Team Deep Neural Networks for Interference Channels

44 citations recorded by the source corpus.

How researchers see this paper

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Deep Learning for Distributed Optimization: Applications to Wireless Resource Management (2019, methodology): “An on-off power control problem in the IFC is addressed with individual transmitters equipped with their own DNN for the distributed computation in [9].”
Learning Optimal Resource Allocations in Wireless Systems (2018, background): “that has been taken in several unconstrained problems in wireless optimization [24]–[27].”
Optimal Wireless Resource Allocation With Random Edge Graph Neural Networks (2019, methodology): “That is, by treating the resource allocation problem itself as a form of statistical regression, we obtain a means of training policies that solve the optimal allocation problem directly rather than via a training set [14]–[19].”
Learning to Rest: A Q-Learning Approach to Flying Base Station Trajectory Design with Landing Spots (2018, methodology): “We use additive white Gaussian noise model [7] for the distributed CGI in the simulation.”
Learning to Cooperate in Decentralized Wireless Networks (2018, methodology): “We use additive white Gaussian noise model [7] for the distributed CGI in the simulation.”
Robust Decentralized Joint Precoding using Team Deep Neural Network (2018, methodology): “In contrast, we apply to the problem of decentralized joint precoding the idea of Team DNNs introduced in [11] for decentralized scheduling.”