Link adaptation is fundamental in managing spectrum resources efficiently and is proven to be fundamental in the overall system operation and performance boost. The aim of this paper is to propose and characterize a novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunication standards. Tests were conducted in a laboratory-level 5G system where, by means of a channel emulator, downlink performance for a hotspot-like scenario is evaluated. We show how the proposed PID link adaptation algorithm reacts to the downlink channel variations, and hence ensures convergence to the target BLER and boosts the system throughput, in comparison with traditional MCS selection and reference adaptation algorithms.
Andrea Nicolini, Davide Dardari, Vincenzo Icolari, Massimo Notargiacomo (2023). Link Adaptation Algorithm for Optimal Modulation and Coding Selection in 5G and Beyond Systems. IEEE [10.1109/ICC45041.2023.10279293].
Link Adaptation Algorithm for Optimal Modulation and Coding Selection in 5G and Beyond Systems
Andrea Nicolini;Davide Dardari;Vincenzo Icolari;
2023
Abstract
Link adaptation is fundamental in managing spectrum resources efficiently and is proven to be fundamental in the overall system operation and performance boost. The aim of this paper is to propose and characterize a novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunication standards. Tests were conducted in a laboratory-level 5G system where, by means of a channel emulator, downlink performance for a hotspot-like scenario is evaluated. We show how the proposed PID link adaptation algorithm reacts to the downlink channel variations, and hence ensures convergence to the target BLER and boosts the system throughput, in comparison with traditional MCS selection and reference adaptation algorithms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
