Convolutionally Coded SNR-Adaptive Transmission for Low-Latency Communications

TL;DR

This paper introduces a SNR-adaptive convolutional coding scheme with optimized constellations to improve low-latency wireless communications, outperforming traditional methods in error rate and spectral efficiency.

Contribution

It proposes a novel non-iterative convolutional coding system with optimized constellations tailored for low-latency requirements, enhancing performance over existing adaptive systems.

Findings

Significant bit-error-rate improvements

Enhanced spectral efficiency

Outperforms traditional adaptive modulation systems

Abstract

Fifth generation new radio aims to facilitate new use cases in wireless communications. Some of these new use cases have highly de-manding latency requirements; many of the powerful forward error correction codes deployed in current systems, such as the turbo and low-density parity-check codes, do not perform well when the low-latency requirement does not allow iterative decoding. As such, there is a rejuvenated interest in noniterative/one-shot decoding algorithms. Motivated by this, we propose a signal-to-noise ratio-adaptive convolutionally coded system with optimized constellations designed specifically for a particular set of convolutional code parameters. Numerical results show that significant performance improvements in terms of bit-error-rate and spectral efficiency can be obtained compared to the traditional adaptive modulation and coding systems inlow-latency communications.