Closed-Loop Transmission Power Control for Reliable and Low-Power BLE Communication in Dynamic IoT Settings

TL;DR

This paper introduces a hybrid closed-loop transmission power control framework for BLE in IoT environments, improving reliability and energy efficiency by balancing responsiveness and throughput accuracy under dynamic conditions.

Contribution

It proposes a novel hybrid PID-based control strategy combining RSSI and throughput feedback for robust BLE power management in variable environments.

Findings

Hybrid control maintains stable throughput with minimal variance.

Proposed method outperforms single-strategy controls in dynamic settings.

Effective energy savings achieved through optimized power adjustments.

Abstract

Reliable and energy-efficient Bluetooth Low Energy (BLE) communication is crucial for Internet of Things (IoT) applications in dynamic environments. However, the Received Signal Strength Indicator (RSSI) and data throughput in BLE are highly susceptible to environmental variability, which degrades communication performance. In this work, we systematically analyze the interdependence among RSSI, throughput, transmission power (TXP), and the peripheral device system power consumption under diverse real-world conditions. We observe that adjusting the TXP effectively influences both RSSI and throughput. We propose a robust closed-loop TXP control framework based on Proportional-Integral-Derivative (PID) controllers. Two initial control strategies are investigated: an RSSI-based approach and a throughput-based approach, each exhibiting distinct advantages and limitations. The RSSI-based method provides rapid responsiveness to signal fluctuations but lacks direct correlation with data throughput, whereas the throughput-based method offers more accurate feedback on effective throughput at the cost of slower response. To address these limitations, a hybrid RSSI-throughput control strategy is developed, combining the responsiveness of RSSI feedback with the accuracy of throughput measurements. Experimental results demonstrate that the proposed hybrid approach maintains data throughput close to the target level with minimal variance, even under rapidly changing environmental conditions.