Preamble Detection in Asynchronous Random Access Using Deep Learning

• DOI: 10.1109/lwc.2023.3325918
• Publication Date: 2023-10-19T18:14:14Z
• Authors: Muhammad Usman Khan; Enrico Testi; Enrico Paolini; Marco Chiani

Grant-free random access protocols are among the enabling techniques for mMTC, where a large number of devices activate sporadically and transmit short packets, typically containing a preamble (or a pilot sequence), without any resource allocation from the BS. One of the critical tasks to be accomplished by the BS is thus the preamble-based detection of the transmitted packets. This letter proposes a DL-based solution for detecting preambles in an asynchronous grant-free random access uplink scenario, assuming multiple antennas at the BS. The DL-based approach outperforms the classical correlator-based approach.