A Massive Grant‐Free Random Access Scheme Based on Spectrum Sensing and Preamble Delay

ABSTRACT As a cornerstone of the internet of things, massive grant‐free random multiple access (MGFRMA) has attracted wide attention in recent years. However, due to lack of coordination, it is difficult to remove access collisions among randomly activated users, which makes the existing solutions unsatisfactory. To solve the issue, this paper introduces cognitive radio (CR) and preamble delay (PD) to reduce access collisions, together with non‐orthogonal multiple access (NOMA) to improve spectrum efficiency, and then develops a CR‐NOMA‐PD‐based MGFRMA scheme. First, a three‐step MGFRMA protocol is advanced. It helps users to obtain the channel occupancy state before uplink transmission with spectrum sensing so as to consciously avoid access conflicts. Then, an optimisation strategy for jointly selecting access channel and power level is designed according to the sensing results. The competitive transmission scheme with PD is formulated, based on which uplink signals are well modelled. Finally, a multi‐user detection algorithm involving channel filtering, power level detection, preamble detection, and data recovery is proposed. The performance of the CR‐NOMA‐PD‐based MGFRMA scheme is also analysed and simulated. Simulation results indicate that the proposed scheme improves the access ratio of users and system overload capacity significantly compared to the existing schemes. It also has better robustness and scalability.