Summary: | 碩士 === 國立中山大學 === 資訊工程學系研究所 === 107 === The existing network is mainly designed for the requirements of Human-to-Human (H2H), and the future network will connect a lot of mechanical equipment. Therefore, this thesis proposes a priority resource allocation algorithm that integrates the prediction methods and the priority scheduling for the uplink of the massive Machine Type Communication (MTC). It can reduce the delay of a UE to send a SR (Scheduling Request) to the eNodeB (Evolved Node B) to obtain the approved resource to transmit the data, which will cause a lot of delay in the process of transmitting the message. Due to there might have different transmission data deadlines for UE (User Equipment), the proposed algorithm uses the priority scheduling to improve transmission success rate and resource utilization rate. Experimental results show that the delay time can be effectively reduced in the case of sufficient resources, which is close to 38%, and the success rate is at least 60%
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