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International Symposium on Turbo Codes and Iterative Information Processing

Hardware-friendly Probabilistic Min-Sum algorithm for fully-parallel LDPC decoders

Huang–Chang Lee, Chung-Chao Cheng, Yeong-Luh Ueng

Published Aug 1, 2014• 2 citations
Publisher

Abstract

In order to simplify the check node operation of the low-density parity-check (LDPC) decoders, this paper presents a Normalized Probabilistic Min-Sum Algorithm (NPMSA), where the second minimum value is replaced by a probabilistic second minimum value. For NPMSA, the number of required comparisons can be reduced to about half compared to that of the conventional Normalized Min-Sum Algorithm (NMSA). It is shown that the simplification only introduces negligible impact on the bit-error rate performance, especially for codes with a high check node degree. When the proposed NPMSA is applied to the (2048, 1723) RS-LDPC code, the degradation in the error-rate performance is only about 0.05 dB. The hardware implementation shows that a throughput of 45.42 Gbps can be achieved using the proposed NPMSA.

DOI
10.1109/istc.2014.6955094

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In order to simplify the check node operation of the low-density parity-check (LDPC) decoders, this paper presents a Normalized Probabilistic Min-Sum Algorithm (NPMSA), where the second minimum value is replaced by a probabilistic second minimum value. For NPMSA, the number of required comparisons can be reduced to about half compared to that of the conventional Normalized Min-Sum Algorithm (NMSA). It is shown that the simplification only introduces negligible impact on the bit-error rate performance, especially for codes with a high check node degree. When the proposed NPMSA is applied to the (2048, 1723) RS-LDPC code, the degradation in the error-rate performance is only about 0.05 dB. The hardware implementation shows that a throughput of 45.42 Gbps can be achieved using the proposed NPMSA.
In this paper, a modified normalized Min-Sum algorithm (MNMSA) is proposed for decoding irregular Low Density Parity Check Codes (LDPC) with non-uniform degree distribution. The proposed algorithm provides an efficient decoding scheme to enhance the error performance of an irregular LDPC code without increasing the hardware complexity. An efficient 6- bit quantization scheme is utilized in the proposed algorithm with optimally combined normalization and down scaling factors to resolve the magnitude overestimation issue which occurs during iterative message passing process between the nodes. The simulation results demonstrate that the proposed algorithm achieves good decoding performance in terms of Frame Error Rate (FER) and Bit Error Rate (BER) without the requirement of complex arithmetic calculations. Compared to other min- sum based decoding algorithms the decoding process of the proposed MNMSA requires only fewer decoding iterations over wide range of signal- to- noise ratio (SNR) to achieve comparable decoding performance to that of Belief Propagation (BP) algorithm without increasing the hardware complexity.
This paper has presented various min-sum related LDPC decoding algorithms and their typical hardware architectures of check node update in the scenario of parallel implementation. The m-to-2m decoder has been introduced to generate more efficient new hardware implementations of check node update, which can obviously reduce the number of multiplication operations for normalized min-sum algorithm for high rate LDPC codes. Simulations have claimed the performance of normalized min-sum is nearly the same as that of Log-BP, namely the optimal algorithm. In general, this paper has proved that normalized min-sum is good choices as LDPC decoding methods.
This letter presents a heuristic technique for simplifying the parity-check node operation in a relaxed min-sum iterative decoder. The proposed decoder eliminates the second-minimum computation in check nodes, which allows broadcasting the same output to all neighboring variable nodes to alleviate routing problem in VLSI implementations of low-density parity check (LDPC) decoders. The second-minimum, when required, is emulated by adding an offset to the first-minimum. The proposed relaxed decoder also uses a relaxation factor equal to 0.5 to simplify variable nodes. Simulation results for two LDPC codes show the proposed decoding algorithm with only 4-bit quantization closely matches the performance of floating-point normalized/offset min-sum and sum-product decoders in the waterfall region.
This paper proposes a low-complexity min-sum algorithm for decoding low-density parity-check codes. It is an improved version of the single-minimum algorithm where the two-minimum calculation is replaced by one minimum calculation and a second minimum emulation. In the proposed one, variable correction factors that depend on the iteration number are introduced and the second minimum emulation is simplified, reducing by this way the decoder complexity. This proposal improves the performance of the single-minimum algorithm, approaching to the normalized min-sum performance in the water-fall region. Also, the error-floor region is analyzed for the code of the IEEE 802.3an standard showing that the trapping sets are decoded due to a slow down of the convergence of the algorithm. An error-floor free operation below BER=10-15is shown for this code by means of a field-programmable gate array (FPGA)-based hardware emulator. A layered decoder is implemented in a 90-nm CMOS technology achieving 12.8 Gbps with an area of 3.84 mm2.
In this paper, we propose an improvement of the normalized min-sum (MS) decoding algorithm and novel MS decoder architectures with reduced word length using nonuniform quantization schemes for low-density parity-check (LDPC) codes. The proposed normalized MS algorithm introduces a more exact adjustment with two optimized correction factors for check-node-updating computations, while the conventional normalized MS algorithm applies only one correction factor. The proposed algorithm provides a significant performance gain without any additional computation or hardware complexity. The finite word-length analysis in implementing an LDPC decoder is a very important factor since it directly impacts the size of memory to store the intrinsic and extrinsic messages and the overall hardware area in the partially parallel LDPC decoder. The proposed nonuniform quantization scheme can reduce the finite word length while achieving similar performances compared to a conventional quantization scheme. From simulation results, it is shown that the proposed 4-bit nonuniform quantization scheme achieves an acceptable decoding performance, unlike the conventional 4-bit uniform quantization scheme. Finally, the proposed MS decoder architectures by the nonuniform quantization scheme provide significant reductions of 20% and up to 8% for the memory area and combinational logic area, respectively, compared to the conventional 5-bit ones.