Trade-off Analysis of Reliability and Energy Efficiency in SPA and MSA LDPC Decoding Algorithms for Wireless Sensor Networks

Low-Density Parity-Check (LDPC) codes provide strong error-correction capability for wireless communication systems, but their iterative decoding process introduces computational and energy costs that are particularly important in energy-constrained Wireless Sensor Networks (WSNs). This study comparatively evaluates the Sum-Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) for LDPC decoding, with emphasis on the trade-off between communication reliability and estimated decoding energy. A simulation-based evaluation was implemented in MATLAB R2019b using BPSK modulation over an Additive White Gaussian Noise (AWGN) channel. Both decoders were evaluated under identical conditions over Eb/N0 values of 1–9 dB using Bit Error Rate (BER), average decoding iterations, and estimated Decoding Energy per Bit (DEB) as performance measures. SPA achieved a lower mean BER of 0.00528, compared with 0.00956 for MSA. Conversely, MSA required fewer average decoding iterations (8.6 versus 10.8) and consequently achieved a lower mean estimated DEB of 0.43 nJ/bit compared with 0.54 nJ/bit for SPA under the adopted common fixed energy-per-iteration model. The results demonstrate a clear reliability–energy trade-off: SPA provides higher decoding reliability, whereas MSA reduces iterative computational effort and estimated decoding energy. MSA therefore represents a practical alternative for energy-constrained WSN applications where a moderate reliability penalty can be tolerated.