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Global Congress on Emerging Technologies (GCET)

On The Minsum Decoding Algorithm For The 5G NR LDPC Codes

Asma Alqudah

Published Dec 9, 2024• 0 citations
Publisher

Abstract

The paper presents a detailed analysis of the minsum decoding algorithm as applied to low-density parity-check (LDPC) codes used in 5G new radio (NR) systems. With the increasing demand for higher data rates and improved reliability in next-generation wireless communications, LDPC codes have emerged as a pivotal component in 5G NR's coding strategy. The minsum algorithm, known for its simplicity and efficiency in message passing, is evaluated in the context of its performance and practical implementation for these codes. Minsum decoding reduces complexity by approximating the soft-decision values using the minimum of the incoming messages, rather than applying the more computationally expensive operations such as hyperbolic tangent functions. In the context of 5G NR, this approximation makes minsum decoding particularly attractive for hardware implementation, providing a good trade-off between error-correction performance and computational efficiency. The algorithm iteratively updates messages passed along the edges of the Tanner graph, leveraging the sparsity of LDPC codes. This abstract reviews the relevance of minsum decoding to 5G NR LDPC codes, emphasizing its role in balancing performance with low computational requirements, critical in mobile and high-throughput applications.

DOI
10.1109/gcet64327.2024.10934509

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The paper presents a detailed analysis of the minsum decoding algorithm as applied to low-density parity-check (LDPC) codes used in 5G new radio (NR) systems. With the increasing demand for higher data rates and improved reliability in next-generation wireless communications, LDPC codes have emerged as a pivotal component in 5G NR's coding strategy. The minsum algorithm, known for its simplicity and efficiency in message passing, is evaluated in the context of its performance and practical implementation for these codes. Minsum decoding reduces complexity by approximating the soft-decision values using the minimum of the incoming messages, rather than applying the more computationally expensive operations such as hyperbolic tangent functions. In the context of 5G NR, this approximation makes minsum decoding particularly attractive for hardware implementation, providing a good trade-off between error-correction performance and computational efficiency. The algorithm iteratively updates messages passed along the edges of the Tanner graph, leveraging the sparsity of LDPC codes. This abstract reviews the relevance of minsum decoding to 5G NR LDPC codes, emphasizing its role in balancing performance with low computational requirements, critical in mobile and high-throughput applications.
Day by day the internet traffic is increasing rapidly. Challenges to improve these internet traffic requirements leads to evolution of 5G NR LDPC (New Radio Low Density Parity Check) codes which provides high coding gain and energy efficiency. BER Vs Eb/No dB curve defines the energy efficiency and coding gain of the any error correcting codes. LDPC codes which are adopted by 5G Standard are called 5G NR LDPC codes.In the design of the decoder,Message Passing Approach reduces the decoding complexity due to the sparsity of the parity check matrix. An efficient decoding algorithm is the key to the successful code. In this paper an iterative minsum approximation message passing decoding algorithm has been implemented for both BG1 and BG2. Results show that the coding gain can be improved up to 9dB.
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.
5G technology new radios (5G NR) require high-speed decoders that operate on highly irregular low-density parity-check (LDPC) codes.LDPC decoders have gained significant attention due to their excellent error correction performance.This study evaluates on different algorithms and scheduling techniques used for LDPC decoders.The analysis highlights that Min-Sum-based approaches can reduce the computational complexity compared to the basic sum-product algorithm, while the normalized and extended Min-Sum algorithms provide a better trade-off owing to their accurate value assumptions.Furthermore, different scheduling methods are implied for MS to improve speed and reduce latency.This study provides a comparative analysis of the algorithms and architectures that yield high throughputs without compromising performance efficiency.The LNMS algorithm with a data-level rescheduling technique resolves data dependency issues.This resolves the complexity of CN and VN and improves the throughput, making it suitable for 5G NR applications.The decoded throughput achieved with this scheduling is 7.0 Gbps.This throughput is achieved by maintaining the standard parameters and worst case parameters, such as four/eight iterations, BG1, and a code rate of 0.8/0.5.The evaluated architectures are implemented on Field Programmable Gate Array (FPGA) devices.This study aids in selecting the optimal architecture and scheduling techniques for LDPC decoders by considering various performance standards to deploy wireless networks in 5G and beyond.
The development of the Fifth Generation (5G) New Radio (NR) provides several significant advantages when compared to the fourth generation (4G) Long Term Evolution (LTE) in mobile communications. Due to the outstanding characteristics of Low-Density Parity-Check (LDPC) codes such as high decoding performance, high throughput, low complexity, they have been accepted as the standard codes for the 5G NR. In this paper, we propose two LDPC decoding algorithms: Hybrid Offset Min-Sum (HOMS) and Variable Offset Min-Sum (VOMS), which are aimed at improving the error correction performance. The main idea of the HOMS/VOMS algorithm is to apply modified factors to both variable-nodes and check-nodes updated processing in order to compensate the extrinsic messages overestimation of the MS-based algorithms and increase the protection ability for degree-1 variable-nodes. The simulation results show that at the Bit-Error-Rate (BER) of 10-5, the proposed HOMS/VOMS algorithm achieves the decoding gain up to 0.2 dB compared to the Offset Min-Sum (OMS) algorithm, with a slight increase in decoding complexity.
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.
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.