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Deep learning aided estimation of the probability of outage in multi-user NOMA

Neema M, E S Gopi, Venkatesh T K, Mukesh Gandhi


Artificial intelligence plays an important role in future telecommunication. In this paper, we demonstrate the usage of an artificial neural network (ANN) based regression model to obtain the closed-form expression for outage probability as a function of SNR in a multi-user Non-Orthogonal Multiple Access (NOMA). In this work, we propose two deep neural networks, The first one is to estimate the optimum power allocation among the users considering their channel conditions. The second network is used to determine the average probability of outage for a given set of channel conditions. The extensive experimental results promise the usage of  proposed technique in real-time scenario

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