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IEEE Communications Letters

A Novel Base Graph Based Static Scheduling Scheme for Layered Decoding of 5G LDPC Codes

Kuangda Tian, Hao Wang

Published May 2, 2022• 19 citations
Publisher

Abstract

Quasi-cyclic low-density parity-check (QC-LDPC) codes have been selected as the channel coding scheme for 5G new radio (NR) data channel. In this letter, a novel base graph based static scheduling (BGSS) method is proposed for layered decoding of 5G LDPC codes to accelerate decoding convergence and reduce the average number of iterations (ANI). In the proposed BGSS method, the update order of layers is determined based on row weight, column weight and number of punctured non-zero elements of BG matrix. Three optimization rules are included in BGSS to determine the order: 1) The layer with less punctured non-zero element is updated firstly. 2) The layer with relatively small row weight is updated firstly. 3) The layer which can utilize more recent information is updated firstly. The first rule has the highest priority and the third rule has the lowest priority. Simulation results show that compared with other scheduling method, the proposed method reduces about 1.1 ANI and obtains about 0.05dB performance gain for given LDPC codes.

DOI
10.1109/lcomm.2022.3171658

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Journal of Physics Conference Series•Jun 1, 2021•0 citations
Quasi-cyclic low-density parity-check (QC-LDPC) codes have been selected as the channel coding scheme for 5G new radio (NR) data channel. In this letter, a novel base graph based static scheduling (BGSS) method is proposed for layered decoding of 5G LDPC codes to accelerate decoding convergence and reduce the average number of iterations (ANI). In the proposed BGSS method, the update order of layers is determined based on row weight, column weight and number of punctured non-zero elements of BG matrix. Three optimization rules are included in BGSS to determine the order: 1) The layer with less punctured non-zero element is updated firstly. 2) The layer with relatively small row weight is updated firstly. 3) The layer which can utilize more recent information is updated firstly. The first rule has the highest priority and the third rule has the lowest priority. Simulation results show that compared with other scheduling method, the proposed method reduces about 1.1 ANI and obtains about 0.05dB performance gain for given LDPC codes.
Quasi-cyclic low-density parity-check codes (QC-LDPC) are selected as the channel coding scheme for the data channel of the new radio (NR) enhanced mobile broadband (eMBB) in fifth-generation (5G) mobile communication technology. Traditional layered scheduling strategies used in 5G LDPC codes improve decoding convergence speed, but fixed scheduling schemes cannot fully utilize dynamic changes in decoded messages. To address this issue, this paper proposes a layered scheduling scheme for 5G LDPC codes based on edge information. By prioritizing updates to layers with minimal changes in edge information, this method reduces decoding complexity and accelerates convergence with minimal performance loss. Simulation results demonstrate that this approach enhances decoding performance by approximately 0.05dB compared to other improved hierarchical scheduling strategies.
Low-density parity-check (LDPC) codes have been chosen for the fifth-generation (5G) new radio (NR) enhanced Mobile Broad Band (eMBB) data channel. Since NR LDPC codes puncture the first two block columns of the parity-check matrix, the decoding complexity is reduced, but it slows down the convergence rate. In this letter, we propose a fixed schedule that decodes the layers with the least-punctured edges and those with the highest-degree (LPHD), which has much faster convergence speed than conventional schemes. The fixed scheduling schemes cannot take full advantage of the dynamic changes of decoding messages. As a result, the residual-based layered belief propagation (RB-LBP) is proposed to rearrange the layers dynamically among different iterations. Compared with some informed dynamic scheduling (IDS) strategies, RB-LBP reduces the decoding complexity with slight performance loss.
In this study, we analyze the characteristics of scheduling sequences for layered belief propagation (LBP) that can result in efficient decoding of low-density parity-check (LDPC) codes. Specifically, we claim that scheduling sequences leading to high decoding efficiency should prioritize updating check nodes with lower error probabilities aggregated from neighboring variable nodes. We prove this conclusion separately on both the BEC and the BI-AWGN channels. Some observable characteristics in “good” scheduling sequences regarding row weights, rows connected to punctured columns, and column weights can serve as corollaries to this conclusion. By comprehensively considering these characteristics of good scheduling, we design a multi-sequence nested scheduling scheme of layered decoding for 5G New Radio (NR) LDPC codes. The proposed schemes can obtain scheduling sequences for various rates of rate-compatible LDPC codes using small hardware storage. What’s more, by respectively storing double-sequence, triple-sequence, or more sequences to obtain scheduling sequences at various code rates, a trade-off can be made between decoder storage and decoding performance. Experimental results demonstrate that the proposed scheme achieves performance improvements compared to existing scheduling schemes at nearly all code rates.
In this letter, an improved scheduling scheme is proposed for the layered decoding of 5 G LDPC codes. Specifically, two novel techniques are introduced. Firstly, the delayed update of core matrix (DUCM) is proposed which can be incorporated with any layered-based scheduling schemes to improve error-correction performance. Secondly, a semi-dynamic scheduling scheme (SDSS) is developed which can outperform existing static ones at the cost of negligible complexity. Finally, extensive simulations are performed. The results show that, by combining above two techniques, the derived SDSS-DUCM scheme can significantly improve the error-correction performance and reduce the average number of iterations (ANI), compared with the state-of-the-art scheduling scheme.
5G new radio low density parity check (5G-NR LDPC) codes specified by the 3rd generation partnership project (3GPP), a representative class of multi-edge-type, quasi-cyclic and raptor-like LDPC codes with rate-compatible and length-scalable capability, could meet with high-throughput demands. The corresponding decoding algorithm and implementation should support low complexity, high performance and scaleinvariance to channel variations and receiver imperfections. Flooding scheduling is usually used for the prevalent decoding algorithms and architecture of LDPC codes, but it is inefficient and inflexible compared with layered scheduling. This paper proposes a new simplification method where the sub-groups with similar fitting functions of normalization factors are incorporated into the same type, and enhanced adaptive normalized min-sum algorithm (enhanced ANMSA) for layered scheduling is further proposed for the implementation of 5G-NR LDPC codes. Based on the new simplification method, the proposed algorithm defines three types of check nodes for base graph 2 (BG2) in 5G-NR LDPC codes, and then obtains three look-up tables for BG2 by training. Simulation results demonstrate that the proposed algorithm can achieve excellent performance for 5G-NR LDPC codes of different rates and lengths over Binary-input AWGN channel and Rayleigh channel.
Abstract In order to cater to the needs of the 5G standard, one of the prominent solutions in terms of high coding gain, high throughput and low power dissipation is the 5G NR LDPC (New Radio Low Density Parity Check) codes which have been adopted by 5G Standard. LDPC codes are the successful Third Generation Forward Error Correcting codes. An Efficient decoder is the key to the success of any Error Correcting Code. LDPC codes are one whose parity check matrix have a very few non zero entries. 5G NR LDPC codes are constructed by Protographs or base graphs and are block structured. This paper improves the performance of Layered Iterative minsum Approximation Message Passing decoding Algorithm using Rate Matching, Fixed Point Quantization and Offset minsum techniques. Rate Matching is to maintain the exact number of encoded blocks with in the TTI. Simulation of this algorithm with BPSK encoding over AWGN channel shows that BER of 10-3 gives Eb/No of~2 dB for the block length of 105.