# Adaptive BBU Migration Based on Deep Q-Learning for Cloud Radio Access Network
## 1 Introduction  
As mobile technologies have advanced from 1G to 6G, the objectives of users and network operators have changed. However, communities are becoming more data-centric, reliant on data, and automating their activities more and more in the modern world. The widespread application of automation in industrial production processes will greatly boost productivity. Millions of sensors will be deployed across homes, factories, and cities, with AI-powered systems running in local cloud and fog environments to support innovative applications [1, 2, 3, 4, 5]. To accommodate a wide range of devices and address future data demands, 6G new radio (NR) networks are anticipated to meet these needs through expertly managed spectrum resources [6, 7, 8]. The goal of recent research has been to determine how to improve the power efficiency of cellular networks. Numerous strategies have been proposed to reduce the energy consumption of BSs, which make up 60-80% of the total energy usage [9, 10]. One of these strategies is switching from the conventional distributed base station (D-BS) design [11] to the cloud radio access network (C-RAN), a centralized,cooperative, cloud-based, and environmentally friendly radio base station architecture that China Mobile proposed in 2010 [12; 13]. The architecture of the cloud radio access network consists of two parts: the remote radio head (RRH) and the baseband unit (BBU). Digital processing of baseband signals is performed by the BBU in conjunction with all higher-layer operations. Using antennas, RRH transmits and receives wireless signals [14; 15]. The use of the distributed base station architecture as a next-generation base station platform is constrained by a number of problems. The following highlights a few of these D-BS architecture drawbacks and how C-RAN addresses them [16]. 1. **Problem:** In a standard RAN or distributed BS architecture, the number of BS increases and the matching cell size reduces as the number of cellular users rises. This results in higher CAPEX and OPEX as well as increased power consumption [17; 18]. **Solution:** The baseband processing is performed at a centralized site, whereas the RF unit is kept at a distributed position under the architecture that China Mobile introduced. Therefore, centralization lowers power consumption and associated costs even as the number of cells grows. 2. **Problem:** The conventional RAN relies on a costly radio frequency (RF) component and a specialized signal processing unit, which results in a large unit that requires additional room to operate [19]. **Solution:** Because the RF unit is small and light, it may be placed in any commonplace, such as a light pool, tree trunk, or rooftop. Once more, C-BBU's usage of load balancing and virtualization technology results in a smaller BS architecture by reducing the size of the BBU pool. 3. **Problem:** The main switching center (MSC) is the only component responsible for network connectivity in the conventional RAN architecture, which lengthens network latency. **Solution:** C-RAN integrates certain MSC control plane functions into the C-BBUs. The overall end-to-end time delay and backhaul congestion are further minimized, as control and processing tasks are handled at the C-BBU, which is positioned closer to the user equipment (UE). Additionally, the flexibility and scalability of C-RAN are increased by the use of virtualization and cloud computing technology at the radio access network (RAN) platform [20] which decreased the number of base stations. A single platform can provide services to various cellular operators according to their service level agreement (SLA) by using the aforementioned concepts [21]. The load distribution among different BBUs in the BBU pool fluctuates significantly due to the continual initiation or termination of communication services. Low-load or idle BBUs must remain active in the same operational state as high-load BBUs to ensure uninterrupted service for users within the coverage area.