TWO STAGE MACHINE LEARNING BASED CHANNEL STATE FEEDBACK

    公开(公告)号:US20240421875A1

    公开(公告)日:2024-12-19

    申请号:US18335726

    申请日:2023-06-15

    Abstract: Methods, systems, and devices for wireless communication are described. A user equipment (UE) may select a non-Discrete Fourier Transform (non-DFT) codebook of a set of non-DFT codebooks associated with a channel state feedback message. The UE may determine a set of singular vectors associated with the non-DFT codebook based on a first machine learning model, where the set of singular vectors corresponds to a subspace associated with the non-DFT codebook. The UE may compress the non-DFT codebook, the set of singular vectors, or both, based on a second machine learning model. The UE may transmit the channel state feedback message including the compressed non-DFT codebook, the compressed set of singular vectors, or both.

    DISTORTION PROBING REFERENCE SIGNAL CONFIGURATION

    公开(公告)号:US20230246775A1

    公开(公告)日:2023-08-03

    申请号:US18194479

    申请日:2023-03-31

    CPC classification number: H04L5/0048 H04B17/309

    Abstract: Methods, systems, and devices for wireless communications are described. A configuration for a reference signal used to determine a non-linear behavior of transmission components at a transmitting device may be determined. The configuration for the reference signal may be determined based on signaling transmitted by the transmitting device, signaling transmitted by a device that receives the reference signal, or both. Additionally, or alternatively, the configuration for the reference signal may be determined based on a configuration of other signals transmitted by the transmitting device prior to or concurrently with the transmission of the reference signal. The determined configuration may be used to generate and transmit the reference signal or to determine a configuration of a received reference signal. In both cases, a non-linear response of transmission components at the transmitting device may be determined based on the reference signal.

    GENERALIZED NEURAL NETWORK ARCHITECTURES BASED ON FREQUENCY AND/OR TIME DIVISION

    公开(公告)号:US20230007530A1

    公开(公告)日:2023-01-05

    申请号:US17365510

    申请日:2021-07-01

    Abstract: Certain aspects of the present disclosure provide techniques for measurement encoding and decoding using neural networks to compress and decompress measurement data. One example method generally includes: generating, via each of a plurality of neural network encoders operating on measurement data, a compressed measurement based on a respective portion of the measurement data, wherein each of the neural network encoders is based on the same neural network model; generating at least one message indicative of the measurement data based on the compressed measurements; and transmitting the at least one message.

    ARCHITECTURES FOR TEMPORAL PROCESSING ASSOCIATED WITH WIRELESS TRANSMISSION OF ENCODED DATA

    公开(公告)号:US20220284267A1

    公开(公告)日:2022-09-08

    申请号:US17193974

    申请日:2021-03-05

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitting wireless communication device may encode a data set using a single shot encoding operation and a temporal processing operation associated with at least one neural network to produce an encoded data set, wherein a dimensionality of a subset of inputs of a set of inputs to the temporal processing operation is greater than a dimensionality of the encoded data set. The transmitting wireless communication device may transmit the encoded data set to a receiving wireless communication device. Numerous other aspects are described.

    Managing Information Transmission For Wireless Communication

    公开(公告)号:US20210264254A1

    公开(公告)日:2021-08-26

    申请号:US16911713

    申请日:2020-06-25

    Abstract: Embodiments include methods for managing information transmission between a base station and a wireless device. A base station may apply an encoder neural network to assistance information that may aid a wireless device in communicating with the base station to generate encoded assistance information. The base station may transmit the encoded assistance information to the wireless device via a control or data channel. The wireless device may use the encoded assistance information to update one or more behaviors of the wireless device without decoding the encoded assistance information. The wireless device may include a different neural network configured to learn how to use the encoded assistance information to update one or more behaviors of the wireless device.

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