Recent advances in wireless technologies have paved the way for convergence in wireless communications, sensing, imaging, and localization applications, giving rise to breakthrough applications across multiple industries. However, the resulting "ubiquitous wireless intelligence" raises security, privacy, environmental, and health concerns. It is time to address ethical matters in wireless communication and sensing, a topic not less important than ethical AI. From a communications engineering perspective, we aim to establish a unified ethical framework, primarily at the physical layer of wireless systems.
Methods and Technologies
Investigate signal processing and machine learning techniques for extracting user and device location information and molecular composition data, among other sensory information, from wireless signals.
Propose methods that enhance physical-layer privacy and security by analyzing radio-frequency signal fingerprints in time, frequency, and spatial domains, especially in high-frequency systems.
Investigate methods for extracting sensory information from data packets aggregated at the network layer.
Study the performance and complexity tradeoffs in a privacy-preserving joint communications, sensing, and localization framework.
Derive information-theoretic bounds on the achievable data rates and sensing accuracy.
Design circuits that realize the proposed algorithms efficiently in hardware.
Conduct studies that examine the impact of high-frequency wireless signals on health; propose mitigation techniques from an engineering perspective (waveform design).
