Traffic Density-Based RRH Selection for Power Saving in C-RAN

TLDR: This paper investigates the power saving issue in the C-RAN, where it attempts to get a power consumption tradeoff between the optical transport network and the RRHs and develops an efficient local search algorithm, which includes three types of local improvement operations to address the intractable optimization task.

Abstract: Cloud radio access network (C-RAN) is deemed as a promising architecture to meet the exponentially increasing traffic demand in a mobile network. However, it needs a huge amount of transport capacity between the remote radio heads (RRHs) and the baseband unit pool. Though an optical transport network can be employed to support such a massive capacity, it always leads to enormous power consumption that is comparable with the transmission powers of the RRHs, which can significantly decrease the performance of the C-RAN if not well addressed. In this paper, we investigate the power saving issue in the C-RAN, where we attempt to get a power consumption tradeoff between the optical transport network and the RRHs. An RRH selection problem is formulated to achieve this goal, which is based on the traffic density of the service area. Our optimization task is to select a subset of the RRHs to minimize the total power consumption of the C-RAN while satisfying a series of network constraints, including the power and bandwidth budgets of the RRHs, the traffic demands of users, and the spectral efficiency. We develop an efficient local search algorithm, which includes three types of local improvement operations: “add,” “open,” and “close,” to address the intractable optimization task. Numerical results indicate that our proposal can significantly reduce the power consumption of the C-RAN. Moreover, our proposed algorithm converges stably and quickly, indicating that it is promising for applications.