Analytical Framework for Throughput Enhancement in BLE Extended Advertising With Packet Chaining

Bluetooth Low Energy (BLE) 5.x introduced extended advertising with packet chaining for high-throughput BLE-based IoT applications. However, achieving maximal throughput in BLE largely depends on the selection of transmission parameters, such as packet size and the number of chained packets. Therefore, determining the optimal packet size and the number of chained packets is crucial. However, this task is challenging due to the nonlinearity of the problem. To date, none of the existing works have focused on determining the optimal values for these parameters. To address the aforementioned bottlenecks, we first develop a comprehensive analytical framework to model throughput. Based on this framework, we derive simplified closed-form analytical expressions to choose the transmission parameters optimally, ensuring maximal throughput. Additionally, we develop an algorithm that autonomously optimizes transmission parameters based on network configuration. Analytical results demonstrate that the proposed framework significantly improves throughput compared to conventional approaches. The accuracy of our analytical model is validated through simulations, demonstrating strong agreement with the analytical results.