DRL-based RIS-assisted ISAC Network:Challenges and Opportunities
The Deep Reinforcement Learning(DRL)has received widespread attention,which has potential in Reconfigurable Intelligent Surface(RIS)assisted Integrated Sensing And Communication(ISAC)network.However,due to the high cost of data offloading and model training,the existing RIS-assisted ISAC frameworks still face great challenges.To overcome this problem,the paper analyzes the main technology of DRL in the field of ISAC networks and its solution,which can solve the of high complexity,high-frequency transmission and limited coverage problems.To promote the implementation of these technologies,this paper further discusses the future development trends of DRL technologies in RIS-assisted ISAC networks,including potential applications and problems to be solved.
Deep Reinforcement Learning(DRL)Reconfigurable Intelligent Surface(RIS)Integrated Sensing And Communication(ISAC)
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维普
