Group-based Random Access with Age of Information Minimization in 6G umMTC

6G has defined ultra-massive machine type communication (umMTC) as a key scenario in response to the advancement of IoT technologies. The presence of a large number of machine-type communication devices (MTCDs) in umMTC calls for the research of efficient random access (RA) schemes. To address the problem of high collision rates in dense networks, a group-based RA approach has been introduced. In the group-based RA approach, we design an optimal congestion control method to minimize the Age of Information (AoI). Since AoI and collision rate are in a trade-off relationship, we aim to maximize the successful RA rate by iteratively searching for the optimal congestion control factor. Simulation results represent that the proposed scheme achieves a 10% collision rate and an average AoI of less than 100 age, enabling the 90% successful RA rate in 100,000 MTCDs deployment scenario.