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公开(公告)号:US20240113917A1
公开(公告)日:2024-04-04
申请号:US17952203
申请日:2022-09-23
Applicant: QUALCOMM Incorporated
Inventor: Kumar Pratik , Arash Behboodi , Pouriya Sadeghi , Tharun Adithya Srikrishnan , Alexandre Pierrot , Joseph Binamira Soriaga , Supratik Bhattacharjee
CPC classification number: H04L25/0224 , H04L5/0051
Abstract: Methods, systems, and devices for wireless communications are described. A wireless device may receive an assignment of a set of resources associated with a channel where the set of resources includes a first subset of resources allocated for data transmission and a second subset of resources allocated for a reference signal. The wireless device may generate multiple channel estimations per layer of the channel and perform a refinement operation utilizing the estimations to generate a channel estimation associated with multiple layers. Each iteration of the refinement operation may include generating respective gradients associated with each per layer channel estimation; generating a current set of values of a latent variable; and modifying the channel estimations.
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公开(公告)号:US11616666B2
公开(公告)日:2023-03-28
申请号:US17349744
申请日:2021-06-16
Applicant: QUALCOMM Incorporated
Inventor: Rana Ali Amjad , Kumar Pratik , Max Welling , Arash Behboodi , Joseph Binamira Soriaga
Abstract: A method performed by a communication device includes generating an initial channel estimate of a channel for a current time step with a Kalman filter based on a first signal received at the communication device. The method also includes inferring, with a neural network, a residual of the initial channel estimate of the current time step. The method further includes updating the initial channel estimate of the current time step based on the residual.
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公开(公告)号:US11700070B2
公开(公告)日:2023-07-11
申请号:US17734524
申请日:2022-05-02
Applicant: QUALCOMM Incorporated
Inventor: Kumar Pratik , Arash Behboodi , Joseph Binamira Soriaga , Max Welling
IPC: H04B17/373 , H04B17/391
CPC classification number: H04B17/373 , H04B17/3913
Abstract: A processor-implemented method is presented. The method includes receiving an input sequence comprising a group of channel dynamics observations for a wireless communication channel. Each channel dynamics observation may correspond to a timing of a group of timings. The method also includes determining, via a recurrent neural network (RNN), a residual at each of the group of timings based on the group of channel dynamics observations. The method further includes updating Kalman filter (KF) parameters based on the residual and estimating, via the KF, a channel state based on the updated KF parameters.
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