Seungnyun Kim

Cell-free system where a group of base stations (BSs) cooperatively serves users has received much attention as a promising technology for the future wireless systems. In order to maximize the cooperation gain in the cell-free systems, acquisition of downlink channel state information (CSI) at the BSs is crucial. While this task is relatively easy for the time division duplexing (TDD) systems due to the channel reciprocity, it is not easy for the frequency division duplexing (FDD) systems due to

As a means to achieve thousand-fold throughput improvements of future wireless communications, ultra-dense network (UDN) where a large number of small cells are densely deployed on top of the macro cells has received great deal of attention in recent years. While UDN offers number of benefits, intensive deployment of small cells may pose a serious concern in the energy consumption. Over the years, to reduce the energy consumption of UDN, an approach that turns off the lightly loaded base station

MmWave cell-free systems where multiple base stations (BSs) cooperatively serve user using the mmWave band signal have gained much attention recently due to its capability to dramatically improve the system capacity. One potential drawback of mmWave cell-free systems is that an intensive deployment of BSs increases the energy consumption of network substantially. To improve the energy efficiency, acquisition of accurate downlink channel state information (CSI) at the BSs is essential. However, t

Cell-free massive MIMO system is a promising technology of 5G wireless communications that provide a user-centric coverage to the user by the basestation cooperation. Most prior works on the cell-free massive MIMO systems assume the time division duplexing (TDD) systems, although the frequency division duplexing (FDD) systems dominate the current wireless communications. In the FDD systems, CSI acquisition and feedback overhead are serious concerns when the number of antennas is large. To addres

Terahertz (THz) communication is envisaged as an attractive way to attain abundant spectrum resources for 6G wireless communications. One main difficulty of the THz communications is the severe attenuation of signal power caused by the high diffraction and penetration losses and atmospheric absorption. To compensate for the severe path loss, a beamforming technique realized by the massive multiple-input multiple-output (MIMO) has been widely used. Since the beamforming gain is maximized only whe

Recently, we have been witnessing the remarkable progress and widespread adoption of sensing technologies in autonomous driving, robotics, and metaverse. Considering the rapid advancement of computer vision (CV) technology to analyze the sensing information, we anticipate a proliferation of wireless applications exploiting the sensing and CV technologies in 6G. In this article, we provide a holistic overview of the sensing and CV-aided wireless communications (SVWC) framework for 6G. By analyzin

Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) is envisioned as a key technology to support ever-increasing data rates in 6 G communication systems. To make the most of THz UM-MIMO systems, acquisition of accurate channel information is crucial. However, the THz channel acquisition is not easy due to the humongous pilot overhead that scales linearly with the number of antennas. In this paper, we propose a novel deep learning (DL)-based channel acquisition technique called

To meet the ever-increasing data rate demand expected in 6G networks, terahertz (THz) ultra-massive (UM) multiple-input multiple-output (MIMO) systems have gained much attention recently. One notable aspect of these systems is that the deployment of an extremely large-scale antenna array and high transmission frequency result in an expansion of the near-field region where the electromagnetic (EM) radiation is modeled as a spherical wave. In the near-field region, the channel becomes a function o

Recently, a reconfigurable intelligent surface (RIS) that controls the reflection characteristics of incident signals has received a great deal of attention. To make the most of the RIS-aided systems, an acquisition of RIS reflected channel information at the base station (BS) is crucial. However, this task is by no means easy due to the pilot overhead induced by the large number of reflecting elements. In this paper, we propose an efficient channel estimation and phase shift control technique r

Cell-less communication is one of a promising technology of 5G wireless communications for providing a user-centric approach that goes beyond the regional cell of the conventional cellular system. In order to provide user-centric services, location information of the mobile station is required. In this paper, we propose a new localization technique to support the cell-less communication. The proposed scheme consists of two parts. First, estimating the signal parameters, angle of arrival (AOA) an

As a means to provide ubiquitous connectivity across the ground-air-space 3D network, low Earth orbit (LEO) satellite mega-constellation systems comprising thousands of LEO satellites have attracted significant interest from both academia and industry recently. One major issue of LEO mega-constellation systems is the frequent handovers between satellites and beams, causing an increase in communication latency and deterioration of quality of service (QoS). In this paper, we propose a user-centric

Cell-free massive MIMO system is one of a promising technology of 5G wireless communications that can provide high throughput from the basestation cooperation. To capitalize on the gain obtained by the basestation cooperation, the downlink channel state information (CSI) should be available at the basestations. In the popularly used frequency division duplexing (FDD) system, the downlink CSI must be fed back from the users. However, due to a large number of antennas and basestations, the feedbac

Massive multi-input multi-output systems with large-scale transmit antenna arrays can bring significant improvements in the spectral efficiency and energy efficiency. To fully enjoy the benefits of the massive MIMO systems, acquisition of accurate downlink channel state information (CSI) at the basestation is crucial. While the CSI acquisition is relatively easy for the time division duplexing (TDD) systems, it is quite burdensome for the frequency division duplexing (FDD) systems due to the CSI

Cell-less system is a promising technology of the next generation wireless communications where a group of basestations intelligently recognizes user's communication environments and cooperatively serves the user. In order to maximize the gain obtained by the basestation cooperation, acquisition of accurate downlink channel state information (CSI) at the basestation is crucial. While this task is relatively easy for the time division duplexing (TDD) systems due to the channel reciprocity, it is

Reconfigurable intelligent surface (RIS) is a promising technology that can provide a virtual line-of-sight (LoS) link for the mmWave communications via intelligent signal reflection. In order to maximize the throughput of RIS-aided mmWave systems, acquisition of accurate downlink channel information at the base station (BS) is crucial. However, since the BS needs to acquire not only the conventional direct channel between the BS and user but also the channels reflected by RIS (i.e., BS to RIS a