| dc.description.abstract | In the rapidly evolving world of technology, the internet has become an integral part of our lives. As the percentage of people using the internet continues to grow, the demand for network performance is also increasing. Currently, mobile communication has advanced to 5G, and in order to cater to different applications of the network in daily life, the ITU-R (ITU Radiocommunication Sector) has defined three major scenarios: URLLC (Ultra-Reliable Low-Latency Communication), eMBB (Enhanced Mobile Broadband), and mMTC (Massive Machine Type Communication). The performance requirements for three different scenarios vary, and the design considerations for resource utilization in base stations also differ. In many present-day environments, there may be a simultaneous need for multiple scenario usage, making the coexistence of multiple scenarios a significant challenge for system architecture design.
In a network environment, when users need to upload data to the network, they must first establish a connection with the base station. This connection process is known as random access. However, since base station resources are limited, a competitive method must be employed to establish connections for all users. Only those who successfully compete can begin uploading data. For URLLC, another upload method called Grant-free has been developed to assist its low-latency characteristics. This paper primarily explores the coexistence of URLLC and eMBB scenarios. When different random access methods are used for each scenario, it is crucial to ensure that both scenarios achieve the desired performance. However, different resource allocation methods have their pros and cons. Therefore, in addition to investigating dynamic adjustment methods for grouping, this paper also designs a decision-making method to switch between different grouping modes. This allows the base station to select the current mode based on factors such as the success rate or quantity of User Equipment (UE) in the current environment, aiming to improve the performance of URLLC.
This paper simulates and analyzes two grouping methods, three switching methods, and two parameter adjustment methods. Through this analysis, each method is examined to determine its suitable scenarios, advantages, disadvantages, and overall performance. The paper also aims to identify the most ideal switching method and provide further explanations on how to optimize the two parameter adjustment methods. | en_US |