Joint Preamble and AOA Estimation-Based Random Access Scheme for Cellular-IoT Networks

In this letter, to overcome the preamble collision issue of massive random access (RA) in cellular-IoT networks, we design a clustered ESPRIT-based joint preamble and angle of arrival (AOA) estimator, in which the AOA information of the user equipment (UE) is regarded as a new RA label. With the assistance of the obtained AOA information provided by the designed joint estimator, the base station (BS) can recognize every detected preamble that collided and further reduce the preamble collision probability. Simulation results show that compared with the benchmark, the proposed joint estimator-based RA (JERA) scheme not only obtains the AOA estimation of UE that has successfully accessed but also achieves a better RA performance.