"In a free space optics (FSO) based drone assisted mobile network, a drone mounted base station (DBS) can be rapidly deployed over a place of interest to relay traffic between mobile users and a macro base station (MBS), and FSO is applied as the fronthaul solution between the DBS and the MBS to provide a high link capacity at a long distance. However, due to inevitable optical beam misalignment, having a smaller divergence angle of the optical beam may increase the outage probability of the FSO based fronthaul link. On the other hand, having a larger divergence angle may reduce the capacity of the FSO based fronthaul link. So, it is critical but challenging to determine the divergence angle in order to optimize the tradeoff between minimizing the outage probability and maximizing the capacity for the FSO based fronthaul link in the context of the FSO based drone assisted mobile network. In this paper, we formulate an optimization problem to determine the optimal divergence angle that can minimize the link outrage probability, while guaranteeing the capacity of the FSO based fronthaul link no less than the threshold. The Link outagE and cApacity awaRe divergeNce angle (LEARN) algorithm is designed to efficiently solve the problem. The performance of LEARN is demonstrated via extensive simulations by comparing its performance with the baseline method, where the divergence angle is fixed under different settings."