DESIGN OF LDPC DECODER BY SPLIT ROW,MIN SUM AND MIN PRODUCT USING MATLAB
In modern communication systems, the purpose is to transmit the encoded information bits to the receiver correctly by a medium without introducing noise to the data. The Low-density parity-check (LDPC) codes are first introduced in 1962 by Gallager at MIT during Ph.D. which has received significant attention due to close error performance to Shannons Limit. LDPC decoder can be designed using three types of architectures. Serial architecture requires less hardware but deliver low decoding throughputs. In Semi-parallel architecture, row and column operations are performed partially in parallel and deliver higher throughput as compared to serial architecture. In fully parallel architecture, corresponding to the parity check matrix in the Tanner graph, the row processor is direct. LDPC codes can be iteratively decoded in different ways and that decoding depends on the complexity and error performance requirements. The design uses three methods of LDPC decoding methods i.e Split Row, Min-Sum, and Min Product. These algorithms are widely used in LDPC decoders and are known as standard decoders. The Min-Sum algorithm performs row and column operations iteratively using two types of messages: check node message α and variable node message β. The design shows the comparison result of Split Row, Min-Sum, and Min Product using Matlab simulation.
Reference Paper-1: Split-Row: A Reduced Complexity, High Throughput LDPC Decoder Architecture
Author’s Name: T. Mohsenin and B. M. Baas
Source: IEEE
Year: 2006
Reference Paper-2: Design of Low-Density Parity-Check Decoder Using Min-Sum Algorithm
Author’s Name: Rishabh Jain, David L. Lubkeman, and Srdjan M. Lukic
Source: IEEE
Year: 2018
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SIMULATION VIDEO DEMO
