Low-density parity-check codes (LDPC) are among the most powerful error correcting tools today available. For this reason they became very popular in several applications such as the digital satellite broadcasting system (DVB-S2), wireless local area network (IEEE 802.11n) and metropolitan area network (802.16e). Whereas several code-specific decoders have been proposed in the literature, the implementation of a high performance yet flexible LDPC decoder still is a challenging topic. This work presents a novel formulation of the decoding algorithm that strongly simplifies internal communication requirements and enables the development of decoders supporting generally defined LDPC codes. The resulting architecture is tailored to decode both IEEE 802.11n and IEEE 802.16e LDPC codes, as well as any other code of comparable complexity. The implementation cost deriving from the full flexibility offered by the proposed approach is also evaluated.
Low-density parity-check codes (LDPC) are among the most powerful error correcting tools today available. For this reason they became very popular in several applications such as the digital satellite broadcasting system (DVB-S2), wireless local area network (IEEE 802.11n) and metropolitan area network (802.16e). Whereas several code-specific decoders have been proposed in the literature, the implementation of a high performance yet flexible LDPC decoder still is a challenging topic. This work presents a novel formulation of the decoding algorithm that strongly simplifies internal communication requirements and enables the development of decoders supporting generally defined LDPC codes. The resulting architecture is tailored to decode both IEEE 802.11n and IEEE 802.16e LDPC codes, as well as any other code of comparable complexity. The implementation cost deriving from the full flexibility offered by the proposed approach is also evaluated.
Future technologies such as cognitive radio require flexible and reliable hardware architectures that can be easily configured and adapted to varying coding parameters.The objective of this work is to develop a flexible hardware encoder and decoder for low-density parity-check (LDPC) codes.The design methodologies used for the implementation of a LDPC encoder and decoder are flexible in terms of parity-check matrix, code rate and code length.All these designs are implemented on a programmable chip and tested.Encoder implementations of LDPC codes are optimized for area due to their high complexity.Such designs usually have relatively low data rate.Two new encoder designs are developed that achieve much higher data rates of up to 844 Mbps while requiring more area for implementation.Using structured LDPC codes decreases the encoding complexity and provides design flexibility.The architecture for an encoder is presented that adheres to the structured LDPC codes defined in the IEEE 802.16e standard.A single encoder design is also developed that accommodates different code lengths and code rates and does not require re-synthesis of the design in order to change the encoding parameters.The flexible encoder design for structured LDPC codes is also implemented on a custom chip.The maximum coded data rate of the structured encoder is up to 844 Mbps and for a given code rate its value is independent of the code length.An LDPC decoder is designed and its design methodology is generic.It is applicable to both structured and any randomly generated LDPC codes.The coded data rate of the decoder increases with the increase in the code length.The number of decoding iterations used for the decoding process plays an important role in determining the decoder performance and latency.This design validates the estimated codeword after every iteration and stops the decoding process when the correct codeword is estimated which saves power consumption.For a given paritycheck matrix and signal-to-noise ratio, a procedure to find an optimum value of the maximum number of decoding iterations is presented that considers the affects of power, delay, and error performance.
The Low-Density Parity-Check codes are among the most powerful forward error correcting codes, since they enable to get as close as a fraction of a dB from the Shannon limit.This astonishing performance combined with their relatively simple decoding algorithmmake these codes very attractive for the next digital transmission system generations. Itis already the case for the next digital satellite broadcasting standard (DVB-S2), where an irregular LDPC code has been chosen to protect the downlink information. In this thesis, we focused our research on the iterative decoding algorithms and their hardware implementations. We proposed first a suboptimal algorithm named the λ-min algorithm. It reduces significantly the complexity of the decoder without any significant performance loss, as compared to the belief propagation (BP) algorithm. Then we studied and designed a generic architecture of an LDPC decoder, which has been implemented on a FPGA based platform. This hardware decoder enables to accelerate the simulations more than 500 times as compared to software simulations. Moreover, based on an all-tunable design, our decoder features many facilities: It is possible to configure it for a very wide code family, so that the research for good codes is processed faster ; thanks to the genericity of the processing components, it is also possible to optimize the internal coding format, and even to compare various decoding algorithms and various processing schedules. Finally, our experience in the area of LDPC decoders led us to propose a formal framework for analysing the architectures of LDPC decoders. This framework encompassesboth the datapath (parallelism, node processors architectures) and the control mode associated to the several decoding schedules. Thus within this framework, a classification of the different state-of-the-art LDPC decoders is proposed. Moreover, some synthesis of efficient and unpublished architectures have been also proposed.
