# A Survey on Open Radio Access Networks: Challenges, Research Directions, and Open Source Approaches
## 6 Challenges and Future Research Directions
### Open RAN Field Issues
From this proposed architecture, experiment results show that the hierarchical orchestration approach can leverage the capabilities of existing orchestrators and their communities to achieve a remarkable resource allocation in E2E networks. However, this research still needs further studies. Future research should be directed towards identifying requirements, classes, and relations of ontology for hierarchical orchestration protocols. Also, future research should define a systematic translation, make a model, and evaluate and assess the new hierarchical orchestration model. A low-complexity, closed-loop control system for Open-RAN architectures to support drone-sourced video streaming applications is proposed by [95]. Flying drones has a higher likelihood of having line-of-sight propagation compared to UEs which can lead to performance degradation in high data rate transmission. The control system jointly optimizes the drone's location in space and its transmission directionality to minimize its uplink interference impact on the network. The proposed system was prototyped and tested in a dedicated outdoor multi-cell RAN testbed. Numerical simulations are also used to evaluate the system. Results show that the control scheme achieves an average 19% network capacity gain compared to traditional BS-constrained control solutions. Building a 5G network that is energy efficient is also an important issue. Increased network capacity, geographical coverage, and increased traffic demands require network densification and will lead to more energy consumption. The negative impact of exhaustive energy consumption will not only degrade business profits but also impact the environment. State-of-the-art applications of ML techniques used in the 5G RAN to enable energy efficiency are reviewed by [96]. Recent research focuses on the functional split technique for green Open RAN [97]. An RL-based dynamic function splitting (RLDFS) technique that decides on the dynamic function splits among DUs and the CU in an Open RAN system to make the best use of renewable energy source (RES) supply and minimize operator costs was proposed. Performance evaluation was performed using a real data set of solar irradiation and traffic rate variations. Results showed that the proposed RLDFS method effectively uses renewable energy and is cost-efficient. Other researchers also proposed F-RAN, or fog-computing-based RAN to improve RAN's performance and cost. This is another type of RAN, which its architecture is based on fog computing. Fog computing is a term for an alternative to cloud computing that puts a substantial amount of storage, communication, control, configuration, measurement, and management at the edge of a network [98]. This fog computing can be applied to C-RAN to alleviate the constraints of FH and high computing capabilities in BBU pool [10]. F-RAN has several advantages, such as rapid and affordable scaling. This makes F-RAN architecture much more adaptive to the dynamic traffic and radio environment. Even though F-RAN is considered an excellent solution for covering C-RAN's weaknesses, it still has some challenges and open problems  
Another method researchers propose to improve RAN's performance and cost is Air-Ground Integrated Mobile Edge Networks (AGMEN). AGMEN is proposed by [99] to integrate UAV-assisted network densification. In AGMEN, multiple drone cells are deployed flexibly to provide agic RAN coverage for the temporally and spatially changing users and data traffic. There are also several critical components in AGMEN, such as multi-access RAN with drone cells and UAV-assisted edge caching. However, AGMEN still has many challenges related to the heterogeneity and dynamic nature of architectural devices. Further research for AGMEN relates to mobile routing, multi-dimension channels, and UAV scheduling. The use of Digital Twin(DT) has the potential to enhance the principles of intelligence, autonomy, and openness within an O-RAN-based system.