Migration from distributed to centralized radio access networks (C-RANs) can be expensive in terms of capital expenditures due to the initial investment while it has lower operational expenditures due to pooling baseband processing into the cloud and reduced power consumption. Partial centralization can be also an option by employing network function splitting and keeping lower physical layer functions co-located with the radio units. This increases the power consumption but relaxes the high capacity requirement in the fronthaul. It is not intuitive which migration strategy is more cost effective. In this paper, we formulate a pool placement optimization problem as an integer linear programming (ILP), which minimizes the total cost of ownership (TCO), and evaluate the migration cost to C-RAN with both full centralization of network functions, and partial centralization by using function splitting. We define a network upgrade optimization problem, by adding new cells to the network, as a revisited version of the original optimization problem to evaluate the upgradability of the architectures. We solve the problem with both ILP for optimality, and genetic algorithm for scalability. Simulation results show that partial centralization results in optimal TCO with lower crossover time compared to C-RAN with full centralization. Index Terms-Total cost of ownership, functional splitting, C-RAN, integer linear programming, genetic algorithm.

Abstract-Centralized Radio Access Network (C-RAN) has been recently proposed to increase network capacity, reduce energy consumption, and improve scalability. However, C-RAN requires an extensive modification to the current infrastructure, which results in a considerable deployment cost. In this paper, we conduct a techno-economic study to evaluate the migration cost of C-RAN, and we propose a methodology for cost and energy efficient C-RAN deployment. We exploit the concept of total cost of ownership, defined as the sum of capital and operational expenditures. We formulate a Digital Unit (DU) pool placement optimization problem as Mixed Integer Linear Programming (MILP), which minimizes the total cost of ownership. We compare the total cost of ownership of C-RAN to that of the existing infrastructure, under different deployment scenarios such as greenfield and brownfield deployment of fiber and DU pool, and different cell sizes. The results show that the optical infrastructure plays a determinant role in the migration cost of C-RAN. If greenfield fiber is assumed, the migration cost cannot be compensated in a reasonable amount of time. If brownfield fiber is assumed, the migration cost is considerably reduced, and a more feasible C-RAN deployment is achieved.