# NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations
## 2 NFV/SDN as an Enabler for UAV Network-Related Work  
NFV (Network Function Virtualization) and SDN (Software Defined Network) are needed as key technologies to achieve variable control of networks and computing for UAV networks. Here, NFV is a platform for deploying applications with computing resources, which is known as MEC (Multi-Access Edge Computing). In [20], the authors proposed an algorithm for controlling backhaul between network devices using OVS (Open Virtual Switch) and Open Flow-based SDN under varying user requirements and showed its effectiveness through numerical analysis. In [21], a testbed was constructed to demonstrate the effectiveness of the proposed algorithm in tracking applications and networks as users move. Specifically, the SDN controller detects user context information, migrates applications to the user's destination using MEC-NFV, and controls the backhaul network with SDN. On the other hand, the system was extended to millimeter-wave V2X (Vehicle-to-Everything) scenarios and evaluated through field demonstration experiments [22]. SDN controls the backhaul to obtain other RSUs (Road Side Units), enabling cooperative communication, which supports safer automated driving.  
Furthermore, we have proposed an algorithm that dynamically controls not only the backhaul network but also the power supply of the base station by SDN according to the traffic conditions of the user [23]. The proposed method effectively satisfies both user satisfaction and power supply connectivity. Furthermore, the significance of using NFV technology to run applications on MEC connected by network control was shown from the perspective of the operator holding the MEC [24]. In addition, the NFV/SDN controller was designed from an E2E viewpoint for MEC, considering both the application and the network [25]. PoC (Proof-of-Concept) of [25] validated the effectiveness of the MEC in the outdoor field.  
Regarding UAV networks, various studies have discussed [26; 27; 28] taking advantage of SDN. As mentioned above, SDN can be applied to UAVs to maintain a backhaul network and connect to nearby base stations in a dynamically changing UAV network configuration. Moreover, by adding MEC-NFV as well as SDN in [29; 30; 31], it is possible to deploy simple applications (e.g., cache contents) by holding a small computing resource in the UAV.  
From a different aspect, signaling control with NFV/SDN was discussed in [32; 33; 34]. In [32], an algorithm was proposed for finding user pairing and power allocation that can maximize the wireless communication capacity using the NOMA (Non-OrthogonalMultiple Access) at the access side. In [33], an interference control method was proposed by changing the number of UAVs and their deployment method to an objective function and flexibly changing them to take advantage of SDN features. In contrast to the above two references, this paper proposes a frequency division method focusing on the access side and thus has a different objective target. On the other hand, [34] proposed an algorithm to control the traffic signal to reduce the energy of computation and latency on the UAV side. Different from [34], this paper proposes a control method that can maximize throughput on the UAV side.  
For these reasons, this paper employs NFV/SDN as a key enabler for a dynamic construction of our proposed UAV networks.