On the Antenna Impedance Mismatch over the Radiated Power in IoT Devices

The efficiency of wireless systems critically depends on the ability of antennas to transfer power from the transmitter circuitry into free space. Although maximum power transfer is theoretically achieved under perfect impedance matching, IoT devices rarely meet this condition due to the ever-changing conditions of the surrounding environment. As a result, a portion of the transmitted power is reflected, reducing the effectively radiated power and degrading system performance. In addition to these radiated losses, load mismatch at the power amplifier output can lead to gain degradation, increased power dissipation, and impaired performance of linearization schemes such as digital predistortion. Such an effect is well-known but has never been quantified. The purpose of this paper is to quantify not only the losses arising from reflection due to impedance mismatch but also those associated with the reduction in amplifier gain by considering both antenna- and amplifier-level perspectives. Theoretical calculations of mismatch losses are first developed and analysed. These results are subsequently validated in an idealised environment, followed by experimental demonstrations in realistic device scenarios, where substantial discrepancies with theoretical predictions and controlled measurements are observed. The findings quantitatively separate and superimpose, for the first time in a unified experimental framework, the radiative mismatch losses (antenna and matching network) from the additional power amplifier gain degradation under realistic load conditions. This demonstrates that passive antenna measurements alone significantly underestimate the total radiated power loss in practical IoT devices. The results emphasise the need to account for real-world operating conditions when evaluating mismatch-induced losses and highlight the importance of co-design and adaptive strategies for both antennas and power amplifiers in future wireless and IoT systems.