Detection schemes and model mismatch analysis for 5G configured-grant access for URLLC
Focussing on factory automation and reliable real-time systems, this paper evaluates user detection in 5G configured-grant (CG) access. We show that the detection performance is significantly influenced by model mismatches resulting in increased misdetection probabilities and deviations from the expected false alarm probability. We demonstrate this effect considering correlation-based detectors and we propose a general likelihood ratio test (GLRT) that allows to minimize this performance reduction. Our simulator implements the 3GPP New Radio (NR) Rel. 15 to provide results directly applicable to the standardization process of 5G ultra-reliable and low-latency communication (URLLC).