  Non-orthogonal multiple access (NOMA) is considered to be one of the best
candidates for future networks due to its ability to serve multiple users using
the same resource block. Although early studies have focused on transmission
reliability and energy efficiency, recent works are considering cooperation
among the nodes. The cooperative NOMA techniques allow the user with a better
channel (near user) to act as a relay between the source and the user
experiencing poor channel (far user). This paper considers the link security
aspect of energy harvesting cooperative NOMA users. In particular, the near
user applies the decode-and-forward (DF) protocol for relaying the message of
the source node to the far user in the presence of an eavesdropper. Moreover,
we consider that all the devices use power-splitting architecture for energy
harvesting and information decoding. We derive the analytical expression of
intercept probability. Next, we employ deep learning based optimization to find
the optimal power allocation factor. The results show the robustness and
superiority of deep learning optimization over conventional iterative search
algorithm.
