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Einblick - Resource Allocation Optimization
Energy-Efficient Resource Allocation in RIS-aided Cell-Free Massive MIMO Systems Using Multi-Agent Reinforcement Learning
This paper proposes a novel multi-agent reinforcement learning (MARL) framework to optimize energy efficiency in RIS-aided cell-free massive MIMO systems by jointly addressing access point selection, precoding, and RIS beamforming.
Energy Efficient Design of Active STAR-RIS-Aided SWIPT Systems
Optimizing energy efficiency in SWIPT systems using active STAR-RIS technology.
Improved Methods of Task Assignment and Resource Allocation with Preemption in Edge Computing Systems
Edge computing resource allocation methods are improved through a distributed approach with preemption, enhancing system-wide performance by 20-25%.
Task Graph Offloading via Deep Reinforcement Learning in Mobile Edge Computing
Optimizing resource allocation in mobile edge computing through deep reinforcement learning for efficient task graph offloading.
Efficient Resource Allocation at mmWave/THz Frequencies with Cooperative Rate-Splitting
Proposing algorithms for energy-efficient communication in high-frequency systems through cooperative rate-splitting.
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