Abstract The problem of the Modulation and Coding Scheme (MCS) selection in 5G V2X systems with Massive MIMO base stations is investigated. The high user mobility results in rapid aging of channel state information, which degrades the performance of conventional MCS and precoder selection algorithms. An MCS and precoder selection algorithm is proposed that is based on the autoregressive model for channel prediction with adaptive triggering of model retraining. Simulations show that the proposed algorithm can significantly reduce the channel resource consumption as compared with the algorithms that use a fixed model update period, while ensuring the desired reliability and data delivery time in variable user speed scenarios.
Glinskiy et al. (Sun,) studied this question.
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