Due to the stringent requirements of ultra-reliability and low latency, Ultra-Reliable Low-Latency Communication (URLLC) is facing great challenges in data packets transmission, especially for uplink transmission. As a key technology, uplink grant free (GF) has been proposed to simplify the uplink transmission procedures for reducing data transmission latency. However, in practical network, predicting the exact packet arrival time of User Equipment (UE) is a very difficult work for base station (BS), without knowing the exact time when the UE generates the messages, GF resource allocation becomes challenging for guaranteeing network resource utilization and UE capacity while ensuring the performance of URLLC. In this paper, a Collision Probability based Multi-User (CPMU) grant free resource allocation method is proposed to select appropriate sending time occasion set and frequency multiplexed scheduling user set for multi-user multi-input multi-output (MU-MIMO) network. Instead of assuming exact packets generation time of UEs by BS, CPMU method adds a fluctuation time for predicted packets generation time and derives the collision probability among multiplexed scheduling users, then the lowest collision probability scheduling UE set is selected. Furtherly, higher resource utilization and UE capacity are obtained. Simulation results demonstrate that, compared with conventional GF resource allocation methods, the presented method improves the system resource utilization from 10% to up to 341%, and increases UE capacity from 25% to up to 400%, while the performance of URLLC is guaranteed.


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    Titel :

    A Collision Probability Based Multi-User Grant-Free Scheduling Method for Ultra-Reliable and Low Latency Communications


    Beteiligte:
    Song, Xi (Autor:in) / Yin, Zhining (Autor:in) / Li, Yan (Autor:in) / Li, Xiaoyu (Autor:in) / Wang, Jiajia (Autor:in) / Jing, Meifang (Autor:in)


    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    3149094 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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