  Integrating unmanned aerial vehicles (UAV) to non-orthogonal multiple access
(NOMA) visible light communications (VLC) exposes many potentials over VLC and
NOMA-VLC systems. In this circumstance, user grouping is of importance to
reduce the NOMA decoding complexity when the number of users is large; however,
this issue has not been considered in the existing study. In this paper, we aim
to maximize the weighted sum-rate of all the users by jointly optimizing UAV
placement, user grouping, and power allocation in downlink NOMA-VLC systems. We
first consider an efficient user clustering strategy, then apply a swarm
intelligence approach, namely Harris Hawk Optimization (HHO), to solve the
joint UAV placement and power allocation problem. Simulation results show
outperformance of the proposed algorithm in comparison with four alternatives:
OMA, NOMA without pairing, NOMA-VLC with fixed UAV placement, and random user
clustering.
