  User association determines which base stations a user connects to, hence
affecting the amount of network interference and consequently the network
throughput. Conventional user association schemes, however, assume that user
instantaneous rates are independent of user association. In this paper, we
introduce a new load-aware user association scheme for millimeter wave (mmWave)
MIMO networks which takes into account the dependency of network interference
on user association. This consideration is well suited for mmWave
communications, where the links are highly directional and vulnerable to small
channel variations. We formulate our user association problem as a mixed
integer nonlinear programming (MINLP) and solve it using the genetic algorithm.
We show that the proposed method can improve network performance by moving the
traffic of congested base stations to lightly-loaded base stations and
adjusting the interference accordingly. Our simulations confirm that our scheme
results in a higher network throughput compared to conventional user
association techniques.
