Device-to-Device (D2D) communication constitutes an emerging network paradigm that promises to unlock decisive capacity gains without the need for expensive cellular resources. However, while deployment of this promising enabler technology in 5G-grade mobile networks is currently underway, the complete understanding of feasible use cases and their respective limitations has not yet been provided in literature. Today, employing D2D connectivity both in human-to-human and machine-to-machine scenarios, the attention of research community focuses on security, privacy, and trust. Inspired by this increasing demand, we provide in this paper a comprehensive summary on our live trial of secure cellular-assisted D2D communication technology within the full-featured 3GPP LTE network deployment. Correspondingly, we describe a novel D2D framework capable of delivering secure direct connectivity even if the managing cellular link is temporarily not available (unreliable), so that communicating devices could continue to exchange confidential data in their private coalitions. To this end, our prototype implementation characterizes the practical capabilities of secure D2D communication in dynamic, urban environments suffering from intermittent 3GPP LTE connectivity.

The integration of millimeter wave (mmWave) and low frequency interfaces brings an unique opportunity to unify the communications and positioning technologies in the future wireless heterogeneous networks (HetNets), which offer great potential for efficient handover using location awareness, hence a location-aware handover (LHO). Targeting a self-organized communication system with autonomous vehicles, we conduct and describe an experimental and analytical study on the LHO using a mmWave-enabled robotic platform in a multi-radio environment. Compared to the conventional received signal strength indicator (RSSI)-based handover, the studied LHO not only improves the achievable throughput, but also enhances the wireless link robustness for the industrial Internet-of-things (IIoT)-oriented applications. In terms of acquiring location awareness, a geometry-based positioning (GBP) algorithm is proposed and implemented in both simulation and experiments, where its achievable accuracy is assessed and tested. Based on the performed experiments, the location-related measurements acquired by the robot are not accurate enough for the standalone-GBP algorithm to provide an accurate location awareness to perform a reliable handover. Nevertheless, we demonstrate that by combining the GBP with the dead reckoning, more accurate location awareness becomes achievable, the LHO can therefore be performed in a more optimized manner compared to the conventional RSSI-based handover scheme, and is therefore able to achieve approximately twice as high average throughput in certain scenarios. Our study confirms that the achieved location awareness, if accurate enough, could enable an efficient handover scheme, further enhancing the autonomous features in the HetNets.