Abstract
Enhancing energy efficiency (EE) in the radio access network (RAN) arises as an important issue for the environmental and economic concerns as well as for prolonging the battery lifetime of mobile devices. In a radio access network (RAN), moving a portion of network functions from the edge nodes into a centralized pool forms the cloudified RAN. This centralized architecture enables large-scale cooperation among densely deployed edge nodes to improve the EE of cloudified RAN. Besides, with powerful processing capabilities, the cloudified RAN can support the implementation of computation offloading where the power-hungry and compute-intensive tasks are offloaded from the mobile devices to the cloudified RAN to achieve the goal of energy saving for the mobile devices. The performance of lifting EE in the cloudified RAN is restricted by the capacity of the fronthaul link which connects the cloud and the edge node. The compression and datasharing strategies are two transmission schemes on the fronthaul link that can reduce the fronthaul load and alleviate the fronthaul capacity restriction. In this dissertation, we investigate the energy-efficient design of the fully cloudified RAN, i.e., cloud RAN and energy conservation for mobile devices via the computation offloading in the partially cloudified RAN, i.e., fog RAN, respectively. To realize the green fully cloudified RAN, i.e., cloud RAN (C-RAN), we investigate and compare the beamformer design with the compression and data-sharing strategies, respectively. The worst-case EE of C-RAN is maximized when the imperfect channel state information is considered. To study the energy conservation on mobile devices, we use the fog RAN (F-RAN) as a hierarchical cloud computing system to process the offloaded tasks from mobile devices. In this work, considering compression-and-forward transmission mechanism and uncertain computation capacity at the EN and the RC, we aim to design energyefficient computation offloading mechanism for delay-sensitive applications in F-RAN.