Task-Oriented Semantics-Aware Communication for Wireless UAV Control and Command Transmission

To guarantee the safety and smooth control of Unmanned Aerial Vehicle (UAV) operation, new command (C&C) data type imposes stringent quality service (QoS) requirements on cellular network. However, existing bit-oriented communication framework is already approaching Shannon capacity limit, which can hardly ultra-reliable low latency communications (URLLC) for C&C transmission. solve problem, task-oriented semantics-aware (TOSA) has been proposed recently by jointly exploiting context its importance to UAV task. best our knowledge, an explicit systematic TOSA emerging remains unknown. Therefore, in this letter, we propose a transmission define value information based both similarity age (AoI) signals. We also deep reinforcement learning (DRL) algorithm maximize information. Last but not least, present simulation results validate effectiveness framework.