Privacy-Preserving Distributed Estimation With Limited Data Rate

• 成果类型: Article
• 署名作者: Ke, Jieming; Wang, Jimin; Zhang, Ji-Feng
• 署名单位: Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; University of Science & Technology Beijing; Zhongyuan University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2026.3660110
• 发表日期: 2026
• 关键词: DIFFUSION STRATEGIES; Parameter Estimation; Fisher Information; convergence rate; networks; noise

摘要

This article focuses on the privacy-preserving distributed estimation problem with a limited data rate, where the observations are the sensitive information. Specifically, a binary-valued quantizer-based privacy-preserving distributed estimation algorithm is developed, which improves the algorithm's privacy-preserving capability and simultaneously reduces the communication costs. The algorithm's privacy-preserving capability, measured by the Fisher information matrix, is dynamically enhanced over time. Notably, the Fisher information matrix of the output signals with respect to the sensitive information converges to zero at a polynomial rate, and the improvement in privacy brought by the quantizers is quantitatively characterized as a multiplicative effect. Regarding the communication costs, each sensor transmits only 1 bit of information to its neighbors at each time step. In addition, the assumption on the negligible quantization error for real-valued messages is not required. While achieving the requirements of privacy preservation and reducing communication costs, the algorithm ensures that its estimates converge almost surely to the true value of the unknown parameter by establishing a co-design guideline for the time-varying privacy noises and step sizes. A polynomial almost sure convergence rate is obtained, and then, the tradeoff between privacy and convergence rate is established. Numerical examples demonstrate the main results.