Configured Grant for Semi-Deterministic Traffic for Ultra-Reliable and Low Latency Communications

TL;DR

This paper investigates enhancing Configured Grant-based scheduling in 5G NR to improve reliability and latency for semi-deterministic traffic, proposing various allocation design improvements for ultra-reliable low latency communications.

Contribution

It introduces novel allocation strategies and enhancements to the Configured Grant mechanism to better support semi-deterministic traffic in ultra-reliable low latency scenarios.

Findings

Improved reliability with additional unlicensed spectrum.

Flexible transmission timing enhances performance.

Allowing time-gaps between repetitions benefits reliability.

Abstract

Configured Grant-based allocation has been adopted in New Radio 3rd Generation Partnership Project Release 16. This scheme is beneficial in supporting Ultra-Reliable and Low Latency Communication for industrial communication, a key Fifth Generation mobile communication usage scenario. This scheduling mechanism enables a user with a periodic traffic to transmit its data readily and bypasses the signaling entailed to scheduling requests and scheduling grants; and provides low latency access. To facilitate ultra-reliable communication, the scheduling mechanism can allow the user to transmit redundant transmissions at consecutive repetition occasions in a pre-defined period. However, for the user with semi-deterministic traffic, the reliability and latency performance with Configured Grant-based allocation deteriorates. This can be due to, e.g., late data arrival in the buffer, and the user unable to transmit its repetitions, which leads to reliability degradation. To improve the Configured Grant reliability performance with semi-deterministic traffic, we consider various allocation designs utilizing, e.g., additional unlicensed spectrum, or flexible transmission in a Configured Grant period, or allowing time-gaps between the repetitions, etc. These enhancements could be a stepping-stone for Sixth Generation Configured Grant models.