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Spectrum resources management of growing demands is a challenging problem andCognitive Radio (CR) known to be capable of improving the spectrum utilization.Recently, Power Spectral Density (PSD) map is defined to enable the CR to reusethe frequency resources regarding to the area. For this reason, the sensed PSDsare collected by the distributed sensors in the area and fused by a FusionCenter (FC). But, for a given zone, the sensed PSDs by neighbor CR sensors maycontain a shared common component for a while. This component can be exploitedin the theory of the Distributed Source Coding (DSC) to make the sensorstransmission data more compressed. However, uncertain channel fading and randomshadowing would lead to varying signal strength at different CRs, even placedclose to each other. Hence, existence of some perturbations in the transmissionprocedure yields to some imperfection in the reporting channel and as a resultit degrades the performance remarkably. The main focus of this paper is to beable to reconstruct the PSDs of sensors \textit{robustly} based on theDistributed Compressive Sensing (DCS) when the data transmission is slightlyimperfect. Simulation results verify the robustness of the proposed scheme.

A Compressive Method for Centralized PSD Map Construction with Imperfect Reporting Channel