  We propose a method to improve the performance of the downlink coordinated
multipoint (DL CoMP) in heterogeneous fifth generation New Radio (NR) networks.
The standards-compliant method is based on the construction of a surrogate CoMP
trigger function using deep learning. The cooperating set is a single-tier of
sub-6 GHz heterogeneous base stations operating in the frequency division
duplex mode (i.e., no channel reciprocity). This surrogate function enhances
the downlink user throughput distribution through online learning of non-linear
interactions of features and lower bias learning models. In simulation, the
proposed method outperforms industry standards in a realistic and scalable
heterogeneous cellular environment.
