Hybrid Active User Detection for Massive Machine-type Communications in IoT

Abstract

Massive machine-type communication (mMTC) concerns the access of massive machine-type communication (MTC) devices to the basestation. To support the massive connectivity, non-orthogonal multiple access (NOMA) and grant-free access have been recently introduced. In grant-free access, each device transmits information without scheduling so that the basestation needs to identify the active devices among all potential devices in a cell. This process, called an active user detection (AUD), is a challenging problem for the NOMA-based systems since it is difficult to find out the active devices from the superimposed received signal. To address this problem, compressed sensing (CS) based active user detection (All)) technique exploiting the low activity of devices in mMTC has been introduced. In this paper, we propose an All) scheme that exploits both pilot and data measurements to improve the All) performance in grant-free NOMA systems. The key idea is to use the common support information of pilot and data signals in a packet. Numerical results demonstrate that the proposed ALT) scheme outperforms the conventional approaches in both AUD and throughput performance.