Designing Efficient Indoor WiFi Mesh Networks: A Layered Approach to Performance Optimization : Evaluating WiFi Mesh Node Performance for Practical IoT Deployments in Dense Indoor Environments

This thesis presents the design, evaluation, and optimization of a robust, efficient, and scalable WiFi-based wireless mesh network specifically developed for dense indoor smart building deployments. Conducted in collaboration with Devward AB, a Swedish IoT company specializing in intelligent building solutions, this research addresses essential requirements, such as guaranteeing a minimum throughput, operating in unlicensed frequency bands, leveraging sub-GHz frequencies for enhanced indoor coverage, prioritizing energy efficiency, and achieving scalability. An extensive review of existing technologies, including WiFi HaLow (IEEE 802.11ah) and WiFi mesh networks (IEEE 802.11s), identifies the most appropriate communication standards. MATLAB-based simulations then evaluate these technologies in combination with the Hybrid Wireless Mesh Protocol (HWMP) and Better Approach To Mobile Ad hoc Networking (BATMAN) routing protocols under realistic indoor scenarios. Our results indicate that while both routing protocols fulfill the defined throughput and reliability criteria, BATMAN consistently provides superior adaptability, scalability, and resilience in dynamic and high-density environments compared to HWMP. Our study also highlights strategic channel allocation to minimize interference and improve overall network reliability. These findings offer critical insights and serve as a robust foundation for future development and practical implementation of IoT-based indoor wireless communication systems.