  This work studies centralized radio resource management in metropolitan area
networks with a very large number of access points and user devices. A central
controller collects time-averaged traffic and channel conditions from all
access points and coordinates spectrum allocation, user association, and power
control throughout the network on an appropriate timescale. The timescale is
conceived to be seconds in today's networks, and it is likely to become faster
in the future. The coordination problem in each time epoch is formulated as a
network utility maximization problem, where any subset of access points may use
any parts of the spectrum to serve any subsets of devices. It is proved that
the network utility can be maximized by an extremely sparse spectrum
allocation. By exploiting this sparsity, an efficient iterative algorithm with
guaranteed convergence is developed, each iteration of which is performed in
closed form. The proposed centralized optimization framework can incorporate a
broad class of utility functions that account for weighted sum rates, average
packet delay, and/or energy consumption, along with very general constraints on
transmission powers. Numerical results demonstrate the feasibility of the
algorithm for networks with up to 1,000 access points and several thousand
devices. Moreover, the proposed scheme yields significantly improved throughput
region and average packet delay comparing with several well-known competing
schemes.
