With the rapid growth in the telecommunications industry moving towards 5G and beyond (5GB) and the emergence of data-hungry and time-sensitive applications, Mobile Network Operators (MNOs) are faced with a considerable challenge to keep up with these new demands. Cloud radio access network (CRAN) has emerged as a cost-effective architecture that improves 5GB performance. The fronthaul segment of the CRAN necessitates a high-capacity and low-latency connection. Optical technologies presented by Passive Optical Networks (PON) have gained attention as a promising technology to meet the fronthaul challenges. In this paper, we proposed an Integer Linear Program (ILP) that optimizes the total cost of ownership (TCO) for 5G using CRAN architecture under different delay thresholds. We considered the Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) as a fronthaul with different splitting ratios.

Currently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient connections between a large number of remote radio heads (RRHs) in the cell sites and the baseband unit (BBU) pool in the central location, known as the fronthaul, has emerged as a new challenge. Many wired and wireless solutions have been proposed to address this bottleneck. Specifically, optical technologies presented by passive optical networks (PONs) are introduced as the best suitable solution for 5G and beyond network fronthaul due to their properties of providing high capacity and low latency connections. We considered time and wavelength division multiplexed passive optical networks (TWDM-PONs) as a fronthaul for 5G and beyond. Taking that into consideration, in this paper, we propose an integer linear program (ILP) that results in the optimal optical fronthaul deployment while minimizing the total cost of 5G and beyond instances. However, for larger network instances, solving the ILP problem becomes unscalable and time-consuming. To address that, we developed two heuristic-based algorithms (the K-means clustering algorithm and the one based on the genetic algorithm—GA). We evaluated the suitability of our proposed ILP and heuristic algorithms in simulations by utilizing them to plan different network instances (dense and sparse).