# Oceania's 5G Multi-Tier Fixed Wireless Access Link's Long-Term Resilience and Feasibility Analysis
## 2 Materials and Methods  
In the context of earlier generations, the network design problem has been thoroughly studied [6; 14; 15]. For instance, the authors advocated using probabilistic techniques to move the position of eNodeB nodes while considering the construction of LTE cells [16]. To find the best site for the base station (BS), the authors suggested a greedy BS deployment algorithm [17]. To reduce the impact of cell edge effects, the deployment is based on core areas. The authors looked at the placement of various user distributions in the target area after selecting the parameters used for input and the number of base stations in the LTE network [16]. The short wavelength of the mm waves limits the range. Therefore, in theory, a significant number of mRRUs must be installed in a cellular network. Most of the research work already conducted [18; 19; 20] dealt with mRRU solo planning. For example, the energy efficiency potential of 5G mobile networks is analyzed, and an analytical model for 5G cloud planning and sizing RAN is reported in [21]. Other studies take a different angle on the planning and deployment of the 5G network. [PERSON] et al. suggested a method for figuring out where base stations should be placed to maximize the coverage of various 5G frequencies in urban settings [22]. A unique open-source techno-economic assessment tool for 5G deployment in macro-cellular scenarios was proposed [23] to reduce costs through infrastructure sharing [24]. In Ref. [16], the authors discuss capacity and coverage planning and analyze coverage and capacity adaptation techniques to improve 4G LTE networks for the upcoming deployment of 5G in non-autonomous scenarios. The authors of [25] suggest that, in 5G networks, edge device deployment should be optimizedwhile cost and energy usage are kept to a minimum. [PERSON] et al. present a comprehensive technical and economic analysis based on different architecture scenarios to reduce the cost of 5G deployment [26]. However, the report does not address coverage, capacity, or quality of service. Using only mmWave transmissions, the authors of [27] developed a standalone 5G architecture. Recent research [28] looked at how the MNO could plan its 5G network to maximize profitability with the least amount of deployment overhead. The authors of [29] studied the deployment of ultra-dense 5G networks and developed a genetic algorithm with non-dominated sorting to address the cell scheduling problem. In order to accommodate user traffic demand during the ultra-dense deployment phase in the mmWave band, the authors of [30] advocated increasing sectorization and the number of antennas. [PERSON] et al. [31, 32] investigated the installation of an ultra-dense network with various BSs running at frequencies ranging from GHz to GHz. However, the positioning of BSs during the cell planning process in a real-world scenario, as well as the customers' data rate requirements and cell coverage restrictions, were not considered.  
For instance, IoT sensors on the factory floor use the high band for optimum performance, whereas 5G communications that can travel dozens of miles will use the low band. These bands are used to ensure that 5G signals not only travel farther but also pass through objects like glass, sheet metal, and concrete [33].  
The ability to entirely control your own 5G network is one of the main advantages that is frequently overlooked. Organizations that reclaim control of their cellular resources can modify those resources to fulfill specified service-level agreements (SLAs), uptime needs, and business goals when they own their spectrum license, infrastructure, and devices. With 5G, transmission speeds will improve along with network capacity and latency.