A graph neural network trained with Lagrangian primal-dual updates allocates power across multiple channels per user and reports higher sum rates and much faster inference than an extended WMMSE baseline in simulation.
A joint channel and power al- location scheme for device-to-device communications underlaying uplink cellular networks,
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Graph Neural Networks for Resource Allocation in Multi-Channel Wireless Networks
A graph neural network trained with Lagrangian primal-dual updates allocates power across multiple channels per user and reports higher sum rates and much faster inference than an extended WMMSE baseline in simulation.