Energy efficient cooperative CRN spectrum sharing using multi-level hierarchical clustering with MCDM

Abstract

Spectrum sensing is playing a vital role in cognitive radio networks (CRN). In cooperative sensing model, energy, task assignment and free channel allocation for requested CRs mostly varies based on location of CR from cluster head. Since heterogeneous CR users are participating in the cooperation, their willingness, battery power and sensing accuracy are to be considered for CR's weight calculation. Otherwise overall sensing results trustworthiness and performance of sensing task may be degraded. Using multi criteria decision making (MCDM) scheme we have calculated each node weight and given that as input to multi-level hierarchical clustering technique. Based on the traffic of each blocks, sensing task will be allocated to a cluster. In MCDM, we derived the weight by using combination of modified analytical hierarchical process (MAHP) for giving weight for attributes of each CR and VIKOR. Final result shows that increased average lifetime of each participating nodes in the simulation.