Dec 15, 2023 · The main objective is to design a framework that leverages DDRL techniques to efficiently manage resources in next-generation V2X communication ...

This study introduces a dynamic duplex deep Q-learning-assisted sequential decision-making algorithm to manage band resources for the next-generation V2X ...

Dec 15, 2023 · Abstract. Resource management in the next-generation vehicle-to-everything (V2X) communication networks is a demanding research problem.

Jul 31, 2023 · The framework learns to make resource allocation decisions that maximize the reliability and throughput of V2X communications and duplex ...

A dynamic neural Q-learning-based resource allocation and resource sharing algorithm is proposed for D2D-based V2V communication in the LTE-A cellular ...

Sep 28, 2023 · The framework aims to optimize radio resource allocation and enhance communication efficiency for next-generation vehicular networks [14].

Hussain, A novel duplex deep reinforcement learning based RRM framework for next-generation V2X communication networks. Expert Syst. Appl. 233, 121004 (2023)

Reuse Distance-Aided Resource Selection Mechanisms for NR-V2X Sidelink Communication · 1. Introduction. Vehicle-to-everything (V2X) is an advanced technology ...

This uses the Q value-based deep transfer reinforcement learning to find the best ratio selection for two slice types using the throughput and latency measures.

A novel duplex deep reinforcement learning based RRM framework for next-generation V2X communication networks · Published: 31 Dec 2022, Last Modified: 31 Jan ...