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.
翻译:超可靠低寿命通信系统(URLLC)是5G细胞系统的新特点。为了满足对上链路数据传输的严格的 URLLC 要求,5G 系统的具体规格引入了无赠款通道访问方法。根据这种方法,用户设备(UE)在不要求基地站(GNB)提供频道资源的情况下进行包传输。通过无赠款通道访问,GNB以长期时间尺度配置上链路传输参数。由于频道质量在时间和频率方面可以发生重大变化,GNB应选择稳健的传输参数,以满足URLLC的要求。许多现有研究认为,固定稳健的上链路传输参数选择可以满足即使是对频道条件差的UE的要求。然而,选择更稳健的传输参数是网络能力。在本文中,我们建议根据GNB的信号到神经比率统计分析,根据频道质量选择传输参数。通过NS-3的模拟结果显示,算法可以满足URLLL Lantency和可靠性要求,同时比固定传输参数减少频道资源消耗两次。