Microsimulation of Space Time Trellis Code

TL;DR

This paper explores using microsimulation combined with machine learning to efficiently compare generator matrices in space-time trellis code design, significantly reducing computational costs while maintaining high accuracy.

Contribution

It introduces a microsimulation approach enhanced by multilayer perceptron to speed up code validation in space-time trellis coding.

Findings

Achieves 93.86% accuracy in code comparison

Reduces simulation time by 98.25%

Validates effectiveness of machine learning in microsimulation

Abstract

Currently, the potential of microsimulation in space time trellis code has not been thoroughly ascertained. Therefore, this letter explores the possibility of using microsimulation in performing a pairwise comparison between competing generator matrices in code design. The validation of code construction is often done with simulation, which can be inherently time consuming. Microsimulation considerably cuts down the computational cost of simulation by employing smaller data and iteration. The effort is made feasible with the assistance of a machine learning model known as multilayer perceptron. When properly conducted, it can offer 93.86% accuracy and 98.25% reduction in temporal cost.