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International Conference on Electronic Information Technology (EIT)

Efficient iterative decoding algorithm of RS-LDPC concatenated schemes with 5G-LDPC codes

Kailin Liu, Ming Jiang, Lijie Hu

Published Aug 15, 2023• 0 citations
Publisher

Abstract

Despite the performance of 5th Generation Low Density Parity Check (5G-LDPC) codes close to the capacity limit, the near-optimal floating-point BP decoding will lead to excessive use of hardware and high complexity of calculation. Thus, the quantized min-sum decoder with limited-precision is usually used in practical implementations. No matter using high or low precision quantization, some 5G-LDPC codes always suffer from the problem of high error floor, which affects their applications in future ultra-reliable scenarios. Using Reed-Solomon (RS) codes as the outer codes can significantly lower the error floor of 5G-LDPC codes due to their Hamming distance properties and excellent error-correction capability. In order to further improve the overall performance, an efficient iterative decoding algorithm of RS-LDPC concatenated codes is proposed in this paper. The proposed iterative algorithm of RS-LDPC codes can achieve noticeable gains over the 5G-LDPC codes at lower FER.

DOI
10.1117/12.2685769

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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.
Very high data rates and decoding computational complexity place strict constraints in 5G and 6G communications. In this paper, non-uniform Quantized Decoding algorithm is proposed for Low-density Parity Check codes (LDPC). In the proposed algorithm, the check node updating process is carried out using quantization, which reduces complexity. The Sum Product Algorithm (SPA) is iterative message passing decoding techniques offer the optimal performance for LDPC codes. Implementations use message-passing decoding with more precision, results extremely high complexity. In Iterative, message-passing (MP), trapping sets and absorbing sets causes low error floor. In this article non-uniform quantization proposed to overcome dynamic range of values over uniform quantization. Simulation results provide coding gain increases closer to of 0.5 dB in higher SNR and has good error floor at 10−5.
Low Density Parity Check(LDPC) Codes is a class of approaching limits error correction codes which has gained widely application in communications. The excellent performance, however, is the result of a large number of repeatedly conducting iterative decoding algorithm, and is apt to be seriously affected by small girth in the parity check matrix. In this paper we present a novel serial concatenated scheme for LDPC codes which utilize much smaller generation matrix and the interleaver to reduce possibilities of girth, thus reducing the number of iterations in decoding. Simulation shows that the new codes have better performance while less requirement of iterations.
This paper presents an adaptation of the Min-Sum decoders for the Low-Density Parity-Check (LDPC) used in the enhanced mobile broadband (eMBB) scenario in the 5th generation mobile networks (5G). Starting from the structure of the proposed LDPC codes for 5G where a significant part of the Variable Nodes (VNs) is with degree-1 and is sensitively to be erroneous in the traditional Offset Min-Sum decoder, we adapt the Min-Sum decoding principle to decode these 5G LDPC codes, targeting to improve the error correction performance. The proposed decoder, named Adapted Min-Sum (AMS), processes the core and the extension parts of the code differently using different offset factors. By doing that, the error probability of degree-1 VN is significantly depressed. We show through the simulation performance that the proposed decoder, with small number of quantization bits, can even surpass the floating-point counterpart and approaches the performance of the Sum-Product decoder for several 5G LDPC code lengths and code rates, with negligible additional complexity.
Since the degree-1 variable nodes (VNs) in the low-density parity-check (LDPC) codes for the 5th generation (5G) mobile communications are very sensitive to be erroneous, the quantized min-sum (QMS) and offset min-sum (QOMS) decodings suffer from poor error-correction performance due to the imprecise estimation of the check-to-variable (C2V) message magnitudes. For this reason, this paper proposes a decomposition mapping based quantized belief propagation (DM-QBP) decoding for 5G LDPC codes. In order to reduce the computation complexity, the check node (CN) update function is realized by look-up tables (LUTs). Furthermore, a decomposition method is presented to eliminate the high memory cost of using large tables without performance loss. Therefore, the CN update function can be implemented based only on simple mappings and fixed-point additions. Simulation results show that, the DM-QBP decoder considerably outperforms the state-of-the-art ones for several 5G LDPC codes. With a small number of quantization bits, its performance is even better than the floating-point OMS decoding in some cases.