Ubiquitous connectivity is essential for emerging edge-assisted machine-type communication (MTC) applications for net-worked robotics, intelligent transportation, smart surveillance, etc., which demand ultra-low latency, high data rate, reliability, and energy efficiency. These applications generate significant uplink traffic, often consisting of raw sensor data, where the utility of data is closely tied to its timeliness. The traffic patterns in these scenarios are event-driven, characterized by high variability and bursts, making them difficult to predict. While 5G networks provide Radio Resource Control (RRC) states-Idle, Inactive, and Connected-designed to manage latency and user equipment (UE) power consumption based on deterministic traffic patterns like video streaming, they may not be optimized for the unpredictable nature of MTC traffic. In this study, we evaluate the performance of legacy 5G systems in handling MTC traffic using the open-source 3GPP-compliant testbed, Open Air Interface (OAI). Our analysis reveals that current 5G UE connection setup mechanisms can adversely affect control latency and UE power consumption due to the irregular and event-driven nature of MTC traffic. To mitigate these issues, we propose an enhanced connection setup process that allows UEs to remain in idle mode during inactivity, thereby conserving power, and facilitating a rapid transition to connected mode with reduced signaling overhead and power consumption. We implement and validate this framework on the OAI testbed, demonstrating its compatibility with the 3GPP standard. Empirical results indicate that our proposed method can reduce UE control latency and power consumption by up to 4× and 3× respectively, compared to legacy 5G connection setup approaches.
Reducing 5G-NR Control Overhead for Swift UE Connection Setup with Low Power Consumption
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