The Low-Density Parity-Check codes are among the most powerful forward error correcting codes, since they enable to get as close as a fraction of a dB from the Shannon limit.This astonishing performance combined with their relatively simple decoding algorithmmake these codes very attractive for the next digital transmission system generations. Itis already the case for the next digital satellite broadcasting standard (DVB-S2), where an irregular LDPC code has been chosen to protect the downlink information. In this thesis, we focused our research on the iterative decoding algorithms and their hardware implementations. We proposed first a suboptimal algorithm named the λ-min algorithm. It reduces significantly the complexity of the decoder without any significant performance loss, as compared to the belief propagation (BP) algorithm. Then we studied and designed a generic architecture of an LDPC decoder, which has been implemented on a FPGA based platform. This hardware decoder enables to accelerate the simulations more than 500 times as compared to software simulations. Moreover, based on an all-tunable design, our decoder features many facilities: It is possible to configure it for a very wide code family, so that the research for good codes is processed faster ; thanks to the genericity of the processing components, it is also possible to optimize the internal coding format, and even to compare various decoding algorithms and various processing schedules. Finally, our experience in the area of LDPC decoders led us to propose a formal framework for analysing the architectures of LDPC decoders. This framework encompasses
both the datapath (parallelism, node processors architectures) and the control mode associated to the several decoding schedules. Thus within this framework, a classification of the different state-of-the-art LDPC decoders is proposed. Moreover, some synthesis of efficient and unpublished architectures have been also proposed.
In recent years, the amount of digital data which is stored and transmitted for private and public usage has increased considerably. To allow a save transmission and storage of data despite of error-prone transmission media, error correcting codes are used. A large variety of codes has been developed, and in the past decade low-density parity-check (LDPC) codes which have an excellent error correction performance became more and more popular. Today, low-density parity-check codes have been adopted for several standards, and efficient decoder hardware architectures are known for the chosen structured codes. However, the existing decoder designs lack flexibility as only few structured codes can be decoded with one decoder chip. In consequence, different codes require a redesign of the decoder, and few solutions exist for decoding of codes which are not quasi-cyclic or which are unstructured. In this thesis, three different approaches are presented for the implementation of fully programmable LDPC decoders which can decode arbitrary LDPC codes. As a design study, the first programmable decoder which uses a heuristic mapping algorithm is realized on a field-programmable gate array (FPGA), and error correction curves are measured to verify the correct functionality. The main contribution of this thesis lies in the development of the second and the third architecture and an appropriate mapping algorithm. The proposed fully programmable decoder architectures use one-phase message passing and layered decoding and can decode arbitrary LDPC codes using an optimum mapping and scheduling algorithm. The presented programmable architectures are in fact generalized decoder architectures from which the known decoder architectures for structured LDPC codes can be derived.
After the introduction of iterative coding, Low Density Parity Check (LDPC) codes have received a lot of attention due to their remarkable near Shannon-limit performance and practical decoder implementation. However, when employing an LDPC code for various applications, multiple issues do arise at the simulation, algorithm and implementation levels. The first issue is the performance evaluation of the iterative LDPC decoder in the very low Bit Error Rate (BER) regions. So far, no analytical tool has been developed to evaluate the performance of LDPC codes. Unfortunately standard Monte Carlo (MC) simulations cannot be used for performance estimation in these low BER regions due to prohibitive execution times. The second issue is the efficiency of the decoding algorithm. Due to the presence of short cycles in the bipartite graph, sum-product decoding algorithms lead to considerable performance loss for short block-length LDPC codes and produce error floors for longer codes. In addition, the iterative processing and estimation of soft probabilistic values with these algorithms result in very high computational complexity, which in turn impedes the adoption of LDPC codes for power constrained systems. Another prime objective is to design a high throughput decoder architecture which is capable of supporting multiple rates and variable code lengths within minimal area.
This work aims to address and provide solutions to the above problems. As a solution to the performance estimation problem of LDPC codes, a highly efficient and novel fast BER simulation technique is developed. At the algorithm level, a performance improvement and error floor avoidance method is introduced, and a computationally efficient algorithm is developed for the sum-product decoding of LDPC codes. And finally, at the architecture level, a high throughput multi-rate variable code length implementation is presented which, when implemented, efficiently minimizes device resources while alleviating the routing complexity of the decoder.
Low-density parity-check (LDPC) codes are among the most powerful known error correcting codes and they have been shown to achieve performance very close to the Shannon bound. In practical hardware implementations of LDPC decoders, bit error rate performances are affected strongly by fixed-point representation of processed data and, although many papers have been published in recent years on the subject of LDPC codes, only a few of them report results on the effects of finite precision. In the paper two novel arithmetic approximations for the basic processing operations of the decoding algorithm are presented. The two proposed solutions are analysed in terms of bit error rate performance for different finite precison representations of both external and internal data; the estimated performance loss is comparable to that reported by previous works and limited to approximately 0.1 dB for cases of interests. However the proposed solutions support a reduced complexity formulation of the decoding algorithm, so enabling the implementation of flexible decoders that can be adapted to different LDPC codes, block sizes and code rates.