System-level evaluation of 5G standalone communication infrastructure for robotic telesurgery
摘要
Telesurgery, which enables remote surgical procedures via robotic systems and network communication, has emerged as a promising approach to reducing disparities in surgical access. Successful real-time telesurgery requires ultra-low latency, minimal jitter, and stable video transmission. While earlier implementations relied on dedicated communication lines, the advent of fifth-generation (5G) mobile networks offers new opportunities for scalable, infrastructure-independent telesurgical communication.
MethodsA feasibility study was conducted using the hinotori™ Surgical Robot System. The communication route was extended via a docomo Multi-access Edge Computing (MEC) server located 400 km away to simulate an 800-km round trip. Five network configurations were tested: 4G LTE, 5G Non-Standalone (NSA), and 5G Standalone (SA) in both Sub6 and NR-DC modes. System performance was evaluated based on round-trip latency, video continuity, buffer stability, and uplink throughput. Additionally, a stress test was performed under 5G SA Sub6 conditions by injecting external traffic to simulate public network congestion.
ResultsBoth 5G SA configurations achieved sub-120 ms latency with stable, uninterrupted video transmission. Sub6 mode provided smoother buffering and more predictable control performance than NR-DC. In contrast, 4G LTE and high-bitrate 5G NSA resulted in high latency and frequent video freezes. Under simulated congestion, 5G SA Sub6 maintained performance with up to 300 Mbps of background traffic, but transmission became unstable beyond 400 Mbps, leading to marked video degradation.
ConclusionThe Sub6-based 5G SA configuration achieved sub-120 ms latency and stable video transmission, approaching the clinically desirable < 100 ms threshold, indicating technical feasibility for telesurgical operation under controlled experimental conditions. However, its susceptibility to network congestion was evident. Further real-world validation and the integration of advanced traffic management technologies will be essential to ensure safe clinical deployment.