Industry-University Cooperation Foundation Hanyang University

Airs Medical Inc.

Lg Electronics Inc.

Sunwoo Kim

Jaehyun Kim

Youngho Kim

Joohyun Lee

Jeewook Kim

Jingu Lee

Dongrip Kim

Minsoo Jeong

Taekyoon Kim

Jeongwan Kang

Keunwoo Jeong

Jaeyeon Yoon

Hyeongwook Seo

Hongseok Jung

According to an embodiment of the present invention, there is provided a magnetic resonance image processing method that is performed by a magnetic resonance image processing apparatus, the magnetic resonance image processing method including: acquiring first k-space data calculated based on a sub-sampled magnetic resonance signal; acquiring second k-space data from the first k-space data by using a first artificial neural network model; and acquiring a first magnetic resonance image from the second k-space data by using an inverse Fourier operation.

Magnetic resonance image processing apparatus and method using artificial neural network in k-space domain

Provided are a method and a device for performing sidelink communication. Provided are a method by which a terminal performs sidelink communication, and a device, the method comprising the steps of: transmitting, to the other terminal, sidelink control information, which includes request information for requesting adjustment information, and indication information for indicating a resource type to be included in the adjustment information; receiving adjustment information from the other terminal; and determining a resource for performing sidelink communication on the basis of the adjustment information and/or resource sensing information.

Method for performing sidelink communication, and device therefor

The present embodiments provide a method by which a terminal uses an AI/ML model in a wireless communication network, the method comprising the steps of receiving activation or deactivation instruction information for the AI/ML model; activating or deactivating the AI/ML model on the basis of the instruction information; and transmitting a response to activation or deactivation of the AI/ML model.

Method and apparatus for using artificial intelligence/machine learning model in wireless communication network

A method for beam alignment through location recognition in a wireless communication system and an apparatus therefor are provided. The method includes a first process of configuring a beam set including beams based on relative location information of a terminal, a second process of receiving reference signals (RSs) from the terminal by using the beams, and a third process of determining an optimal beam from among the beams included in the beam set, and the third process includes configuring a window including adjacent beams in the beam set, measuring beams within the window by using the RSs, determining a local optimal beam from among the measured beams, and re-configuring a window based on the local optimal beam.

Apparatus and method for beam alignment based on location information in wireless communication system

The disclosure relates to a pre-5th-generation (5G) or 5G communication system to be provided for supporting higher data rates beyond 4th-generation (4G) communication system such as long term evolution (LTE). An operation of a base station to location-based user classification and power allocation in a wireless communication system is provided. The method performed by a base station includes forming a pre-defined terminal group beam, classifying terminals into a plurality of terminal group by using location information of the plurality of terminals, received from the base station, allocating transmit (Tx) power to a terminal in a terminal group based on the location information of the plurality of terminals existing in each terminal group, and adjusting Tx power distributed to each terminal group so that an overall system communication capacity is greatest.

Apparatus and method for transmitting and receiving information and power in wireless communication system

Growing community of inventors

Seoul, South Korea

Sunwoo Kim