  User association is necessary in dense millimeter wave (mmWave) networks to
determine which base station a user connects to in order to balance base
station loads and maximize throughput. Given that mmWave connections are highly
directional and vulnerable to small channel variations, user association
changes these connections and hence significantly affects the user's
instantaneous rate as well as network interference. In this paper, we introduce
a new load balancing user association scheme for mmWave MIMO networks which
considers this dependency on user association of user's transmission rates and
network interference. We formulate the user association problem as mixed
integer nonlinear programming and design a polynomial-time algorithm, called
Worst Connection Swapping (WCS), to find a near-optimal solution. Simulation
results confirm that the proposed user association scheme improves network
performance significantly by moving the traffic of congested base stations to
lightly-loaded ones and adjusting the interference accordingly. Further, the
proposed WCS algorithm outperforms other generic algorithms for combinatorial
programming such as the genetic algorithm in both accuracy and speed at several
orders of magnitude faster, and for small networks where exhaustive search is
possible it reaches the optimal solution.
