Low Density Parity Check (LDPC) codes have been widely used as error correction codes for many application on communication discipline. It has been proved that they can approach Shannon's capacity limit and implementable. On the other hand, the architecture of LDPC decoders should be designed carefully in order to obtain a convincing trade-off between logic complexity and error correction performance. In this paper, we proposed an optimized Block Processing Unit (BPU) to perform all the operations of check nodes and variable nodes of a QC-LDPC/LDPC decoder. The optimized BPU can reduce the logic complexity significantly compared to the original one. While the same quantization bit-width and calculation are employed, it can maintain a similar throughput and error correction performance. The experimental results show that it can provide a better trade-off between the logic complexity and the error correction performance than the original one.
Low Density Parity Check (LDPC) codes have been widely used as error correction codes for many application on communication discipline. It has been proved that they can approach Shannon's capacity limit and implementable. On the other hand, the architecture of LDPC decoders should be designed carefully in order to obtain a convincing trade-off between logic complexity and error correction performance. In this paper, we proposed an optimized Block Processing Unit (BPU) to perform all the operations of check nodes and variable nodes of a QC-LDPC/LDPC decoder. The optimized BPU can reduce the logic complexity significantly compared to the original one. While the same quantization bit-width and calculation are employed, it can maintain a similar throughput and error correction performance. The experimental results show that it can provide a better trade-off between the logic complexity and the error correction performance than the original one.
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.
The performance of a high-throughput long-distance communication system such as an optical transmission system is limited by the Net Coding Gain (NCG) of the Forward Error Correction (FEC) system. Summarizing the previous research works, Low-Density Parity-Check (LDPC) codes form one of the most promising FEC schemes to be applied in high-throughput communication systems. Designing a practical channel coding scheme with high code rate, low complexity, high throughput and extremely low error floor has always been a very challenging problem. Quasi-cyclic low-density parity-check (QC-LDPC) codes have been promising candidates to fulfill the above requirements but the implementation issues remain. In this paper, we propose a layered QC-LDPC decoder architecture with high code rate, low complexity, high throughput and excellent error performance. The architecture has been implemented using FPGA and the error performance has been shown to be good.
One of the most important units of Low-Density Parity-Check (LDPC) decoders is the Check-Node Unit.Its main task is to find the first two minimum values among incoming variable-to-check messages and return check-tovariable messages.This block significantly affects the decoding performance, as well as the hardware implementation complexity.In this paper, we first propose a modification to the check-node update rule by introducing two optimal offset factors applied to the check-to-variable messages.Then, we present the Check-Node Unit hardware architecture which performs the proposed algorithm.The main objective of this work aims to improve further the decoding performance for 5 th Generation (5G) LDPC codes.The simulation results show that the proposed algorithm achieves essential improvements in terms of error correction performance.More precisely, the error-floor does not appear within Bit-Error-Rate (BER) of 10 -8 , while the decoding gain increases up to 0.21 dB compared to the baseline Normalized Min-Sum, as well as several state-ofthe-art LDPC-based Min-Sum decoders.
Low-density parity-check (LDPC) codes are adopted in many applications due to their Shannon-limit approaching error-correcting performance. Nevertheless, belief-propagation (BP) based decoding of these codes suffers from the error-floor problem, i.e., an abrupt change in the slope of the error-rate curve that occurs at very low error rates. Recently, a new type of decoders termed finite alphabet iterative decoders (FAIDs) were introduced. The FAIDs use simple Boolean maps for variable node processing, and can surpass the BP-based decoders in the error floor region with very short word length. We restrict the scope of this paper to regular dv=3 LDPC codes on the BSC channel. This paper develops a low-complexity implementation architecture for the FAIDs by making use of their properties. Particularly, an innovative bit-serial check node unit is designed for the FAIDs, and a small-area variable node unit is proposed by exploiting the symmetry in the Boolean maps. Moreover, an optimized data scheduling scheme is proposed to increase the hardware utilization efficiency. From synthesis results, the proposed FAID implementation needs only 52% area to reach the same throughput as one of the most efficient standard Min-Sum decoders for an example (7807, 7177) LDPC code, while achieving better error-correcting performance in the error-floor region. Compared to an offset Min-Sum decoder with longer word length, the proposed design can achieve higher throughput with 45% area, and still leads to possible performance improvement in the error-floor region.
Low-density parity-check (LDPC) codes are adopted in many applications due to their Shannon-limit approaching error-correcting performance. Nevertheless, belief-propagation (BP) based decoding of these codes suffers from the error-floor problem. Recently, a new type of decoders termed finite alphabet iterative decoders (FAIDs) were introduced. The FAIDs use simple Boolean maps for variable node processing. With very short word length, they can surpass the BP-based decoders in the error floor region. This paper develops a low-complexity implementation architecture for FAIDs by making use of their properties. Particularly, an innovative bit-serial check node unit is designed for FAIDs, and the symmetric Boolean maps for variable node processing lead to small silicon area. An optimized data scheduling scheme is also proposed to increase the hardware utilization efficiency. From synthesis results, the proposed FAID implementation needs only 52% area to reach the same throughput as one of the most efficient Min-sum decoders for an example (7807, 7177) LDPC code, while achieving better error-correcting performance in the error-floor region.
Low-Density Parity-Check (LDPC) codes have traditionally performed better at longer code lengths. This research develops and rigorously evaluates a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder architecture intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G and subsequent technologies. The paper investigates LDPC codes in short-length contexts through architectural optimization based on a layered decoding approach, which provides improved convergence speed and reduced latency compared with traditional flooding techniques. The short block-length QC-LDPC code (280,176) addresses the dual challenge of achieving ultra-low latency while maintaining high performance relative to existing work. For a target BLER of 10−2, the decoder outperforms the shorter reference codes (60,40) and (96,64), with an Eb/N0 gain of up to 0.9 dB, part of which is attributable to the longer block length rather than to the decoder alone. The FPGA implementation results demonstrate that the design is hardware-efficient: it operates at a maximum frequency of 218.62 MHz, resulting in a throughput of 155.77 Mbps, while maintaining a decoding latency of only 1.129 µs and a power consumption of 0.201 W.