  Modern day wireless networks have tremendously evolved driven by a sharp
increase in user demands, continuously requesting more data and services. This
puts significant strain on infrastructure based macro cellular networks due to
the inefficiency in handling these traffic demands, cost effectively. A viable
solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial
nodes between the macro and small cell tiers for improving coverage and
boosting capacity. This letter investigates the problem of user demand based
UAV assignment over geographical areas subject to high traffic demands. A
neural based cost function approach is formulated in which UAVs are matched to
a particular geographical area. It is shown that leveraging multiple UAVs not
only provides long range connectivity but also better load balancing and
traffic offload. Simulation study demonstrate that the proposed approach yields
significant improvements in terms of 5th percentile spectral efficiency up to
38\% and reduced delays up to 37.5\% compared to a ground-based network
baseline without UAVs.
