Publications by authors named "Young-Hwan You"

This paper proposes a heuristic association algorithm between access points (APs) and user equipment (UE) in user-centric cell-free massive multiple-input-multiple-output (MIMO) systems, specifically targeting scenarios where UEs share the same frequency and time resources. The proposed algorithm prevents overserving APs and ensures the connectivity of all UEs, even when the number of UEs is significantly greater than the number of APs. Additionally, we assume the use of low-resolution analog-to-digital converters (ADCs) to reduce fronthaul capacity.

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Reconfigurable intelligent surface (RIS) has emerged as a promising technology to enhance the spectral efficiency of wireless communication systems. However, if there are many obstacles between the RIS and users, a single RIS may not provide sufficient performance. For this reason, a double RIS-aided communication system is proposed in this paper.

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The reconfigurable intelligent surface (RIS) and rate-splitting multiple access (RSMA) are considered as promising technologies for the beyond Fifth-Generation (B5G) and Sixth-Generation (6G) wireless systems by controlling the propagation environment, which attenuates the transmitted signal, and by managing the interference by splitting the user message into common and private messages. Because conventional RIS elements have each impedance connected to the ground, the sum-rate performance improvement of the RIS is limited. Therefore, the new RISs, which have impedance elements connected to each other, have been proposed recently.

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A reconfigurable intelligent surface (RIS) has potential for enhancing the performance of wireless communication. A RIS includes cheap passive elements, and the reflecting of signals can be controlled to a specific location of users. In addition, machine learning (ML) techniques are efficient in solving complex problems without explicit programming.

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This paper proposes a novel hybrid beamforming and relay selection scheme for spectral efficiency maximization in a non-regenerative multi-relay multi-input multi-output (MIMO) system. The analog beamforming component in the radio-frequency (RF) domain must follow an element-wise constant modulus constraint, which makes the underlying design problem mathematically intractable and therefore, it is quite challenging to obtain the global optimal solution. To address this problem, phase-only precoding/combining matrices are derived by maximizing the end-to-end received signal-to-noise ratio (SNR) under transmit power constraint at the source and each relay node.

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Visible light communication (VLC) has contributed new unused spectrum in addition to the traditional radio frequency communication and can play a significant role in wireless communication. The adaptation of VLC technology enhances wireless connectivity both in indoor and outdoor environments. Multiple-input multiple-output (MIMO) communication has been an efficient technique for increasing wireless communications system capacity and performance.

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Non-orthogonal multiple access (NOMA) has great potential to implement the fifth-generation (5G) requirements of wireless communication. For a NOMA traditional detection method, successive interference cancellation (SIC) plays a vital role at the receiver side for both uplink and downlink transmission. Due to the complex multipath channel environment and prorogation of error problems, the traditional SIC method has a limited performance.

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Article Synopsis
  • An intelligent reflecting surface (IRS) is a programmable device that enhances the control of electromagnetic wave propagation, playing a crucial role in the evolution of sixth-generation (6G) communication networks.
  • The text provides an in-depth overview of the use of machine learning (ML), particularly deep learning (DL), in optimizing IRS-enhanced communication, including principles, channel estimation, and practical applications.
  • It also discusses current designs for IRS-enhanced wireless networks and highlights key challenges and research prospects for integrating IRS with other cutting-edge technologies in future wireless communication.
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A cell-free massive multiple input multiple output (MIMO) system is an attractive network model that is in the spotlight in 5G and future communication systems. Despite numerous advantages, the cell-free massive MIMO system has a problem in that it is difficult to operate in reality due to its vast amount of calculation. The user-centric cell-free massive MIMO model has a more feasible and scalable benefit than the cell-free massive MIMO model.

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