On the Frame Error Rate of Transmission Schemes on Quasi-Static Fading Channels

TL;DR

This paper introduces a threshold-based method to estimate frame error rates for various transmission schemes on quasi-static fading channels, extending existing approaches to non-iterative schemes and validating with simulations.

Contribution

It proposes a unified threshold-based framework for estimating frame error rates of both iterative and non-iterative schemes on quasi-static fading channels, including new performance evaluation plots.

Findings

Threshold accurately estimates frame error rates within 0.4 dB of simulations.

The approach applies to uncoded, convolutional, and turbo coding schemes.

Performance plots reveal the impact of frame size on scheme performance.

Abstract

It is known that the frame error rate of turbo codes on quasi-static fading channels can be accurately approximated using the convergence threshold of the corresponding iterative decoder. This paper considers quasi-static fading channels and demonstrates that non-iterative schemes can also be characterized by a similar threshold based on which their frame error rate can be readily estimated. In particular, we show that this threshold is a function of the probability of successful frame detection in additive white Gaussian noise, normalized by the squared instantaneous signal-to-noise ratio. We apply our approach to uncoded binary phase shift keying, convolutional coding and turbo coding and demonstrate that the approximated frame error rate is within 0.4 dB of the simulation results. Finally, we introduce performance evaluation plots to explore the impact of the frame size on the performance of the schemes under investigation.