# A Survey on Open Radio Access Networks: Challenges, Research Directions, and Open Source Approaches
## 6 Challenges and Future Research Directions
### Open RAN Field Issues
Through the initial step that O-RAN Alliance took, other wireless communities, MNOs, and vendors can follow O-RAN's path by increasing their support toward developing complete and truly Open RAN and open-source RAN-related projects. Fortunately, more organizations are now expected to contribute to Open RAN. IEEE Standard Association has initiated an Open RAN Industry Connections Activity to help the existing Open RAN industry efforts [123]. This program will accelerate collaboration between organizations and individuals in the Open RAN field. The next open issue related to RAN is the latency issue. Rakuten's Open RAN deployment in Japan is a real-life example of this challenge. Even though the overall performance of Rakuten's Open RAN mobile network is rated \"very good\", the latency score shows room for improvement relative to major MNOs in assessed cities [21]. The latency problem is more severe in URLLC network slices that require low latency. Using vBBU could result in higher latency [71]. The following research should explore backup strategies for several use case scenarios. A gradient-based scheme is proposed by [124] to overcome the latency problem. This scheme solves Open RAN's minimum delay function placement and resource allocation. There are many layers of RAN, and Open RAN allows these layers to be split and deployed as virtual functions and openly communicate with each other layer for service provisioning. An E2E mobile operator employing Open RAN is modeled by [124], with a hierarchical mobile network architecture consisting of local, regional, and core data center layers. These three hierarchical layers add flexibility in resource allocation and increase reliability while taking advantage of Open RAN. In addition, the case where the traffic of a service function requests (SFRs) traverses multiple chains via a single path through containerized network functions (CNFs) is also modeled. This formulation proposed a gradient-based solution to achieve the optimal solution efficiently. This solution is applied through the gradient-based minimum delay (GBMD) algorithm. This algorithm can serve up to 90% E2E network delay decrease. Another method proposed by [125] can also be used to reduce latency for cross-service interactions in the network. The proposed method focuses on network slicing and is called optimized edge slice orchestration (MESON). This method is a combination of optimized cross-slice communication (CSC) in network-level slicing, MANO, and edge computing. MESON fosters cross-slice or tenant interactions, and provides the necessary means for the establishment of cross-service interactions, thus exploiting opportunities  
Figure 19: Open source 4G/5G software license types. for providing co-location service. The research has shown that the main operations in the MESON layer can lower the delay of the service response time, with a delay of less than 40 ms, with points of presence (PoPs) of at least 100, thus reducing network latency. Another issue that still exists in Open RAN is the issue of scalability. We already know that Open RAN is more scalable than its predecessors, thanks to NFV, SDN, and automation, which made the RAN more scalable and flexible in its management and orchestration [4]. Open RAN's framework relies heavily on AI-embedded software to maintain its scalability and flexibility [126]. RIC is also responsible for making Open RAN scalable. Both Non-RT and Near-RT RIC have made the RAN more scalable and adaptable. The Near-RT RIC provides a secure and scalable platform, thus making it possible to control its xApps flexibly [39]. All of these are undertaken to make Open RAN more scalable, leading to a more effective RAN, especially in terms of its performance. However, the scalability in Open RAN still needs to be improved. There are several concerns regarding the Open RAN scalability [22, 89]:  
1. Operators wanting to adopt the cloud-native Open RAN need to expect the cloud scaling challenges [22]. Scaling the DU virtualization across servers will be a real-time problem.