Energy Consumption Forecasting and Network Optimisation for IoT Deployments over Wi-Fi HaLow

This thesis investigates how Wi-Fi HaLow devices consume energy when using the Target Wake Time (TWT) mechanism. It develops an energy forecasting model based on direct measurements from commercial Wi-Fi HaLow hardware and identifies configurations that minimise energy use. The research combines experimental measurements with analytical modelling to capture energy consumption across different operational phases, including wake-up, transmission, and sleep. The validated model provides practical guidance for configuring Wi-Fi HaLow networks to extend battery life, supporting more reliable and cost-effective IoT deployments in energy-constrained environments.