Wireless communication technologies and Internet of Things (IoT) applications are the main drivers of upcoming sustainable Smart City networks which require an effective resource management. The reduction of the transmission energy consumption and the efficient utilization of the available spectrum for wireless communication, for instance, have to be enabled by energy-efficient and cognitive IoT networks. These are implemented through optimized communication protocol stacks and algorithms that rely on actual physical layer and channel state information. The modeling and the prototype evaluation of protocol optimization approaches are mainly driven by pure simulation studies with abstracted physical layer and channel models. With the Radio-in-the-Loop (RIL) simulation [1] and modeling [2], we have created an evaluation approach that integrates real wireless hardware and radio environments into the simulation of protocol sequences and algorithms. In this paper, we demonstrate a cross-layer optimization case study for energy efficient modeling using software-defined radios alongside this basic methodology. We exemplary show the scenario of a receiver-sensitivity control to increase the energy efficiency of receiver-dominated IoT nodes in Smart City networks.