Preamble Detection in NB-IoT Random Access with Limited-Capacity Backhaul

We study multi-base station (BS) preamble detection schemes for the narrow-band Internet of Things (NB-IoT) random access by using stochastic geometry analysis. Specifically, we compare the preamble detection performance of two baseline detection schemes: Quantize-and-Forward (QnF) and Detect-and-Forward (DnF). QnF requires the feedback of quantized received power levels while DnF requires 1-bit feedback of local detection result. Our results show that DnF scheme outperforms QnF scheme when the backhaul capacity is limited or when the minimum distance between user and BSs is less than a threshold. Our results also show that the use of multiple collaborative BSs can lead to a significant improvement of the preamble detection performance, as well as reduction of the total power of the preamble transmission.