Channel Estimation for an Antenna Array
    2.
    发明公开

    公开(公告)号:US20230353426A1

    公开(公告)日:2023-11-02

    申请号:US17923138

    申请日:2021-05-10

    CPC classification number: H04L25/0254 H04L25/0212

    Abstract: A method of channel estimation for an antenna array is disclosed. The method includes, receiving a signal transmitted by the antenna array, obtaining a neural network model trained for channel estimation using the received signal, inputting a representation of the received signal into the neural network model and generating a channel estimate for the received signal, and deciding whether to employ a further neural network model for the channel estimation.

    MANAGING NETWORK SENSING CAPABILITIES IN A WIRELESS NETWORK

    公开(公告)号:US20220272506A1

    公开(公告)日:2022-08-25

    申请号:US17671765

    申请日:2022-02-15

    Abstract: A method comprising controlling sensing operations of one or more access nodes, obtaining information from the sensing operations of the one or more access nodes, receiving, from a device, a request to be provided sensing services, wherein the sensing services are based on the obtained information, determining a sensing quality of service associated with the request, receiving, from the device, information regarding sensing capabilities of the device, and based, at least partly, on the request and the sensing capabilities of the device, determining if the requested sensing services can be provided.

    Full Resource Allocation
    4.
    发明公开

    公开(公告)号:US20230284152A1

    公开(公告)日:2023-09-07

    申请号:US18019293

    申请日:2020-08-06

    CPC classification number: H04W52/262 H04L1/0003 H04L1/0025 H04W52/146

    Abstract: A method including: determining a respective first amount of resources each with a respective first power and a non-aggressive MCS such that a target value is guaranteed for a BLER of a transmission to a terminal under a channel estimate of a channel and a SINR estimate; and instructing a transmission device to perform the transmission using the non-aggressive MCS on the first amount of the resources each with the first power, wherein the transmission device may perform hypothetically the transmission using an aggressive MCS on a second amount of the resources each with a respective maximum available power such that the target value is guaranteed for the BLER under the assumed conditions; the first amount of the resources is larger than the second amount of the resources, the respective first power is less than the respective maximum available power.

    Transmission System with Channel Estimation Based on a Neural Network

    公开(公告)号:US20220376956A1

    公开(公告)日:2022-11-24

    申请号:US17623445

    申请日:2019-07-03

    Abstract: An apparatus, method and computing program is described including: receiving one or more received symbols and one or more received bits, wherein the received symbols are received at a receiver of a transmission system including a transmitter, a channel, and the receiver; converting one or more of the received bits that are deemed to be correct into one or more estimated transmission symbols; generating an estimated channel transfer function based on one or more of the estimated transmission symbols and corresponding received symbols; and providing training data pairs, each training data pair including a first element based on the estimated channel transfer function and a second element based on the corresponding received symbols.

    METHODS AND APPARATUSES FOR JOINT COMMUNICATION AND SENSING

    公开(公告)号:US20250097937A1

    公开(公告)日:2025-03-20

    申请号:US18887244

    申请日:2024-09-17

    Abstract: A serving base station is disclosed, serving a user equipment, includes means for: transmitting, to the user equipment, a scheduling grant for an uplink transmission; transmitting, to at least one supporting base station, sensing support information associated with the scheduling grant; receiving, from the user equipment, an uplink transmission in accordance with the scheduling grant; determining sensing information based on the received uplink transmission. Also disclosed are: a method, performed by a serving base station; a supporting base station, supporting a serving base station serving a user equipment in a sensing operation; a method, performed by a supporting base station; a sensing management function; a network entity including means for performing a sensing management function, and a system including at least one user equipment, at least one serving base station and at least one supporting base station.

    CLASSES OF NN PARAMETERS FOR CHANNEL ESTIMATION

    公开(公告)号:US20230125699A1

    公开(公告)日:2023-04-27

    申请号:US17908726

    申请日:2020-03-06

    Abstract: It is provided a method, comprising identifying a value of an onsite channel characteristic of a receive channel; requesting a neural network parameter, wherein the request comprises an indication of the onsite channel characteristic; monitoring if the neural network parameter is received in response to the request; estimating the receive channel by a neural network using the neural network parameter if the neural network parameter is received.

    RADAR EXCITATION SIGNALS FOR WIRELESS COMMUNICATIONS SYSTEM

    公开(公告)号:US20210286064A1

    公开(公告)日:2021-09-16

    申请号:US16923618

    申请日:2020-07-08

    Abstract: One radar excitation signal has a first burst duration and a first sampling period. Another radar excitation signal has a second burst duration and a second sampling period. The first sampling period of the first signal is configured for scanning a velocity range and the second sampling period of the second signal is configured for scanning a portion of the velocity range, and the first burst duration is smaller than the second burst duration. The at least two radar excitation signals are embedded into a frame structure for a wireless communications system. At least one radar operation comprising at least one transmission based on the frame structure is performed. In this way the overhead of the radar excitation signals on the air interface of the wireless communications system may be controlled, while supporting a fine velocity resolution and a sufficiently large maximum velocity for a monitored target.

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