Empirical Study of Network Slicing Performance for Healthcare IoT Applications on Nigerian 5G Infrastructure

Network slicing in 5G networks enables the creation of virtualised logical networks with guaranteed quality of service parameters, offering theoretical promise for priority healthcare IoT applications, but empirical performance data for network slicing under the specific traffic conditions and infrastructure characteristics of Nigerian 5G deployments are absent. This study empirically evaluated network slicing performance for healthcare IoT applications including vital signs telemetry, medical imaging transmission, and hospital asset tracking on a testbed emulating the MTN Nigeria 5G network architecture in Lagos. A 5G core network testbed was constructed using Open5GS and UERANSIM on virtualised infrastructure, with network slicing configured using three slice types: eMBB for medical imaging (guaranteed 50 Mbps minimum throughput), URLLC for vital signs telemetry (target latency below 5 milliseconds), and mMTC for asset tracking (1,000 devices per square kilometre density). Traffic isolation between slices was verified under mixed load conditions by simultaneously loading all three slices to 80 percent capacity. Results showed URLLC slice latency remained below 4.8 milliseconds at 80 percent load, meeting the target. eMBB slice throughput maintained 48.7 Mbps minimum at 80 percent load, within 3 percent of the guaranteed rate. mMTC device registration success rate was 99.4 percent at 800 devices per km2. Cross-slice interference resulted in zero degradation under all tested conditions, confirming isolation effectiveness. The study recommends Nigerian mobile operators prioritise URLLC slice standardisation for hospital deployments and engage the Federal Ministry of Health on healthcare 5G connectivity standards.

Keywords: network slicing, 5G healthcare IoT, URLLC, Open5GS, Nigeria