Invention Grant
- Patent Title: Carrier aggregation optimization using machine learning
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Application No.: US18148601Application Date: 2022-12-30
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Publication No.: US11743878B2Publication Date: 2023-08-29
- Inventor: Sharad Shahi , Madhup Chandra , Tom Chin
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: Harrity & Harrity, LLP
- Main IPC: H04W72/04
- IPC: H04W72/04 ; G06N3/04 ; H04W24/02 ; H04W72/0453 ; H04W72/51

Abstract:
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, an apparatus of a user equipment (UE) may determine a set of inputs to a neural network configured to predict radio frequency channel conditions or a user context associated with the UE. In some aspects, the set of inputs includes historical data related to a wireless environment, a communication pattern, or a behavior pattern associated with the UE. The apparatus of the UE may determine, using the neural network and based at least in part on the set of inputs, an optimal number of aggregated carriers to maximize one or more of a power parameter or a performance parameter. The apparatus of the UE may communicate using the optimal number of aggregated carriers. Numerous other aspects are described.
Public/Granted literature
- US20230144151A1 CARRIER AGGREGATION OPTIMIZATION USING MACHINE LEARNING Public/Granted day:2023-05-11
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