Knapsack-based energy-efficient node selection scheme for cooperative spectrum sensing in cognitive radio sensor networks

A cognitive radio (CR) is the most promising candidate for the successful deployment of dynamic spectrum access (DSA). To embed DSA in a wireless sensor network, a CR is required to be installed on each sensor node. Such a sensor network is known as a cognitive radio sensor network (CRSN). Spectrum sensing is a prerequisite for a CR. Therefore every node in the CRSN consumes energy for spectrum sensing. To achieve a high-sensing accuracy, the nodes share sensing results among themselves, which is known as cooperative spectrum sensing (CSS). CSS improves sensing; however it increases energy consumption and shortens the lifetime of the network. As a CRSN is characterised as an energy constraint network, to prolong the lifetime of the network, the number of cooperating nodes should be minimum. This study presents a user selection scheme to minimise the overhead energy consumed by CSS in a CRSN. On the basis of the binary knapsack problem and its dynamic programming solution, the proposed technique selects the best nodes among the potential nodes subject to the energy constraint of the CRSN. The simulation results indicate the advantages of employing the proposed method, depending on the desired performance-energy consumption tradeoff.