A deep reinforcement learning resource allocation strategy for integrated sensing, communication and computing

Lili Cai; Jincan He

doi:10.1016/j.phycom.2024.102349

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JOURNAL ARTICLE

A deep reinforcement learning resource allocation strategy for integrated sensing, communication and computing

Lili Cai Jincan He

Year: 2024 Journal: Physical Communication Vol: 64 Pages: 102349-102349 Publisher: Elsevier BV

DOI: 10.1016/j.phycom.2024.102349

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Keywords:

Computer science Energy consumption Mobile edge computing Distributed computing Latency (audio) Reinforcement learning Edge computing Server Computation offloading Wireless sensor network Enabling Efficient energy use Enhanced Data Rates for GSM Evolution Computer network Artificial intelligence Telecommunications

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Cited By

4.18

FWCI (Field Weighted Citation Impact)

Refs

0.87

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Energy Efficient Wireless Sensor Networks

Physical Sciences → Computer Science → Computer Networks and Communications

Age of Information Optimization

Physical Sciences → Computer Science → Computer Networks and Communications

A deep reinforcement learning resource allocation strategy for integrated sensing, communication and computing

Metrics

Citation History

Topics

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