Fast Simulation of Channel-Coded MIMO-OFDM Transmission in Multipath Fading at Low Error Rates

The low-error-rate requirement of ultra-reliable communication poses a significant challenge to simulation-based performance evaluation of such systems, as conventional Monte Carlo (MC) simulation becomes extremely time-consuming at very low error rates. This work considers fast simulation of multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) transmission over multipath fading channels via importance sampling (IS). The efficiency of an IS simulator hinges on several key factors: 1) how sharply it can differentiate error-causing and non-error-causing subsets in the sample space, 2) how readily it can profile the probability distribution regarding these subsets, and 3) how proficiently it can generate and distribute samples over particular subsets of interest. In this perspective, we develop a novel IS method in the vein known as histogram-shaping Monte Carlo (HSMC). First, an error gauging function that is generally applicable to channel-coded MIMO-OFDM systems is proposed to highlight potentially error-causing samples in multipath fading channels. Second, we develop a sampler that not only generates random samples effectively from error-causing subsets but also facilitates fast estimation of subset-associated probabilities. New Radio (NR) link-level simulation is conducted to showcase the advantages of the proposed method, revealing approximately 10- to $10^{7}$ -fold speedup compared to conventional MC simulation.