Radio access network control with deep reinforcement learning

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United States of America Patent

PATENT NO 11494649
APP PUB NO 20210241090A1
SERIAL NO

16778031

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Abstract

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A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

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Patent Owner(s)

Patent OwnerAddress
AT&T INTELLECTUAL PROPERTY I L P754 PEACHTREE STREET NE SUITE 7C ATLANTA GA 30308

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chen, Jie Watchung, US 1059 5911
Chen, Yu Pittsburgh, US 837 9647
Krishnamurthi, Ganesh Danville, US 13 280
Wang, Huahui Bridgewater, US 39 98
Yang, Huijing Princeton, US 10 25
Zhao, Wenjie Princeton, US 77 463

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