Performance of a Massive MIMO IoT System With Random Nonorthogonal Reference Signals.

To support a vast amount of Internet of Things (IoT) devices using massive multiple-input multiple-output (MIMO) systems simultaneously, due to the limited available resources, uplink orthogonal reference signals (ORSs) must be heavily reused for channel estimation. In this situation, the performance of massive MIMO systems can be seriously degraded due to the collision of ORSs. Random nonorthogonal reference signals (NORSs) can be considered to cope with this problem since they can be independently generated regardless of the number of IoT devices. However, as the number of IoT devices increases, RS contamination also increases. In this article, we consider applying random NORSs in massive MIMO to support a large amount of IoT devices. Generally, ORSs can deliver better spectral efficiency (SE) than NORSs. However, we show that the NORS scheme has higher fairness and lower outage probability. In addition, in the situation of massive IoT, the SE performance of the NORS scheme shows substantially similar to that of the ORS scheme. These results indicate that the NORS scheme has several advantages compared to the ORS scheme in the situation of massive IoT. We provide numerical analysis which reveals some useful characteristics of using NORSs for massive MIMO with massive IoT connectivity. Using these characteristics, we propose an algorithm that can significantly reduce the outage probability.