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The aim of this correspondence is two-fold: (i) to assess the performance of a conventional wireless system jointly subject to short-term fading (α-μmodel), long-term fading (Gamma model), path loss (power-law decay), and mobility (random waypoint model) through analytical formulations; and (ii) to assess the performance of a non-conventional wireless system subject to the same conditions as before but with the transmission-medium-receiving chain replaced by an autoencoder using deep neural networks. The paper derives novel closed-form expressions for the probability density function, cumulative distribution function, and moment-generating function of the received signal. The performance analysis under investigation concerns outage probability, symbol error probability, asymptotic analyses, and channel capacity, all in closed-form formulations. In addition to showing that mobility has a beneficial effect on the overall mean performance, this work also illustrates that the said unconventional system may achieve as good a performance of the conventional one.
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Pereira et al. (2023) studied this question.
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