Adaptive Transmission Parameters Selection Algorithm for URLLC Traffic in Uplink

TL;DR

This paper proposes an adaptive algorithm for uplink transmission parameter selection in 5G URLLC, optimizing reliability and latency while significantly reducing resource consumption compared to fixed methods.

Contribution

The paper introduces a novel adaptive algorithm that dynamically adjusts transmission parameters based on channel quality, improving efficiency and meeting URLLC requirements.

Findings

The algorithm meets URLLC latency and reliability standards.

It reduces channel resource consumption by over 50%.

Simulation results validate the effectiveness of the adaptive approach.

Abstract

Ultra-Reliable Low-Latency Communications (URLLC) is a novel feature of 5G cellular systems. To satisfy strict URLLC requirements for uplink data transmission, the specifications of 5G systems introduce the grant-free channel access method. According to this method, a User Equipment (UE) performs packet transmission without requesting channel resources from a base station (gNB). With the grant-free channel access, the gNB configures the uplink transmission parameters in a long-term time scale. Since the channel quality can significantly change in time and frequency domains, the gNB should select robust transmission parameters to satisfy the URLLC requirements. Many existing studies consider fixed robust uplink transmission parameter selection that allows satisfying the requirements even for UEs with poor channel conditions. However, the more robust transmission parameters are selected, the lower is the network capacity. In this paper, we propose an adaptive algorithm that selects the transmission parameters depending on the channel quality based on the signal-to-noise ratio statistics analysis at the gNB. Simulation results obtained with NS-3 show that the algorithm allows meeting the URLLC latency and reliability requirements while reducing the channel resource consumption more than twice in comparison with the fixed transmission parameters selection.