State-Augmented Learnable Algorithms for Resource Management in Wireless Networks
Author:
Affiliation:
1. Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
2. Intel Labs, Intel Corporation, Hillsboro, OR, USA
Funder
ARL DCIST CRA
NSF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://ieeexplore.ieee.org/ielam/78/9675017/9991085-aam.pdf
Reference46 articles.
1. Intelligent O-RAN for beyond 5G and 6G wireless networks;niknam,2020
2. Gaussian Interference Networks: Sum Capacity in the Low-Interference Regime and New Outer Bounds on the Capacity Region
3. Resource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning
4. Ergodic Stochastic Optimization Algorithms for Wireless Communication and Networking
5. Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications
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