###### Abstract
These PONs have transmission speeds of up to 40 Gbit/s and utilize multi-level communication protocols such as quadrature amplitude modulation (QAM), quadrature phase shift keying (QPSK), and phase shift keying (PSK) to enhance the spectral efficiency. Wavelength division multiplexing (WDM) is also utilized to transmit information through multiple channels, resulting in rigid frequency grids within a spectrum section [3]. Implementing approaches that employ multiple lasers to replicate each frequency of the International Telecommunication Union (ITU) grid has significantly increased network speed and efficiency. However, deploying this technology has proven costly, primarily due to the requirement for multiple lasers and the considerable economic investment that it requires. Additionally, achieving high phase coherence between each laser frequency has posed a significant challenge, thereby restricting the capacity and effectiveness of these approaches [6]. Other researchers have taken a different approach to optimizing the utilization of existing infrastructure without introducing new PON standards [2,7], thereby avoiding network cost escalation. Developers have created dynamic bandwidth allocation (DBA) algorithms to achieve this. Designers have created these algorithms to share network resources by taking advantage of carrier availability when customers do not require an exclusive channel and by making requests at specific times [8,9]. Additionally, some strategies aim to distribute network requests effectively by utilizing heuristics that optimize latency; while these approaches achieve faster response speeds, their networks are rigid and do not permit the utilization of various modulation formats and wavelengths. Alternative methods of achieving dynamic bandwidth allocation involve the utilization of multiple channels enabled by wavelength division multiplexing (WDM) infrastructure and the development of algorithms such as Dynamic Wavelength and Bandwidth Allocation (DWBA) or Routing and Spectrum Assignment (RSA), which leverage the capabilities of WDM technology. Despite their potential to enhance the network efficiency, the significant separation between wavelengths (200 GHz, 100 GHz, and 50 GHz) limits optimal spectrum utilization, particularly for requests that require a low transfer rate--as is the case for Internet of Things (IoT) devices. Additionally, these approaches do not account for the use of different multi-level modulation formats, which could help to reduce the portion of the spectrum needed [10,11]. A few methodologies have been proposed in the literature that employ machine learning and optimization techniques to enhance the spectral efficiency of the WDM approach [12, 13, 14]. This optimization aims to transmit the maximum amount of data in the shortest possible time and achieve spectrum allocation. These approaches have achieved promising results, such as minimizing the required spectrum, predicting future demands, and efficient network management. However, they carry a significant computational cost that impedes their use in real-life scenarios, where processing time and hardware device implementation must be ensured [15,16]. Alternatives employing flexible networking approaches are available, integrating radio frequency infrastructures, wireless systems, and optical networks. This approach is called the Multi-Stratum Resources Optimization with Converged Radio over Fiber and 5G Network (C-RoFN) architecture, and they enable the comprehensive maximization of resources, including radio frequency, optical spectrum, and BBU processing capacity. The primary goal is to enhance the radio coverage and meet quality of service standards; while these methodologies focus on spectrum allocation, they revolve around integrating diverse transmission sources, contrary to spectral allocation within an optical network.