2007/07/05 by Alessandro Nordio, A. Nordio, Carla Fabiana Chiasserini +3 · 47 citations
Computer Science · Engineering · Mathematics · #Algorithm #Artificial intelligence #Bandlimiting #Computer science #Distributed Sensor Networks and Detection Algorithms #Engineering #Fourier transform #Harmonics #Mathematical analysis #Mathematical optimization #Mathematics #Mean squared error #Microwave Imaging and Scattering Analysis #Noise (video) #Statistics #Target Tracking and Data Fusion in Sensor Networks #Wireless sensor network #cs.OH
paper · pdf · doi:10.1109/tsp.2008.924865
published in IEEE Transactions on Signal Processing 56(8), 3535-3547 (Institute of Electrical and Electronics Engineers)
arxiv created 2007/07/05 · openalex publication_date 2008/07/24 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We consider a wireless sensor network, sampling a bandlimited field, described by a limited number of harmonics. Sensor nodes are irregularly deployed over the area of interest or subject to random displacement; in addition sensors measurements are affected by noise. Our goal is to obtain a high quality reconstruction of the field, with the mean square error (MSE) of the estimate as performance metric. In particular, we analytically derive the performance of several reconstruction/estimation techniques based on linear filtering. For each technique, we obtain the MSE, as well as its asymptotic expression in the case where the number of field-harmonics and the number of sensors grow to infinity, while their ratio is kept constant. Through numerical simulations, we show the validity of the asymptotic analysis, even for a small number of sensors. We provide some novel guidelines for the design of sensor networks when many parameters, such as field bandwidth, number of sensors, reconstruction quality, and sensor displacement characteristics, to be traded off.