Card-flipping decision-making technique for handover skipping and access point assignment: a novel approach for hybrid lifi networks - Murad, Sallar S.; Yussof, Salman; Hashim, Wahidah; Badeel, Rozin (Institute of Electrical and Electronics Engineers, 2024)
The hybrid LiFi/WiFi communication networks have demonstrated their efficacy and advantages in terms of data transmission rates and robust security. Multiple difficulties were identified in these networks, including the access point assignment (APA) and the process of handover (HO). These troubles are influenced by multiple elements, including optical gain at the recipient, mobility, distance, blockage, shadowing, and other variables. These elements can be regarded as criteria, and it is crucial to only evaluate many criteria when making decisions in order to attain more precise results, despite the complexity involved. Various studies have recently put forth diverse approaches for APA and HO. However, the majority of these studies involve multiple phases and steps in the decision-making process. Furthermore, as far, only a single study employing the multicriteria decision-making (MCDM) technique for a hybrid LiFi/WiFi network has been discovered. Nevertheless, although the MCDM technique is highly accurate, it involves multiple phases and processes to achieve the optimal access point (AP). This results in heightened intricacy of the system, leading to longer AP transfer times and higher HO rates. In order to address the aforementioned constraints, this paper introduces a novel approach known as card-flipping decision making (CFDM). CFDM enables swift and precise decision-making while minimizing computational complexity. Additionally, it incorporates HO rates that involve bypassing HOs and selecting the most optimal AP. The analytic hierarchy process (AHP) is adopted to estimate the subjective weights of each criterion and establish their level of priority based on expert judgment. The method provided in this study is combined with the AHP steps and outcomes. As a result, the proposed work is referred to as the merged AHP-CFDM. The determination of weights in the AHP included conducting numerous investigations, such as evaluating the consistency ratio (CR) and calculating the AHP consensus indicator using the rank-based maximum likelihood method (RGMM) and Shannon entropy techniques. The investigation demonstrates improvements in total system efficiency in terms of computational complexity and HO rates when compared to both standard approaches and benchmark techniques. The simulation results demonstrate that the proposed strategy outperforms other methods significantly when compared to the most relevant studies.