## 2 Related Work and Motivation  
This section provides an overview of prior research work related to energy-efficient cellular networks. Table 1 provides a comparative analysis of key research contributions in the field of energy-efficient cellular networks. It categorizes various studies based on their focus areas, including SDN, NFV, C-RAN, and other green communication strategies. This classification helps highlight existing gaps and supports the argument for integrating SDN, NFV, and C-RAN to enhance network sustainability. [PERSON] et al. [18] focused on making off-grid cellular base stations more sustainable by utilizing renewable energy sources, such as solar power, and energy storage. The size of solar panels, converters, and batteries was examined based on the macro Long-Term Evolution (LTE) base station's daily energy consumption requirements. In this study, an optimal solar design, energy output, and cost were considered using the HOMER tool [19]. The results demonstrated that this approach guaranteed 100% energy independence and long-term stability for LTE base stations. [PERSON] et al. [20] introduced an optimal energy-sharing framework as Multi-Objective Linear Programming (MOLP). This framework primarily targeted two goals: the energy collected at the base station and the load on the  
Figure 3: Block Diagram of cellular architecture based on SDN, NFV, and C-RAN. base station in future time slots. Deep Q-learning was used to predict the energy collected at the base station, and the results were simulated in MATLAB version R2017b. The obtained results showed that the considered multi-operator energy cooperation surpassed the current methods in terms of deployment and management cost, performance, and energy efficiency. [PERSON] et al. [21] presented an overview of sustainable and energy-efficient cellular base stations. The cellular base station system models and the possibilities of using renewable energy solutions were investigated. Along with these, locations where renewable energy-based base stations could be deployed were proposed. [PERSON] et al. [22] explored a hybrid energy-sharing system for LTE renewable energy-powered base stations using physical power lines. In this architecture, each LTE base station was equipped with its own renewable energy source and storage, and access to electricity/energy was shared via power cables to reduce the load on traditional energy sources. The proposed architecture was simulated for the LTE cellular system, and the output showed a significant reduction in the average energy consumption. Similarly, [PERSON] et al. [23] explored the practicality of using solar power and wind turbines attached to an energy storage system in an LTE base station located in a remote area of Bangladesh. [PERSON] et al. [24] explored the combination of solar Photovoltaic (PV) and biomass resources to power off-grid LTE cellular base stations in Bangladesh. A hybrid energy-sharing system was used, and it was concluded that this approach was cost-effective and energy efficient. [PERSON] et al. [25] introduced an Ultra-Dense Heterogeneous Network (UDHN), and the considered architecture was simulated. A random access method was proposed to improve network efficiency, reduce signaling overhead, and enhance energy efficiency. The simulated results confirmed the effectiveness of the considered network architecture. The authors also highlighted the main challenges faced by the UDHN. [PERSON] et al. [26] presented a quick overview of methods such as heterogeneous networks and cell-zooming to make cellular communication more energy efficient. Research challenges were discussed, and techniques for greener cellular communication were suggested. [PERSON] et al. [27] considered energy-efficient resource allocation, network planning, the use of renewable energy resources, and C-RAN to make 5G and beyond 5G cellular networks more energy efficient. [PERSON] et al. [28] presented a comprehensive review of approaches that could be considered to make 5G communication networks more energy efficient.