QoS-Aware Balanced and Unbalanced Associations in Massive MIMO Enabled Heterogeneous Cellular Networks

As for the massive MIMO (multiple-input and multiple-output) enabled HCNs, we design a QoS-aware association scheme to maximize the sum of achievable rates under long-term rate constraints. Since the various BSs have different transmit power and antennas, this scheme (unbalanced association) may result in an extremely imbalanced load distribution. To fully exploit the network resources, we design another scheme (balanced association) to maximize the network-wide utility that is a logarithmic function of long-term rates. In fact, these schemes can be well implemented in the practical scene since the users can introduce long-term rate constraints to guarantee their QoS requirements. Significantly, it is not the case for the most existing schemes. Considering that these formulated problems are in a nonlinear and mixed-integer form and hard to tackle, we try to develop centralized algorithms using Lagrange multiplier method and distributed algorithms using dual decomposition. Numerical results show that the balanced association significantly outperforms the unbalanced association on the load balancing gain, rate fairness, but the QoS guarantee. In addition, we also show the impacts of the number of massive antennas on the association performance.