摘要(英) |
In recent years, the international organization 3GPP has continued to customize the standard specifications of the fifth generation mobile communication (5G). 5G can be divided into three major application scenarios, namely Enhanced Mobile Broadband (eMBB), Ultra-reliable and Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC). URLLC can be used in industrial automation production, unmanned driving, etc. in the future. The purposes of URLLC is high reliability and low latency. However, such strict requirements will bring great challenges to existing network communication systems, so this paper will focus on the resource allocation of URLLC.
For the burst URLLC traffic to be uplinked, the Uplink Grant-free method can effectively reduce the request delay between the UE and the BS. BS may allocate the dedicated resource or shared resource pool to URLLC UE for uplink. No matter which resource is used, there are strength and weaknesses. Therefore, this paper will group UEs according to the traffic characteristics. Under limited bandwidth, it will make the most effective resource allocation, and use reinforcement learning to determine the size of the shared resource pool. From the simulation results, it shows that the resources can be effectively saved in various situations, and achieve the goals of high reliability and low latency at the same time, especially in high load case. |
參考文獻 |
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