## 2 Related Work and Motivation
Techniques such as energy harvesting, resource allocation, massive Multiple Input Multiple Output (mMIMO), Device-to-Device (D2D) networks, spectrum sharing, and ultra-dense networks for 5G green cellular communication were explored. A multi-tier network architecture for 5G was also proposed to make it more energy efficient. [PERSON] et al. [29] presented a detailed overview of saving the energy of base stations by using sleep modes. A mechanism was provided to put the base station into sleep mode for ultra-dense cellular networks and wake them up when needed. Challenges and solutions related to energy-efficient cellular networks were also discussed. [PERSON] et al. [30] provided a brief overview of green cellular communication, considering techniques like D2D communication, mMIMO systems, Heterogeneous Networks (HetNets), and Green-IoT (G-IoT). Challenges related to cost, bandwidth, and spectral efficiency were also addressed. Similarly, [PERSON] et al. [31] presented a detailed overview of making cellular communication green. Strategies such as mMIMO, D2D communication, Millimeter Wave (mmWave), HetNet network deployment, and C-RAN were considered. Hardware solutions to develop an energy-efficient smart grid were also explored. [PERSON] et al. [32] explored the importance of green communication and presented a research overview on Artificial Intelligence (AI)-based green cellular communication. The use of AI-based systems to manage the cellular network and enhance energy efficiency was emphasized. The authors also investigated the use of Machine Learning (ML), especially deep learning, to enhance 6G cellular technology. [PERSON] et al. [33] presented the deployment of a smart grid for 5G cellular systems to reduce power consumption. Similarly, [PERSON] et al. [34] explored techniques such as smart grids, HetNet network architecture, and sleep modes of base stations to develop energy-efficient cellular communication. Additionally, it was mentioned that environmental activists, regulators, and the government could encourage eco-friendly base stations in Nigeria. [PERSON] et al. [35] and [PERSON] et al. [36] presented a survey on developing green cellular communication by utilizing the sleep mode technique for base stations. Energy harvesting was also considered to power up the base stations. [PERSON] et al. [37] provided information about ongoing research on beamforming for energy harvesting in cellular communication networks. The performance of the beamforming system in energy-harvesting cellular communication was also investigated. [PERSON] et al. [38] simulated the base station sleep mode mechanism to enhance energy efficiency for 5G and LTE communication systems. The Particle Swarm Optimization (PSO) algorithm was utilized to maintain coverage using LTE base stations when 5G base stations were switched off. The outcome of this simulation work showed that 3.52 kW of energy per day could be conserved while maintaining high data rates when 5G base stations were switched off. Similarly, [PERSON] et al. [39] focused on implementing Self-Adaptive-Scheduling (SAS) algorithms to switch 5G base stations on and off to enhance energy efficiency and reduce CO\({}_{2}\) emissions. [PERSON] et al. [40] carried out a survey on energy-efficient 5G networks and emphasized the use of energy-harvesting hardware. [PERSON] et al. [41] presented the challenges of minimizing power consumption in green energy-powered C-RAN. This challenge was represented by Mixed Integer Linear Programming (MILP), and a two-phase heuristic polynomial-time algorithm was introduced to solve the problem. [PERSON] et al. [42] carried out a simulation to investigate energy consumption in cellular crosshaul networks. Possible C-RAN configurations were explored. It was concluded that carrying out more data processing before transmission was more energy efficient while enhancing the network. The study's findings emphasized the importance of choosing the right functional split, as the scenarios differed in energy consumption by a factor of 40.