Energy-efficient data collection in UAV-assisted semantic awareness IoT network

Semantic communication shows great potential in reducing data redundancy and improving data collection efficiency in the Internet of Things (IoT) networks. However, IoT devices have limited energy storage capacity, so it is not possible to transmit semantic information to cloud center all the time. To this end, we propose an energy-efficient uploading mechanism in the UAV-assisted semantic awareness data collection system. Specially, we minimize the maximum energy consumption of IoT devices via jointly optimizing user scheduling and UAV trajectory. Since the formulated optimization problem is non-convex, we propose an efficient iterative algorithm to obtain a feasible solution. As the number of iterations increases, the user min- max energy consumption gradually converges to a steady state. Simulation results show that the proposed algorithm has good convergence. In addition, the simulation results of our proposed scheme show that the system performance is greatly improved compared with the conventional bit information transmission and non-optimization schemes.