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IEICE Transactions on Communications

An Efficient LDPC Decoder Architecture with a High-Performance Decoding Algorithm

Jui-Hui Hung, Sau-Gee Chen

Published Jan 1, 2010• 0 citations
Publisher

Abstract

In this work, a high performance LDPC decoder architecture is presented. It is a partially-parallel architecture for low-complexity consideration. In order to eliminate the idling time and hardware complexity in conventional partially-parallel decoders, the decoding process, decoder architecture and memory structure are optimized. Particularly, the parity-check matrix is optimally partitioned into four unequal sub-matrices that lead to high efficiency in hardware sharing. As a result, it can handle two different codewords simultaneously with 100% hardware utilization. Furthermore, for minimizing the performance loss due to round-off errors in fixed-point implementations, the well-known modified min-sum decoding algorithm is enhanced by our recently proposed high-performance CMVP decoding algorithm. Overall, the proposed decoder has high throughput, low complexity, and good BER performances. In the circuit implementation example of the (576, 288) parity check matrix for IEEE 802.16e standard, the decoder achieves a data rate of 5.5Gbps assuming 10 decoding iterations and 7 quantization bits, with a small area of 653K gates, based on UMC 90nm process technology.

DOI
10.1587/transcom.e93.b.2980

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In this work, a high performance LDPC decoder architecture is presented. It is a partially-parallel architecture for low-complexity consideration. In order to eliminate the idling time and hardware complexity in conventional partially-parallel decoders, the decoding process, decoder architecture and memory structure are optimized. Particularly, the parity-check matrix is optimally partitioned into four unequal sub-matrices that lead to high efficiency in hardware sharing. As a result, it can handle two different codewords simultaneously with 100% hardware utilization. Furthermore, for minimizing the performance loss due to round-off errors in fixed-point implementations, the well-known modified min-sum decoding algorithm is enhanced by our recently proposed high-performance CMVP decoding algorithm. Overall, the proposed decoder has high throughput, low complexity, and good BER performances. In the circuit implementation example of the (576, 288) parity check matrix for IEEE 802.16e standard, the decoder achieves a data rate of 5.5Gbps assuming 10 decoding iterations and 7 quantization bits, with a small area of 653K gates, based on UMC 90nm process technology.
In this paper, an area efficient partially parallel decoder architecture suited for (modified) min-sum decoding algorithm for general high rate quasi-cyclic low-density parity-check (QC-LDPC) codes is proposed. To reduce the hardware complexity for parallel processing, an efficient data scheduling unit is presented. The optimized partially parallel decoder architecture can linearly increase the decoding throughput with small hardware overhead. Typically, over 30% of memory can be saved with the architecture presented in this paper. Consequently, the proposed approach facilitates the applications of LDPC codes in area/power sensitive high speed communication systems.
In this paper, a memory efficient partially parallel decoder architecture suited for high rate quasi-cyclic low-density parity-check codes using (modified) min-sum decoding algorithm is proposed. In general, more than thirty percent of memory can be saved over conventional partially parallel decoder architectures. To reduce the computation delay of check-node processing unit, an efficient architecture based on variants of rank order filter is presented. The optimized partially parallel decoder architecture can linearly increase the decoding throughput with small hardware overhead. Consequently, the proposed approach facilitates the applications of LDPC codes in area/power sensitive high speed communication systems
This paper studies low-complexity high-speed decoder architectures for quasi-cyclic low density parity check (QC-LDPC) codes. Algorithmic transformation and architectural level optimization are incorporated to reduce the critical path. Enhanced partially parallel decoding architectures are proposed to linearly increase the throughput of conventional partially parallel decoders through introducing a small percentage of extra hardware. Based on the proposed architectures, a (8176, 7154) Euclidian geometry-based QC-LDPC code decoder is implemented on Xilinx field programmable gate array (FPGA) Virtex-II 6000, where an efficient nonuniform quantization scheme is employed to reduce the size of memories storing soft messages. FPGA implementation results show that the proposed decoder can achieve a maximum (source data) decoding throughput of 172 Mb/s at 15 iterations
The bit-error-rate (BER) performance of an LDPC decoding algorithm will be seriously degraded when the algorithm is realized with fixed-point implementation in practical applications, due to the introduced quantization errors and rounding errors. To remedy the problem, this paper proposes an improved min-sum algorithm (MSA), called CMVP algorithm. It achieves better performances than the popular min-sum algorithm (MSA), under the condition of the same fixed-point precision. Besides, the hardware overhead of the new algorithm over conventional MSA is small. On the other hand, under the condition of comparable performances, MSA algorithm needs a higher fixed-point precision and hardware costs than the new CMVP algorithm, according to the simulations and hardware synthesis results. The new algorithm also works well in a wide range of code rates and code lengths.
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.
In this paper, a combined Low-Density Parity-Check (LDPC) code decoding design method, called modified Block-Type LDPC (B-LDPC), for realistic LDPC coding system architectures is presented. The B-LDPC code, which is a special class of quasi-cyclic LDPC (QC-LDPC), has an efficient encoding algorithm owing to the simple structure of their parity-check matrices. A proposed distribution of irregular parity-check matrix for the modified B-LDPC is developed so that we can obtain an area-efficient decoder design, good error correction performance, and achievable architecture implementation. The modified B-LDPC code decoding utilizes the iterative min-sum algorithm (MSA) and its decoding architecture design employs the non-overlapping operations of bit node unit (BNU) and check node unit (CNU). Different block matrix sizes for parity-check matrix can be adopted so that the modified B-LDPC code decoding improves the throughput without obvious performance degradation.