  The increasing demand for rich multimedia services and the emergence of the
Internet-of-Things (IoT) pose challenging requirements for the next generation
vehicular networks. Such challenges are largely related to high spectral
efficiency and low latency requirements in the context of massive content
delivery and increased connectivity. In this respect, caching and
non-orthogonal multiple access (NOMA) paradigms have been recently proposed as
potential solutions to effectively address some of these key challenges. In the
present contribution, we introduce cache-aided NOMA as an enabling technology
for vehicular networks. In this context, we first consider the full file
caching case, where each vehicle caches and requests entire files using the
NOMA principle. Without loss of generality, we consider a two-user vehicular
network communication scenario under double Nakagami$-m$ fading conditions and
propose an optimum power allocation policy. To this end, an optimization
problem that maximizes the overall probability of successful decoding of files
at each vehicle is formulated and solved. Furthermore, we consider the case of
split file caching, where each file is divided into two parts. A joint power
allocation optimization problem is formulated, where power allocation across
vehicles and cached split files is investigated. The offered analytic results
are corroborated by extensive results from computer simulations and interesting
insights are developed. Indicatively, it is shown that the proposed
caching-aided NOMA outperforms the conventional NOMA technique.
