AoI and Energy-Aware Data Collection for IRS-Assisted UAV-IoT Networks Under Jamming

With the rapid popularity of autonomous aerial vehicles (AAV)-Internet of Things (IoT) networks, timely and energy-efficient data collection is a critical issue. The strong Line-of-Sight (LoS) communication of UAVs makes them more susceptible to jamming attacks, resulting in increased communication latency and energy consumption (EC). In this article, the problem of jointly minimizing Age of Information (AoI) and EC in data collection under malicious jamming attacks is formulated by optimizing the diagonal phase shift matrix of the intelligent reflective surface (IRS), UAV trajectory, and the transmit powers of IoT devices. The formulated problem is solved by an alternating optimization (AO) scheme. Specifically, we first obtain the closed-form solution of the IRS diagonal phase shift matrix by using the quantitative passive beamforming method. Then, the UAV trajectory is optimized by the variable parameter particle swarm annealing (VPPSA) algorithm, and the suboptimal solution of the transmit powers of IoT devices is obtained by the successive convex approximation (SCA) algorithm. Extensive simulation results demonstrate that the proposed algorithm outperforms the benchmark schemes in terms of AoI and EC.