Data-Oriented View for Convolutional Coding With Adaptive Irregular Constellations

Abstract

Current wireless systems offer various use-cases where conventional channel capacity focused performance criteria might not apply. Following the similar perspective, convolutional encoding can find more room due to its low complexity and low decoding delay. Besides, it has been also shown that error performance of a convolutional encoder can be improved further by using adaptive irregular constellations. A new performance measure, data-oriented approach, was recently proposed for the transmission of small data packets, i.e. mission-critical IoT applications, over fading channels. In this paper, delay performance gain resulting from convolution coding optimized irregular constellations is investigated. Then, we derive a new performance criterion based on delay and finite block length constraints. Based on this criterion, we design irregular constellations together with convolutional coding for short packet transmission.

Data-Oriented Downlink RSMA Systems

“…The DOR metric for the short packet transmission over fading channels was presented in [10] and inspired by it, [11] represented how the DOR expression can be utilized for searching optimum constellation point over a coded scenario in [11]. The DOR metric has been recently utilized in the coverage analysis of reflective intelligent surfaces (RIS)-aided communication systems [12] and over visible light communication scenarios [13].…”