Timeliness and Secrecy-Aware Uplink Data Aggregation for Large-Scale UAV-IoT Networks

Due to the inherent characteristics of system extensibility and implementation flexibility, unmanned aerial vehicle (UAV)-assisted data aggregations will play an essential role in Internet of Things (IoT) networks, where both communication security and timeliness are of high priority. In this paper, we study uplink data aggregation in cooperative jamming-aided large-scale UAV-IoT networks under the threat of eavesdroppers. By employing stochastic geometry, we derive performance metrics related to the age of information (AoI) and secrecy outage probability (SOP) in a system-level manner, and formulate the combat between legitimate entities (i.e., IoT devices and cooperative jammers) and eavesdroppers as a two-stage Stackelberg game. To solve the formulated game, the backward induction method is utilized to obtain the Stackelberg equilibrium (SE) iteratively. Specifically, we first obtain the minimum detection error probability for the eavesdropper by optimizing its detection threshold using the successive convex approximation (SCA) technique. Subsequently, the minimization of AoI violation probability and SOP for the legitimate entity is achieved using the proposed tighter α branch and bound (T-αBB) method by jointly optimizing the transmit powers of the typical IoT device and cooperative jammers as well as the deployment altitude of the typical UAV. Extensive numerical results demonstrate that the proposed solution converges rapidly, with the timeliness and secrecy metrics decreasing by 25.1%, 33.1%, 35.9%, and 37.6% compared to the benchmark scheme in suburban, urban, dense urban, and high-rise urban environments, respectively.