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Neural networks

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LastUpdate Updated on 03/04/2026 [07:45:00]
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METHOD AND BASE STATION FOR RESOURCE ALLOCATION IN DYNAMIC WIRELESS ENVIRONMENT WITH CONTINUAL-LEARNING

Nº publicación: WO2026046493A1 05/03/2026

Applicant:

HUAWEI TECH CO LTD [CN]
CHOUAYAKH AYMAN [DE]
HUAWEI TECHNOLOGIES CO., LTD,
CHOUAYAKH, Ayman

WO_2026046493_A1

Absstract of: WO2026046493A1

A method for a base station associated with one or more terminal devices comprising determining an initial state at a first time, a resource allocation for the one or more terminal devices associated with the base station based on a Deep Neural Network (DNN) policy, causing the resource allocation to be executed, determining a resulting state at a second time preceding the execution of the resource allocation, a local reward for the base station, and local importance values for a current transition and historical transitions. Further, receiving neighbouring importance values for a current transition and historical transitions of a neighbouring base station, determining global importance values based on the local importance values and neighbouring importance values. Determining which transition of a current transition and historical transitions has the lowest global importance value and drop it to store the remaining transitions. Receiving neighbouring rewards for previous transitions and training the DNN policy based on previous transitions and the received neighbouring rewards.

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