Semantic Communication for Cooperative Multi-Task Processing over Wireless Networks

The same authors in [9] studied distributed relevant Applications involving machine-to-machine or human-tomachine information encoding for collaborative feature extraction to communications often have to prioritize task execution fulfill a task, leveraging distributed IB. Moreover, [10] offered over the exact reconstruction of transmitted information a framework for collaborative retrieval of the message using at the receiver. Unlike the traditional information multiple received semantic information and also expanded it theory established by Shannon, which emphasizes the accurate using reinforcement learning in [11]. To consider some physical transmission and reception of bits, the design of communication layer communication aspects, [12] contributed to resource systems for these applications takes a distinct approach, allocation in a multi-user system according to the single task drawing attention to task performance rather than fidelity in accuracy, channel conditions, and computing requests.