Cooperative Wideband Spectrum Sensing for the Centralized Cognitive Radio Network

TL;DR

This paper introduces a novel cooperative wideband spectrum sensing method for centralized cognitive radio networks, leveraging prior occupancy features with modified compressed sensing algorithms to improve detection performance.

Contribution

It proposes the first use of all four occupancy features as prior knowledge in compressed sensing-based cooperative spectrum sensing, with modified algorithms demonstrating enhanced performance.

Findings

Modified algorithms outperform original OMP/SOMP

Prior knowledge improves spectrum sensing accuracy

Enhanced detection in centralized CRNs

Abstract

Various primary user (PU) radios have been allocated into fixed frequency bands in the whole spectrum. A cognitive radio network (CRN) should be able to perform the wideband spectrum sensing (WSS) to detect temporarily unoccupied frequency bands. We summarize four occupancy features for the frequency bands. 1. The occupancy is sparse; 2. The frequency band allocation information is fixed and common; 3. There are three categories for the frequency band usages; 4. The occupied frequency bands are common in the CRN. For the first time, we consider all features as the prior knowledge in the compressed sensing based cooperative WSS (CWSS) algorithm design for a centralized CRN. We propose a modified orthogonal matching pursuit (Mod-OMP) algorithm and a modified simultaneous orthogonal matching pursuit (Mod-SOMP) algorithm for the CWSS. We compare the CWSS performance of Mod-OMP/Mod-SOMP with the original OMP/SOMP and show the performance improvements.