Adaptive random sensor selection for field reconstruction in wireless sensor networks
Proceedings of the Sixth International Workshop on Data Management for Sensor Networks
Asymptotic behavior of random vandermonde matrices with entries on the unit circle
IEEE Transactions on Information Theory
The impact of quasi-equally spaced sensor topologies on signal reconstruction
ACM Transactions on Sensor Networks (TOSN)
Signal reconstruction errors in jittered sampling
IEEE Transactions on Signal Processing
Signal reconstruction in sensor networks with flat and clustered topologies
Computer Networks: The International Journal of Computer and Telecommunications Networking
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Asymptotic analysis of multidimensional jittered sampling
IEEE Transactions on Signal Processing
Channel estimation in wireless OFDM systems with irregular pilot distribution
IEEE Transactions on Signal Processing
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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.