5G 망에서 정보의 적시성을 보장하기 위한 Grant 기반의 상향 링크 스케줄링 기법

초록

In massive machine-type communications (mMTC), one of the top three 5G scenarios, a single gNB needs to realize hyper-connectivity to support up to a maximum of device connections, while ensuring the QoS of the connected devices. In recent research, grant-free uplink processing techniques have been proposed to expedite these needs, but they are limited in mMTC environments with highly heterogeneous traffic environments. In addition, existing scheduling techniques evaluate network performance based on throughput and delay, which makes it difficult to guarantee the timeliness of data. To address these issues, this paper proposes a weighted sum metric and scheduling decision algorithm that combines AoI, a measure of information freshness, and WMA, a measure of data transmission success rate. AoI is calculated as the difference between the time when a data packet is generated and the time when the data packet is received by the gNB, while WMA counts the successful data transmission. We introduce the proposed scheduling decision technique in the ns-3 network simulator, and demonstrate that it can guarantee the freshness of information by showing similar throughput and delay figures compared to the existing scheduling techniques and reducing the system average AoI by up to 44.27%.

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