Performance Analysis of Physical-Layer Network Coding for IIoT Applications

Physical-layer network coding (PNC) was introduced into wireless communication systems to improve system performance metrics such as error rates. The Industrial Internet of Things (IIoT) utilized the PNC concept to communicate robots together and computer applications with high data rates, low latency, and full diversity. A two-way relay network (TWRN) is a basic implementation of PNC in research. This paper provides a performance analysis of TWRN-PNC for IIOT applications over a Rayleigh fading channel employing high-order modulation. The theoretical framework of the proposed model is derived in closed form for the uplink and downlink phases. Additionally, the maximum likelihood (ML) and Latin square (LS) methods are considered for the mapping of superimposed signals to achieve the denoising-and-forward (DNF) relaying protocol in PNC. Theoretical and simulation results of average symbol error rate probability are demonstrated for both multiple access and end-to-end error, using square-quadrature amplitude modulation (QAM), 4-QAM, and 16-QAM modulation schemes, respectively, and simulated uplink throughput at the relay. The positive results are obtained in both simulation and exact results of high-order modulation using Monte Carlo simulation and reported the effectiveness of the approach across varying modulation levels. Throughput is approximately double that of traditional network links.