Low-density parity-check convolutional codes offer the same good error-correcting performance as low-density parity-check block codes while having the ability to encode and decode arbitrary lengths of data. This makes these codes well suited to certain applications, such as forward error control on packet switching networks. In this paper we propose a decoder architecture for low-density parity-check convolutional codes with very large memories. These codes have very good error correcting properties and as such may be applicable in wireless sensor networks and space communication systems. We discuss a realization of this architecture for a (2048,3,6) code implemented on a field-programmable gate-array.
Low-density parity-check convolutional codes offer the same good error-correcting performance as low-density parity-check block codes while having the ability to encode and decode arbitrary lengths of data. This makes these codes well suited to certain applications, such as forward error control on packet switching networks. In this paper we propose a decoder architecture for low-density parity-check convolutional codes with very large memories. These codes have very good error correcting properties and as such may be applicable in wireless sensor networks and space communication systems. We discuss a realization of this architecture for a (2048,3,6) code implemented on a field-programmable gate-array.
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.
Low-density parity-check (LDPC) codes had a renaissance when they were rediscovered in the 1990’s. Since then LDPC codes have been an important part of the field of error-correcting codes, and have been shown to be able to approach the Shannon capacity, the limit at which we can reliably transmit information over noisy channels. Following this, many modern communications standards have adopted LDPC codes. Error-correction is equally important in protecting data from corruption on a hard-drive as it is in deep-space communications. It is most commonly used for example for reliable wireless transmission of data to mobile devices. For practical purposes, both encoding and decoding need to be of low complexity to achieve high throughput and low power consumption. This thesis provides a literature review of the current state-of-the-art in encoding and decoding of LDPC codes. Message- passing decoders are still capable of achieving the best error-correcting performance, while more recently considered bit-flipping decoders are providing a low-complexity alternative, albeit with some loss in error-correcting performance. An implementation of a low-complexity stochastic bit-flipping decoder is also presented. It is implemented for Graphics Processing Units (GPUs) in a parallel fashion, providing a peak throughput of 1.2 Gb/s, which is significantly higher than previous decoder implementations on GPUs. The error-correcting performance of a range of decoders has also been tested, showing that the stochastic bit-flipping decoder provides relatively good error-correcting performance with low complexity. Finally, a brief comparison of encoding complexities for two code ensembles is also presented.
With the superior error correction capability, low-density parity-check (LDPC) codes have initiated wide scale interests in satellite communication, wireless communication, and storage fields. In the past, various structures of single code-rate LDPC decoders have been reported. However, to cover a wide range of service requirements and diverse interference conditions in wireless applications, LDPC decoders that can operate at both high and low code rates are desirable. In this paper, a 9-k code length multi-rate LDPC decoder architecture is presented and implemented on a Xilinx field-programmable gate array device. Using pin selection, three operating modes, namely, the irregular 1/2 code mode, the regular 5/8 code mode, and the regular 7/8 code mode, are supported. Furthermore, to suppress the error floor level, a characterization on the conditions for short cycles in a LDPC code matrix expanded from a small base matrix is presented, and a cycle elimination algorithm is developed to detect and break such short cycles. The effectiveness of the cycle elimination algorithm has been verified by both simulation and hardware measurements, which show that the error floor is suppressed to a much lower level without incurring any performance penalty. The implemented decoder is tested in an experimental LDPC orthogonal frequency division multiplexing system and achieves the superior measured performance of block error rate below 10/sup -7/ at signal-to-noise ratio of 1.8 dB.
Channel coding is an important building block in communication systems. Low-density parity-check codes is one kind of prominent error correcting codes being considered in next generation industry standards. This paper presents a memory efficient, very high speed decoder architecture suited for quasi-cyclic low-density parity-check codes using modified Min-Sum decoding algorithm. In general, about seventy percent of message memory can be saved over conventional decoder architectures, and the decoding speed can be largely accelerated because of the highly efficient VLSI architecture. Consequently, the proposed approach facilitates the applications of LDPC codes in area/latency sensitive communication systems.
Low-density parity-check codes have recently received extensive attention as a forward error correction scheme in a wide area of applications. The decoding algorithm is inherently parallelizable, allowing communication at high speeds. One of the main disadvantages, however, is large memory requirements for interim storing of decoding data. In this paper, we investigate the performance of a hybrid decoding algorithm, using an approximating early decision algorithm and a regular probability propagation algorithm. When the early decision algorithm fails, the block is re-decoded using a probability propagation decoder. As almost all errors are detectable, the error correction performance of the hybrid algorithm is negligibly detonated. However, simulations still achieve a 32% decrease of memory accesses
Low-density parity-check convolutional codes (LDPC-CC) have interesting error correction features. They have a great potential to become a key error-correcting codes for enhancing reliability of modern digital communication systems, optical systems and storage devices. On the implementation side, however, the design of low-cost low-power and high-throughput LDPC-CC decoders remains challenging. This survey paper provides an overview of the state-of-the-art of different algorithmic optimizations proposed to ease and improve the LDPC-CC decoder implementations. To this end, a summary of the available decoding scheduling approaches is provided. Besides, a complexity analysis, performance comparison and an architectural analysis of LDPC-CC decoders based on different scheduling techniques is detailed.