Exploring impacts of age of information on data accuracy for wireless sensing systems: an information entropy perspective

Wireless sensing systems have been employed in the field of healthcare, environment monitoring, and smart agriculture, etc. Since the freshness and accuracy indicators of the sensing data are critical to wireless sensing systems, it is of great significance to ensure their performances simultaneously, i.e., the Age of Information (AoI) and information entropy of the sensing data should be jointly optimized. In this regard, we first establish the wireless sensing system models, including AoI and information entropy expressions. Next, from the information entropy viewpoint, we theoretically analyze an impact of the AoI on data accuracy. Then, we formulate the joint optimization problem of AoI, information entropy, and sensing energy consumption. Furthermore, we propose two numerical algorithms to solve the formulated problem in the known or unknown transmission environment, respectively. Finally, we evaluate the correctness and effectiveness of our proposals under various parameter settings, where the proposed scheme can obtain a better sum-weighted performance on AoI, information entropy, and sensing energy consumption than baselines in the literature.