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.

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

IPC: H04L25/02 ,  H04L5/00

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.

公开(公告)号：US11929853B2

公开(公告)日：2024-03-12

申请号：US17504341

申请日：2021-10-18

Applicant: QUALCOMM Incorporated

Inventor： Arash Behboodi ,  Simeng Zheng ,  Joseph Binamira Soriaga ,  Max Welling ,  Tribhuvanesh Orekondy

IPC: H04L23/02 ,  H04B17/391 ,  H04L25/02 ,  H04L25/03

CPC classification number: H04L25/0254 ,  H04B17/3912 ,  H04B17/3913 ,  H04L25/03165

Abstract: A method performed by an artificial neural network includes determining a conditional probability distribution representing a channel based on a data set of transmit and receive sequences. The method also includes determining a latent representation of the channel based on the conditional probability distribution. The method further includes performing a channel-based function based on the latent representation.

公开(公告)号：US11696093B2

公开(公告)日：2023-07-04

申请号：US17182153

申请日：2021-02-22

Applicant: QUALCOMM Incorporated

Inventor： Farhad Ghazvinian Zanjani ,  Arash Behboodi ,  Daniel Hendricus Franciscus Dijkman ,  Ilia Karmanov ,  Simone Merlin ,  Max Welling

IPC: H04W4/029

CPC classification number: H04W4/029

Abstract: Certain aspects of the present disclosure provide techniques for object positioning using mixture density networks, comprising: receiving radio frequency (RF) signal data collected in a physical space; generating a feature vector encoding the RF signal data by processing the RF signal data using a first neural network; processing the feature vector using a first mixture model to generate a first encoding tensor indicating a set of moving objects in the physical space, a first location tensor indicating a location of each of the moving objects in the physical space, and a first uncertainty tensor indicating uncertainty of the locations of each of the moving objects in the physical space; and outputting at least one location from the first location tensor.

公开(公告)号：US12200660B2

公开(公告)日：2025-01-14

申请号：US17461927

申请日：2021-08-30

Applicant: QUALCOMM Incorporated

Inventor： Arash Behboodi ,  Farhad Ghazvinian Zanjani ,  Joseph Binamira Soriaga ,  Lorenzo Ferrari ,  Rana Ali Amjad ,  Max Welling ,  Taesang Yoo

IPC: H04W4/00 ,  G06N20/00 ,  H04B7/06 ,  H04B7/08 ,  H04W64/00

Abstract: A method of training an artificial neural network (ANN), receives, from a base station, signal information for a radio frequency signal between the base station and a user equipment (UE). The artificial neural network is trained to determine a location of the UE and to map the environment based on the received signal information and in the absence of labeled data.

公开(公告)号：US12199705B2

公开(公告)日：2025-01-14

申请号：US18155454

申请日：2023-01-17

Applicant: QUALCOMM Incorporated

Inventor： Markus Peschl ,  Daniel Ernest Worrall ,  Arash Behboodi ,  Roberto Bondesan ,  Pouriya Sadeghi ,  Sanaz Barghi

IPC: H04B7/0456 ,  H04B7/06 ,  H04B17/336

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for demapping a signal to a point in a signal constellation. An example method generally includes identifying a seed point in a signal constellation from a received signal. A candidate set of codes for the signal is generated based on a seed point and an additive perturbation applied to the seed point. A point in the signal constellation corresponding to the value of the received signal is identified based on a probability distribution generated over the candidate set of codes. Generally, the identified point corresponds to a code in the candidate set of codes having a highest probability in the probability distribution. The point in the signal constellation is output as the value of the received signal.

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

IPC: H04L25/02 ,  H04L25/03

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.