Channel prediction-based user selection algorithm for multiuser environments

摘要

In this paper, we propose a channel prediction-based user selection algorithm for a single-cell wireless network with multiuser environments. The proposed algorithm focuses on mitigating the degradation of performance due to a feedback process. In particular, by using the Naive Bayes (NB) classifier, the proposed algorithm selects the user who is expected to have the biggest channel gain after feedback delay. Simulation results show that the proposed algorithm mitigates a performance decrease of achievable rates.