DUCU Placement for CRAN over Optical MetroAggregation Networks To meet emerging mobile traffic requirements, Centralized Radio Access Network (CRAN) has been proposed to split the base station (BS) into two functional entities: the baseband units (BBU) and the remote radio heads (RRH). In CRAN, by centralizing BBUs into BBU pools and leaving the RRHs in the cell sites, significant cost and energy savings and improved radio coordination can be achieved. However, CRAN requires a costly highcapacity and lowlatency accessaggregation network to support fronthaul traffic (i.e., digitized baseband signal). Hence, more recently, a new CRAN architecture has been proposed (i.e., by 3GPP, IEEE 1914 WG), that defines three baseband function entities (or xe2x80x9csplitsxe2x80x9d): central unit (CU), distributed unit (DU) and remote unit (RU). These three entities are expected to be interconnected by two external interfaces, called F1 and Fx. By transforming the RAN into a 3layer (CUDURU) architecture, more flexible deployment of the baseband functions can be achieved that better adapts to the heterogeneous characteristics of incoming 5G service requirements. It is also expected that, by properly placing CUs and DUs in the metroaggregation network, higher benefits in terms of cost and power consumption can be achieved with respect to the previous 2layer (BBURRH) architecture. In this paper, we investigate the optimal CUDU placement problem in a 3layer RAN architecture and formalize it by integer linear programming. We evaluate the benefits of the 3layer architecture compared to the 2layer architecture, showing that the consolidation degree of baseband processing depends heavily on fronthaul traffic latency, transport network capacity and processing capacity.

Joint Fronthaul Optimization and SDN Controller Placement in Dynamic 5G Networks To address the limitations of current Radio Access Networks (RANs), centralizedRANs adopting the concept of flexible splits of the BBU functions between Radio Units (RUs) and the central unit (CU) have been proposed. This concept can be implemented combining both the Mobile Edge Computing model and relatively largescale centralized Data Centers. This architecture requires high bandwidthlow latency optical transport networks interconnecting RUs and compute resources adopting SDN control. This paper proposes a novel mathematical model based on Evolutionary Game Theory that allows to dynamically identify the optimal split option with the objective to unilaterally minimize the infrastructure operational costs in terms of power consumption. Optimal placement of the SDN controllers is determined by a heuristic algorithm in such a way that guarantees the stability of the whole system.