  To meet the ever growing demand for both high throughput and uniform coverage
in future wireless networks, dense network deployment will be ubiquitous, for
which co- operation among the access points is critical. Considering the
computational complexity of designing coordinated beamformers for dense
networks, low-complexity and suboptimal precoding strategies are often adopted.
However, it is not clear how much performance loss will be caused. To enable
optimal coordinated beamforming, in this paper, we propose a framework to
design a scalable beamforming algorithm based on the alternative direction
method of multipliers (ADMM) method. Specifically, we first propose to apply
the matrix stuffing technique to transform the original optimization problem to
an equivalent ADMM-compliant problem, which is much more efficient than the
widely-used modeling framework CVX. We will then propose to use the ADMM
algorithm, a.k.a. the operator splitting method, to solve the transformed
ADMM-compliant problem efficiently. In particular, the subproblems of the ADMM
algorithm at each iteration can be solved with closed-forms and in parallel.
Simulation results show that the proposed techniques can result in significant
computational efficiency compared to the state- of-the-art interior-point
solvers. Furthermore, the simulation results demonstrate that the optimal
coordinated beamforming can significantly improve the system performance
compared to sub-optimal zero forcing beamforming.
