1 Apt-RAN: A Flexible Split Based 5G RAN to Minimize Energy Consumption and Handovers Himank Gupta, Student Member, IEEE, Mehul Sharma, Student Member, IEEE, Antony Franklin A, Senior Member, IEEE, Bheemarjuna Reddy Tamma, Senior Member, IEEE Abstract—The recent adoption of virtualized technologies in Next Generation Radio Access Network (NG-RAN) has driven a significant impact on energy consumption by subsequently decreasing the number of active base stations. The base sta- tion (gNodeB) of 5G is segregated into cost-efficient Central Units (CU) hosted on virtual platforms and cheaper & smaller Distributed Units (DU) present at the cell sites. Multiple CUs are pooled together in a single powerful central cloud, known as CU pool. The logical connection between DU and CU can be dynamically adjusted and can potentially affect the energy consumption of the CU pool. The deployment of NG-RAN imposes strict latency requirements on the fronthaul link that connects DUs to CU. To relax these strict latency requirements, various alternate architectures such as Flexible RAN Functional Splits have been proposed by 3GPP. In this paper, we first evaluate the energy consumption of DU and CU for various functional split options using OpenAirInterface (OAI), a real- time open source software radio solution. We find that lower layer splits have high energy consumption at CU as compared to higher layer split options. We also observe the variation in energy consumption due to traffic heterogeneity. Motivated by the above study, we formulate an optimization model, Apt-RAN, that optimizes the energy consumption of the CU pool and the number of handovers, considering different functional splits. To address the computational complexity of solving the optimization model, a lightweight polynomial time heuristic algorithm is proposed. Simulation results demonstrate that our proposed model outperforms existing state-of-art schemes. Index Terms—Central Unit (CU), Distributed Unit (DU), Flex- ible functional splits, Handovers, OpenAirInterface (OAI), CU Pool. I. I NTRODUCTION Over the past few years, the popularity of internet-enabled smartphones and tablets, along with data-intensive high-end applications, have increased to preposterous heights [1]. This has resulted in a colossal increase in data demand and has forced the network operators to upgrade their networks con- stantly while keeping the costs as low as possible to offer competitive prices. While the current network architecture was not originally designed to cope up with such exponentially growing rate, Next Generation Radio Access Networks (NG- RAN) has been recently introduced as a competent and profi- cient solution to address the above issues as well as to reduce the deployment cost. In NG-RAN, the protocol stack of Next Generation Node B (gNB) is split into two components, Central Units (CU) and Distributed Units (DU) [2]. DUs remain at the cell site to provide basic signal transmission functionalities whereas CUs are aggregated in a CU pool where cloud computing and vir- tualization mechanisms are used to provide significant energy DU n DATA CENTER OR BS CLOUD . . . . Fig. 1: Programmable & virtualized computing center for CUs in NG-RAN. efficiency and multiplexing gains, as shown in Fig. 1. Both CU and DU communicate through a low latency high-bandwidth interface called as fronthaul interface. Specifications from Common Public Radio Interface (eCPRI) [3] and Next Gen- eration Fronthaul Interface (NGFI) [4] are used to carry the IQ samples over the fronthaul link. The bandwidth and latency budget required to run a fully centralized solution is extremely high. As per 3GPP report [5], a fully centralized network considering 5G-NR with 100 MHz and 32 antennas requires a fronthaul bandwidth 157.3 Gbps. Such a high capacity may not be affordable and thus leaves a room for improvement. Therefore, 3GPP proposed the concept of functional splits to have a partially centralized NG-RAN architecture. A func- tional split determines which gNB functions to be left locally at the cell site and which functions to be moved to the central CU Pool. The functional splits, along with centralization and virtualization technology, provides a higher degree of freedom that can be utilized to make optimized decisions. The traffic pattern of a cell is observed to be influenced by its geographical location and its neighboring cells, known as spatio-temporal traffic variation or the tidal effect, as shown in Fig. 2. It can be observed that the DU load is more during weekdays as compared to the load during the weekends. It is also noticeable that peak load occurs only for few hours of