Читать книгу The Smart Cyber Ecosystem for Sustainable Development - Группа авторов - Страница 64

Even with centralized control, optimal channel allocation problem in WLANs is difficult to be solved in an acceptable complexity level. Recently, researchers have been trying to leverage ML methods to find solutions in feasible time.

In [61], the authors propose a ML method for assigning channels to WLANs APs. The method is based on passive monitoring of data in each cell. Using ML, it calculates the performance loss due to interfering users and finds the best channels for the cells that minimize interference. The algorithm minimizes airtime usage of interfering links in neighboring cells. Due to the dynamic nature of WLANs, the process is repeated iteratively. The authors of [62] concluded that a central control of APs is needed even if the network is influenced by neighboring unmanaged APs. Their approach results in a self-organizing system for channel allocation in WLANs based on cooperation between APs. The authors show that the proposed system leads to a stable network of high performance.

In [63], the authors use ML techniques to learn implicit performance models from real-world measurements. The techniques do not need to know the details of interacting parameters. The authors used the developed model for channel allocation and power control.