公开(公告)号：US20240106682A1

公开(公告)日：2024-03-28

申请号：US18471589

申请日：2023-09-21

Applicant: Nokia Solutions and Networks Oy

Inventor： Aliye KAYA ,  Luiz Fernando MEDEIROS

IPC: H04L25/02 ,  H04L5/00

CPC classification number: H04L25/0204 ,  H04L5/0048 ,  H04L25/0224

Abstract: Disclosed is a method comprising generating a preamble matrix comprising a plurality of entries, wherein at least a subset of the plurality of entries indicate random-access preambles; obtaining a sequence encoded with the preamble matrix; and transmitting the sequence to one or more user devices.

公开(公告)号：US20220114423A1

公开(公告)日：2022-04-14

申请号：US17498060

申请日：2021-10-11

Applicant: NOKIA SOLUTIONS AND NETWORKS OY

Inventor： Aliye KAYA ,  Michal MATERNIA

IPC: G06N3/04 ,  H04B7/06 ,  H04B17/391 ,  G06N3/08

Abstract: To configure a set of user devices, which comprises one or more user devices, to monitor a subset of beams, at least one past beam sequence indicating one or more beams, which served the set is determined, and inputted to a trained model which outputs a probability distribution. Then as many beams as is a number of beams determined for the set to monitor is selected from the probability distribution according to a first criteria, and the set of user devices is configured to monitor and report beams in the beam group. Past beam sequences are also used in training. From the past sequences, set-specifically, past beams that served a set within a first time interval are determined to be used as training data, and future beams that served the set within a second time interval following the first time interval are determined to be used as validation data.

公开(公告)号：US20250132848A1

公开(公告)日：2025-04-24

申请号：US18910325

申请日：2024-10-09

Applicant: NOKIA SOLUTIONS AND NETWORKS OY

Inventor： Aliye KAYA ,  Afef FEKI ,  Christophe GRANGEAT ,  Azra ZEJNILAGIC ,  Kamil BECHTA

IPC: H04B17/391 ,  H04B7/06

Abstract: An apparatus comprising at least one processor, and at least one memory. The at least one memory stores instructions that, when executed by the at least one processor, caused the apparatus to train a neural network configured to be used to infer an effective isotropic radiated power for at least one angle and at least one weight, and to obtain, based on the training, a trained neural network which is used for inference of the effective isotropic radiated power for the at least one angle and the at least one weight. The trained neural network is transmitted to at least one distributed unit.

公开(公告)号：US20250126652A1

公开(公告)日：2025-04-17

申请号：US18726066

申请日：2022-01-10

Applicant: Nokia Solutions and Networks Oy

Inventor： Aliye KAYA ,  Harish VISWANATHAN ,  Luiz Fernando MEDEIROS

IPC: H04W74/0833 ,  H04L27/26

Abstract: Physical random access channel (PRACH) radio receiver devices and related methods and computer programs are disclosed. An uplink (UL) synchronization signal is received at a radio receiver device. The UL synchronization signal comprises a PRACH preamble. The PRACH preamble comprises a preamble sequence set. The radio receiver device extracts the preamble sequence set. The radio receiver device applies a neural network (NN) to the extracted preamble sequence set to determine a physical root sequence index, an associated cyclic shift value, and/or a timing offset value, for at least one preamble sequence instance in the extracted preamble sequence set. The radio receiver device further applies the NN to output at least one of the determined physical root sequence index, the associated cyclic shift value, and/or the timing offset value, for the at least one preamble sequence instance in the extracted preamble sequence set.

公开(公告)号：US20230156765A1

公开(公告)日：2023-05-18

申请号：US17988402

申请日：2022-11-16

Applicant: NOKIA SOLUTIONS AND NETWORKS OY

Inventor： Aliye KAYA ,  Harish VISWANATHAN

IPC: H04W72/08 ,  H04W72/04

CPC classification number: H04W72/085 ,  H04W72/046

Abstract: According to an aspect, there is provided an apparatus for the performing the following. The apparatus implements, separately for at least one downlink beam, a reinforcement learning model, where a state defines which of the plurality of uplink beams belong to a priority beam set for uplink reception corresponding to a downlink beam, an action is defined as an addition of a new uplink beam to the priority beam set, a removal of an uplink beam from the priority beam set or doing nothing and a reward is calculated based on a change in uplink signal-to-noise ratio due to an action adjusted with a cost for taking the action. The apparatus calculates iteratively at least one optimal state using at least one reinforcement learning model based on uplink signal-to-noise ratio statistics and on the plurality of optimal downlink beams for transmission to said plurality of terminal devices.