Title
Feedback Prediction for Proactive HARQ in the Context of Industrial Internet of Things
Abstract
In this work, we investigate proactive Hybrid Automatic Repeat reQuest (HARQ) using link-level simulations for multiple packet sizes, modulation orders, BLock Error Rate (BLER) targets and two delay budgets of 1 ms and 2 ms, in the context of Industrial Internet of Things (IIOT) applications. In particular, we propose an enhanced proactive HARQ protocol using a feedback prediction mechanism. We show that the enhanced protocol achieves a significant gain over the classical proactive HARQ in terms of energy efficiency for almost all evaluated BLER targets at least for sufficiently large feedback delays. Furthermore, we demonstrate that the proposed protocol clearly outperforms the classical proactive HARQ in all scenarios when taking a processing delay reduction due to the less complex prediction approach into account, achieving an energy efficiency gain in the range of 11% up to 15% for very stringent latency budgets of 1 ms at 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> BLER and from 4% up to 7.5% for less stringent latency budgets of 2 ms at 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> BLER. Furthermore, we show that power-constrained proactive HARQ with prediction even outperforms unconstrained reactive HARQ for sufficiently large feedback delays.
Year
DOI
Venue
2020
10.1109/GLOBECOM42002.2020.9322302
GLOBECOM 2020 - 2020 IEEE Global Communications Conference
Keywords
DocType
ISSN
5G mobile communication,Early HARQ,IIOT,Proactive HARQ,Feedback Prediction,Low latency communication,Physical layer,Machine learning,HARQ,Tactile Internet,Machine-type communication
Conference
1930-529X
ISBN
Citations 
PageRank 
978-1-7281-8299-5
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Baris Goktepe110.69
Tatiana Rykova200.34
Thomas Fehrenbach300.34
T. Schierl429427.68
C. Hellge532832.26