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Radio Environment Map (REM) is a map that indicates the radio signal strength (RSS) over a finite geographical region. It enables cognitive radio (CR) users to opportunistically access to the spectrum unoccupied by the primary users (PUs) who are licensed to use specific spectrum. In this paper, a basis expansion based scheme is presented to estimate REM. We take the sparsity of preselected basis...
This paper investigates the problem of distributed best linear unbiased estimation (BLUE) of a random parameter at the fusion center (FC) of a wireless sensor network (WSN). In particular, the application of limited-feedback strategies for the optimal power allocation in distributed estimation is studied. In order to find the BLUE estimator of the unknown parameter, the FC combines spatially distributed,...
This paper develops a framework for the estimation of a time-varying random signal using a wireless sensor network. Given a continuous time model, sensors collect noisy observations and produce local estimates according to the discrete-time equivalent system defined by the sampling period of observations. Estimation is performed using a maximum a posteriori probability estimator (MAP) within a given...
We study the use of distributed average consensus and compressed sensing to perform decentralized estimation of a field measured by networked sensors. We examine field reconstruction of multiple acoustic sources from isotropic magnitude measurements. Compressed projections of global network observations are spread throughout the network using consensus, after which all nodes may invert the source...
The recursive least-squares (RLS) algorithm has well-documented merits for reducing complexity and storage requirements, when it comes to online estimation of stationary signals as well as for tracking slowly-varying nonstationary processes. In this paper, a distributed recursive least-squares (D-RLS) algorithm is developed for cooperative estimation using ad hoc wireless sensor networks. Distributed...
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