University-Industry Cooperation Group of Kyung Hee University

Lg Electronics Inc.

Hyundong Shin

Youngmin Jeong

Hangyu Cho

Dongguk Lim

YoungMin Jeong

Dung Phuong Trinh

Provided are a method of modeling a channel and transmitting molecules for passive transport molecular communication, the method being performed by a first device, that is, a transmission device, and including a molecular transmission step of transmitting molecules which are an information carrier through the channel, an H-diffusion function information reception step of receiving information about an H-diffusion function which is a function associated with a diffusion of the channel, and a molecular transmission property control step of controlling a transmission property that the molecules are transmitted based on the received information about the H-diffusion function, a method of modeling a molecular channel using an H-diffusion function in relation to the diffusion of the channel, and a transmission control method thereof.

Method of modeling channel and transmitting molecules for molecular communication

Disclosed herein is a method of performing quantum channel estimation. The method is performed by a first device of a transmission device, and may include a first quantum state transmission step of transmitting a first quantum state &#x3c1; including an N-qubit sequence to a second device of a reception device through a quantum channel, a second quantum state information reception step of receiving information about a second quantum state &#x3a6;(&#x3c1;) received by the second device through the quantum channel from the second device, and a quantum channel estimation step of estimating the quantum channel based on the received information about the second quantum state &#x3a6;(&#x3c1;).

Quantum system performing quantum channel estimation and method of modeling quantum channel

A method of measuring a location of a user equipment (UE) located indoors in a wireless network includes receiving signals from a plurality of access points (APs), performing training for machine learning using the received signals or information acquired from the received signals, setting a weight vector to be applied to a relevance vector machine (RVM) method using data subjected to the training for machine learning, and applying RVM regression to the set weight vector and measured strengths of the received signals and determining whether the signals received from the plurality of APs are line of sight (LOS) signals or non line of sight (NLOS) signals.

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Suwon-si, South Korea

Hyundong Shin