任务场景驱动的无线通信跨层智能适变方法OA

Traditional wireless communication architectures with hierarchical optimization exhibit limited performance and often lack dedicated designs for specific task scenarios.Consequently,task scenario-driven cross-layer joint optimi-zation has become an inevitable trend.However,it faces challenges such as complex coupling of multi-level parameters,large differences in response times at different levels,and severe conflicts in autonomous decision-making among mul-tiple nodes.Therefore,inspired by the fast conditioned reflex and efficient decision-making of the human brain through deep thinking,a brain-like intelligent cross-layer joint decision-making architecture driven by task scenarios was pro-posed.The key technologies of integrated intelligent adaptation for link-level cross-layer decision-making and efficient cognitive adaptation for multi-node collaboration at the network level were systematically expounded.Some key tech-nologies were verified through specific cross-layer optimization cases.