Pricing-Based Resource Allocation in Virtualized Cloud Radio Access Networks

With centralized processing, cooperative radio, and cloud infrastructure, cloud radio access network (CRAN) has attracted much attention due to its flexibility in network operation and resource management. In this paper, we propose a pricingbased resource allocation strategy in virtualized CRANs, where one mobile network operator (MNO) owns the physical resource and multiple mobile virtual network operators (MVNOs) serve their users with resources leased from the MNO. The problem is naturally formulated as a bi-level optimization problem, where the upper level corresponds to revenue maximization of the MNO and the lower level corresponds to the utility-surplus maximization of the MVNOs. To solve the problem efficiently, we propose to solve the MVNO problem with a low-complexity algorithm, which scales well with the network size. Based on the analysis of the revenue of the MNO, we find that different utility function families result in distinct revenue trends with respect to the price, and correspondingly propose efficient algorithms to find the optimal price that maximizes the revenue. Through simulations, we demonstrate that the proposed algorithm for the MVNO problem can reduce the complexity from O(M
³
) of interior point methods to O(M), where M is the number of users. Meanwhile, the simulation results show that the proposed pricing methods can find the optimal price in a few iterations.