Distributed Dynamic Channel Assignment for Sensor Networks in 5G mMTC

Billions of physical devices are expected to be connected to the Internet by 2020, which will eventually lead to massive machine-type-communication (mMTC), a use case of the fifth generation (5G) wireless access technology. In mMTC, wireless sensor networks (WSNs) can be used to support modern applications such as surveillance and monitoring. To meet the role of mMTC in 5G, cognitive radio technology can be integrated with wireless sensors, and WSNs are then called cognitive radio sensor networks (CRSNs). A channel assignment mechanism is needed to choose licensed channels for the radio interfaces of the sensor nodes. A channel assignment mechanism needs to consider the issue of interference because interference among sensor nodes decreases the performance of the CRSN. In this paper, we propose a channel assignment algorithm for multi-radio multi-channel clustered CRSNs. The proposed algorithm models a network of cluster heads as a conflict graph to determine the interfering links and then chooses different channels for these interfering links to minimize the interference. Using the conflict graph, the algorithm selects different channels to maintain minimum interference among the sensor nodes and to ensure network connectivity. Simulation results show that the proposed algorithm has a 30% higher packet delivery ratio, compared to previous channel assignment mechanism. The algorithm shows robustness to the number of available channels and different clustered routing algorithms.