Abstract
5G and Internet of Things (IoT) wireless systems face challenges to reliable data transmission due to multipath fading, intersymbol interference, and the need for low-complexity Forward Error Correction (FEC). Conventional FEC techniques, such as Low-Density Parity-Check (LDPC) and turbo codes, provide high reliability but are unsuitable for resource-constrained IoT devices due to high decoding complexity. The aim of this study is to evaluate Multi-Threshold Decoders (MTDs) applied to Self-Orthogonal Codes (SOCs) as a low-complexity FEC solution in Orthogonal Frequency-Division Multiplexing (OFDM) and Multiple Input Multiple Output (MIMO) systems with Space–Time Coding (STC). The systems are modeled under ITU-R (Outdoor A, TU6, RA6) and 3GPP Spatial Channel Model (Urban Macro/Micro) fading environments and compared with LDPC (WiMAX, DVB-S2) and turbo codes in terms of Bit Error Rate (BER), Signal-to-Noise Ratio (SNR), decoder complexity, antenna diversity, modulation order, and throughput. Results indicate that SOC+MTD outperform short LDPC and turbo codes under deep fading while achieving reliability comparable to long LDPC codes at significantly lower decoding complexity. Min-sum refinement and approximate Maximum-Likelihood (ML) detection provide up to 2 dB additional SNR gain, and 1×3 antenna diversity reduces required Eb/N₀ by ~7 dB at BER = 10⁻⁵. Higher-order modulations such as 8PSK and 16APSK achieve 1.5–2× higher bit rates with moderate SNR penalties, while Open Computing Language (OpenCL) based Graphics Processing Unit (GPU) acceleration enables a 32-fold increase in simulation speed. These findings demonstrate that SOCs decoded with MTD represent a promising low-complexity, high-reliability FEC approach for 5G and IoT physical layers.