2020/05/23 by Xu Zhang, Marcos M. Vasconcelos, Zhang, Xu +5
Computer Science · #Distributed Control Multi-Agent Systems #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2005.11438
openalex publication_date 2020/05/23 · openalex created_date 2020/05/29 · openalex updated_date 2026/08/01
The emergence of the Internet-of-Things and cyber-physical systems necessitates the coordination of access to limited communication resources in an autonomous and distributed fashion. Herein, the optimal design of a wireless sensing system with n sensors communicating with a fusion center via a collision channel of limited capacity k (k < n) is considered. In particular, it is shown that the problem of minimizing the mean-squared error subject to a threshold-based strategy at the transmitters is quasi-convex. As such, low complexity, numerical optimization methods can be applied. When coordination among sensors is not possible, the performance of the optimal threshold strategy is close to that of a centralized lower bound. The loss due to decentralization is thoroughly characterized. Local communication among sensors (using a sparsely connected graph), enables the on-line learning of unknown parameters of the statistical model. These learned parameters are employed to compute the desired thresholds locally and autonomously. Consensus-based strategies are investigated and analyzed for parameter estimation. One strategy approaches the performance of the decentralized approach with fast convergence and a second strategy approaches the performance of the centralized approach, albeit with slower convergence. A hybrid scheme that combines the best of both approaches is proposed offering a fast convergence and excellent convergent performance.