An Energy-Efficient Internet of Things Framework for Heterogeneous Small Cell Networks PROJECT TITLE : An Energy-Efficient Framework for Internet of Things Underlaying Heterogeneous Small Cell Networks ABSTRACT: It has been found that heterogeneous networks that support Long-Term Evolution Advanced (LTE-A) can provide Communication that is both reliable and service-differentiated. This opens the door for a wide variety of mobile applications, including smart meters, remote sensors, and vehicular applications. A future in which heterogeneous small cell networks are underpinned by the Internet of Things (IoT) could look something like this. This paper proposes an energy-efficient framework for such a scenario, where multitier heterogeneous small cell networks provide wireless connections and seamless coverage for mobile users and IoT nodes. This framework is based on the premise that this scenario will occur. In the framework that we have proposed, an elastic cell-zooming algorithm that is based on the quality of service and traffic loads of end-users is carried out. This algorithm is carried out by adaptively adjusting the transmission power of small cells in order to reduce the amount of energy that is consumed. In addition, in order to achieve the high energy efficiency of IoT underpinning small cell networks, a clustering-based IoT structure is used. In this structure, a SWIPT-CH selection algorithm is proposed in order to maximize the average residual energy of IoT nodes and to mitigate resource competition between IoT nodes and mobile users. This algorithm aims to maximize the amount of energy that is left over from IoT nodes. Extensive simulations show that our proposed framework has the potential to significantly improve the energy efficiency of Internet of Things (IoT) underlaying small cell networks while maintaining a guaranteed outage probability. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest App Popularity Prediction Using Time-Varying Hierarchical Interactions A Photo Crowdsourcing Framework Based on Edge Computing for Real-Time 3D Reconstruction