoding 9 2.3.1 Serial Scheduling 10 2.3.2 Parallel Scheduling 10 2.3.3 Replica Scheduling 11 2.4 Elementary Decoding with Chase-Pyndiah Algorithm 13 2.4.1 Chase-Pyndiah Algorithm for Extended BTCs 13 2.4.2 Reliability Computation of the ML Code-Word 17 2.4.3 Algebraic Decoding for SEC and DEC BCH Codes 20 2.5 Issues of Chase-Pyndiah Algorithm 23 Chapter 3 Complexity Reduction Techniques for Code-Word Set Generation of the Chase-Pyndiah Algorithm 24 3.1 Introduction 24 3.2 Adaptive Selection of LRPs 25 3.2.1 Selection Constraints of LRPs 25 3.2.2 Simulation Results 26 3.3 Test Pattern Selection 29 3.3.1 The Error Coverage Factor of Test Patterns 30 3.3.2 Greedy Selection of Test Patterns 33 3.3.3 Simulation Results 34 3.4 Concluding Remarks 34 Chapter 4 Complexity Reduction Techniques for Soft-Output Update of the Chase-Pyndiah Algorithm 37 4.1 Introduction 37 4.2 Distance Computation 38 4.2.1 Position-Index List Based Method 39 4.2.2 Double Index Set-Based Method 42 4.2.3 Complexity Analysis 46 4.2.4 Simulation Results 47 4.3 Reliability Factor Determination 49 4.3.1 Refinement of Distance-Based Reliability Factor 51 4.3.2 Adaptive Determination of the Reliability Factor 51 4.3.3 Simulation Results 53 4.4 Accuracy Improvement in Extrinsic Information Update 54 4.4.1 Drawbacks of the Sub-Optimal Update 55 4.4.2 Low-Complexity Extrinsic Information Update 58 4.4.3 Simulation Results 59 4.5 Concluding Remarks 61 Chapter 5 High-Throughput BTC Decoding on GPUs 64 5.1 Introduction 64 5.2 BTC Decoder Architecture for GPU Implementations 66 5.3 Memory Optimization 68 5.3.1 Global Memory Access Reduction 68 5.3.2 Improvement of Global Memory Access Coalescing 68 5.3.3 Efficient Shared Memory Control with Data Compression 70 5.3.4 Index Parity Check Scheme 73 5.4 Parallel Algorithms with the CUDA Shuffle Function 77 5.5 Implementation of Algebraic Decoder 78 5.5.1 Galois Field Operations with Look-Up Tables 78 5.5.2 Error-Locator Polynomial Setting with the LUTs 81 5.5.3 Parallel Chien Search with the LUTs 84 5.6 Simulation Results 85 5.7 Concluding Remarks 89 Chapter 6 Competitiveness of BTCs as FEC codes for the Next-Generation Optical Networks 91 6.1 Introduction 91 6.2 The Complexity Reduction of the Modified Chase-Pyndiah Algorithm 92 6.2.1 Summary of the Complexity Reduction 92 6.2.2 The Error-Correcting Performance 94 6.3 Comparison of BTCs and LDPC-CCs 97 6.3.1 Complexity Analysis of the LDPC-CC Decoding 97 6.3.2 Comparison of the 20% Overhead BTC and LDPC-CC 100 6.4 Concluding Remarks 101 Chapter 7 Conclusion 102 Bibliography 105 국문 초록 113Docto