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FPGA-based LDPC decoder design

Radivoje Zarubica

Published Jan 1, 2007• 0 citations
OpenAlex

Abstract

LowDensity Parity Check(LDPC)decoders imple- menting longblocklength codesrequire semi-parallel design. One challenge whenimplementing these codes onField Programmable GateArrays(FPGAs)isefficiently storing messages neededin theiteration process. Tomeetthis challenge, anewclass ofLDPC codesispresented. Theycombineregularity ofimplementation withreduction oftimeneededfordecoding process, anddonot suffer ofanysignificant performance loss duetotheir structure. I.INTRODUCTION Lowdensity parity check(LDPC)codes havegarnered a great deal ofattention intheerror control coding field recently, duetotheability toimplement soft-decision decoders that perform veryneartheShannon bound(for longblocklengths). Thedecoding algorithm isiterative, using message passing amongnodes inaTanner graph representation ofthecode, and allows parallel, orsemi-parallel processing inthecomputation tospeed decoding.

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LowDensity Parity Check(LDPC)decoders imple- menting longblocklength codesrequire semi-parallel design. One challenge whenimplementing these codes onField Programmable GateArrays(FPGAs)isefficiently storing messages neededin theiteration process. Tomeetthis challenge, anewclass ofLDPC codesispresented. Theycombineregularity ofimplementation withreduction oftimeneededfordecoding process, anddonot suffer ofanysignificant performance loss duetotheir structure. I.INTRODUCTION Lowdensity parity check(LDPC)codes havegarnered a great deal ofattention intheerror control coding field recently, duetotheability toimplement soft-decision decoders that perform veryneartheShannon bound(for longblocklengths). Thedecoding algorithm isiterative, using message passing amongnodes inaTanner graph representation ofthecode, and allows parallel, orsemi-parallel processing inthecomputation tospeed decoding.
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.
This thesis is focused on the design and implementation of binary low-density parity-check (LDPC) code decoders for high-speed modern communication systems. The basic of LDPC codes and the performance and bottlenecks, in terms of complexity and hardware efficiency, of the main soft-decision and hard-decision decoding algorithms (such as Min-Sum, Optimized 2-bit Min-Sum and Reliability-based iterative Majority-Logic) are analyzed. The complexity and performance of those algorithms are improved to allow efficient hardware architectures.\n\nA new decoding algorithm called One-Minimum Min-Sum is proposed. It reduces considerably the complexity of the check node update equations of the Min-Sum algorithm. The second minimum is estimated from the first minimum value by a means of a linear approximation that allows a dynamic adjustment. The Optimized 2-bit Min-Sum algorithm is modified to initialize it with the complete LLR values and to introduce the extrinsic information in the messages sent from the variable nodes. Its variable node equation is reformulated to reduce its complexity. Both algorithms were tested for the (2048,1723) RS-based LDPC code and (16129,15372) LDPC code using an FPGA-based hardware emulator. They exhibit BER performance very close to Min-Sum algorithm and do not introduce early error-floor. \n\nIn order to show the hardware advantages of the proposed algorithms, hardware decoders were implemented in a 90 nm CMOS process and FPGA devices based on two types of architectures: full-parallel and partial-parallel one with horizontal layered schedule. The results show that the decoders are more area-time efficient than other published decoders and that the low-complexity of the Modified Optimized 2-bit Min-Sum allows the implementation of 10 Gbps decoders in current FPGA devices. \n\nFinally, a new hard-decision decoding algorithm, the Historical-Extrinsic Reliability-Based Iterative Decoder, is presented. This algorithm introduces the new idea of considering hard-decision votes as soft-decision to compute the extrinsic information of previous iterations. It is suitable for high-rate codes and improves the BER performance of the previous RBI-MLGD algorithms, with similar complexity.
Because of their excellent error-correcting performance, low-density parity-check (LDPC) codes have recently attracted a lot of attention. In this paper, we are interested in the practical LDPC code decoder hardware implementations. The direct fully parallel decoder implementation usually incurs too high hardware complexity for many real applications, thus partly parallel decoder design approaches that can achieve appropriate trade-offs between hardware complexity and decoding throughput are highly desirable. Applying a joint code and decoder design methodology, we develop a high-speed -regular LDPC code partly parallel decoder architecture based on which we implement a -bit, rate- -regular LDPC code decoder on Xilinx FPGA device. This partly parallel decoder supports a maximum symbol throughput of Mbps and achieves BER at 2 dB over AWGN channel while performing maximum decoding iterations.
Low density parity check (LDPC) codes over are an extension of binary LDPC codes with significantly higher performance. However, the computational complexity of the encoders/decoders for these codes is also higher. Hence there is a substantial lack of hardware implementations for LDPC over codes. This paper proposes a novel variation of the belief propagation algorithm for LDPC codes. The new algorithm results in a reduced hardware complexity when imple- mented in VLSI. The serial architecture of the novel decoding algorithm and two other algorithms for LDPC over are implemented on an FPGA. The results show that the proposed algorithm has substantial advantages over existing methods. We show that the implementation of LDPC over decoder is feasible for short to medium length codes. The additional com- plexity of the decoder is balanced by the superior performance of LDPC codes.
Low-density parity-check (LDPC) codes are very efficient error control codes that are being considered for use in many next-generation communication systems. In this study low complexity soft-input, soft-output (SISO) field programmable gate arrays (FPGA) implementations of a novel logarithmic sum-product (LogSP) iterative LDPC decoder and a recently proposed simplified soft Euclidean distance (SSD) iterative LDPC decoder are presented, and their complexities and performance are compared. These implementations operate over any choice of parity check matrix (including those randomly generated, structurally generated and either systematic or non-systematic) and can be parametrically adapted for any code rate. The proposed implementations are both of very low complexity, because they operate using only sums, subtractions, comparisons and look-up tables, which makes them particularly suitable for FPGA realisation. The SSD decoder has a lower implementation complexity than the LogSP LDPC decoder and it also offers the advantage of not requiring knowledge of the channel signal-to-noise ratio, unlike most other LDPC decoders.