Clustering in Cooperative Cognitive Radio Networks Based on Mobility Aware Hybridized Algorithm for Optimization

Abstract

The resource allocation provides an effective role which is primarily affected by power transmission, density of the users and also the mobility of the users. Many methods have been followed by the researchers in CCRNs yet it does not include the issues in mobility with spectrum sensing. This movement of spectrum users increases the complexity of network. In this paper, optimal cluster based spectrum sensing and resource allocation (OCSR) is investigated. Mobility grid resource allocation (MGRA) scheme is proposed using hybridized optimization based algorithm. This includes the following algorithms for optimization, which includes Optimization at Balanced Loaded Condition (OBLC) for optimal cluster formation strategy. The multiple state metrics includes process of multi-dolphin echolocation algorithm (MDEA), which computes multiple requests from secondary users. Throughput is enhanced by mobility enhanced gravitational search algorithm (MGSA). The first contribution of OCSR is usage of equilibrium whale optimization (EWO). Clustering process includes channels division into occupied sub-band and normal subband set, where the detection performance is increased. The proposed method for OCSR is the isolated K-best detectors. The detection probability of the proposed scheme is 95%. Simulation results provide increase in energy, efficiency, system with throughput and increased lifetime.