An Adaptive Exponential Min Sum Decoding Algorithm
Weijia Zhang, Dushantha Nalin K. Jayakody · 2023
The belief propagation (BP) algorithm for low density parity check (LDPC) codes has proven to have excellent performance and is close to the Shannon limit. However, the high computational complexity is not conducive to realistic use. Although the min sum algorithm (MSA) improves the computational convenience and applicability. It also weakens its decoding capability. In order to improve the decoding performance of MSA and exploit the potential, this paper propose an adaptive exponential correction factor. This can improve the decoding performance of MSA. Adaptive exponential min sum algorithm (AEMSA) demonstrate a noticeable improvement over the normalized min sum algorithm (NMSA) and the BP algorithm in high signal to noise ratio (SNR). AEMSA is also a simple, efficient, low power consuming and highly potential decoding algorithm that can be applied in hardware implementations.