Distributed energy-efficient channel assignment in cognitive mesh network for IoT systems

Internet of Things (IoT) has attracted a lot of attention to solve the real-world problem to improve quality of life. Cognitive radio mesh networks (CRMNs) can provide connectivity to a large number of IoT nodes and have the potential to self-organize and reconfigure to make efficient use of spectrum resources. The growing concern regarding energy consumption in communication infrastructure and low power IoT nodes has led researchers to regard minimizing of energy consumption. In this paper, we propose a distributed energy-efficient channel assignment in CRMNs for the IoT systems. We formulate an optimization problem for channel assignment and sharing in CRMNs for IoT systems with an objective to maximize energy-efficiency of the network. We consider constraints on both intra and inter-link interference. We then propose two distributed approaches to solve the channel assignment problem: (1) greedy approach and (2) game theoretic approach while considering the scalability and self-organization requirements of the CRMNs for the IoT systems. We then present extensive simulation results to demonstrate the performance of proposed schemes.