Performance Analysis of NB-IoT Random Access Channel

The existing LTE network is software upgraded to support Narrow Band Internet Of Things (NB-IoT), which is designed to incorporate a massive number of ultra-low-power consuming and ultra-low complex devices operating in the poor coverage area, and the devices communicate to the internet through the existing cellular infrastructure. The massiveness of devices in the network will cause a collision which will degrade the performance of the system. The question that arises is what are the network parameters which could be optimized to reduce the collision in the massive access scenario. In this context, we evaluated the performance of NB-IoT random access channel by modeling the access channel as a multi-channel slotted aloha system. Focusing on the success probability of NB-IoT random access channel, we figured out that the subframe repetition number, back-off window selection, and random-access opportunity per device can be optimized to decrease the preamble collision under massive access scenario.