An Adaptive User Scheduling Algorithm for 6G Massive MIMO Systems

Massive MIMO (Multiple-Input Multiple-Output) is a promising wireless access technology that has emerged as a solution to the ever-increasing demand for network capacity. Massive MIMO is expected to play a crucial role in the deployment of 5G and upcoming 6G networks, enabling the realization of their full potential capacity. Despite the numerous benefits, user scheduling during downlink communication in Massive MIMO systems is a challenging task due to the large number of antenna terminals. In this paper, we propose a novel scheduling algorithm aimed at improving the area throughput, sum capacity, error performance, and ensuring fairness among all users. The proposed algorithm uses the average channel rate as the scheduling criteria, which is calculated from the channel state information obtained from the users during uplink transmission. To evaluate the performance of our proposed algorithm, we conducted simulations using Matlab. Our results demonstrate that our proposed channel rate-based scheduling algorithm is superior to conventional scheduling algorithms in terms of sumrate, throughput, and bit error performance while also ensuring fairness among all users. The proposed algorithm can address the challenge of user scheduling in Massive MIMO systems and contribute to the efficient deployment of 5G and 6G networks. The ability to improve system capacity, area throughput, and provide fairness in communication is of great importance in meeting the high demands of future wireless networks. Our approach could pave the way for further research in improving the performance of Massive MIMO systems, thereby advancing the potential of 5G and 6G networks.