Koichi Tsunekawa - IEEE Xplore Author Profile

Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Institutional Sign In

Institutional Sign In

ADVANCED SEARCH

Author details

Koichi Tsunekawa

Also published under: K. Tsunekawa, Kichi Tsunekawa

Publications

28

Citations

387

Publications by Year

19862015

Co-Authors:

A. AndoH. AraiCheng YangTakatomo EnokiM. Furukawa

Show All Co-Authors (30)

Koichi Tsunekawa

Also published under: K. Tsunekawa, Kichi Tsunekawa

Affiliation

Chubu University

Kasugai-shi

Aichi, Japan

Publication Topics

Wireless Power Transfer,
Wireless Power Transfer System,
Port Impedance,
Power Transfer,
Power Transfer Efficiency,
Resonance Frequency,
Wireless Power,
Coupling Coefficient,
Impedance Matching,
Magnetic Field,
Maximum Power Transfer,
Optimal Impedance

Biography

Koichi Tsunekawa (M'89) received the B. S., M. S., and Ph. D. degrees in science engineering from Tsukuba University, Ibaraki, Japan, in 1981, 1983, and 1992, respectively.,In 1983, he joined NTT Electrical Communications Laboratories (ECL), Nippon Telegraph and Telephone Corporation, Tokyo, Japan. Since 1984, he has been engaged in the research and development of portable telephone antennas in land mobile communication systems. From 1993 to 2003, he was with NTT DoCoMo Inc. He worked on radio propagation research, intelligent antenna systems for wireless communications, and developing IMT-2000 antenna systems. His studied antenna systems for MIMO transmission and millimeter-wave broadband access. From 2003 to 2006, he was with the Wireless...

Publications

28

Citations

387

Publications by Year

19862015

Co-Authors:

A. Ando
H. Arai
Cheng Yang
Takatomo Enoki
M. Furukawa

Show All Co-Authors (30)

Author's Published Works

Search History

Showing 1-25 of 122 results

Conferences (74)

Journals (38)

Magazines (10)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Jianzhong Zhang(79)
Jianzhong Charlie Zhang(38)
Lingjia Liu(35)
Boon Loong Ng(21)
Yang Li(16)
Samsung Research America, Richardson, TX, USA(14)
University of Southern California, Los Angeles, CA, USA(10)
Standards and Mobility Innovation Laboratory, Samsung Research America, Plano, TX, USA(9)
Samsung Research America(7)
Department of Electrical Engineering and Computer Science, University of Kansas, USA(6)
IEEE Transactions on Wireless Communications(13)
IEEE Access(7)
IEEE Communications Magazine(7)
2019 IEEE Global Communications Conference (GLOBECOM)(4)
2015 IEEE Global Communications Conference (GLOBECOM)(3)
IEEE(121)
KICS(1)
Video(1)
San Diego, CA, USA(7)
Pacific Grove, CA, USA(4)
Seoul, Korea, Republic of(4)
Waikoloa, HI, USA(4)
Austin, TX, USA(3)
Base Station(58)
Antenna Array(54)
User Equipment(30)
Channel Estimation(23)
Channel Model(23)

Select All on Page

Sort By

Results

Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-Context Learning

Hao Zhou;Chengming Hu;Dun Yuan;Ye Yuan;Di Wu;Xue Liu;Zhu Han;Jianzhong Zhang

IEEE Wireless Communications Letters

Year: 2025 | Volume: 14, Issue: 3 | Journal Article |

Cited by: Papers (1)

HTML

Generative artificial intelligence (GAI) is a promising technique towards 6G networks, and generative foundation models such as large language models (LLMs) have attracted considerable interest from academia and industry. This letter considers a novel edge-cloud deployment of foundation models in 6G networks. Specifically, it aims to minimize the service delay of foundation models by radio resourc...Show More

Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-Context Learning

Hao Zhou;Chengming Hu;Dun Yuan;Ye Yuan;Di Wu;Xue Liu;Zhu Han;Jianzhong Zhang

IEEE Wireless Communications Letters

Year: 2025 | Volume: 14, Issue: 3 | Journal Article |

Physics-Inspired Deep Learning Anti-Aliasing Framework in Efficient Channel State Feedback

Yu-Chien Lin;Yan Xin;Ta-Sung Lee;Jianzhong Charlie Zhang;Zhi Ding

IEEE Transactions on Wireless Communications

Year: 2025 | Volume: 24, Issue: 2 | Journal Article |

HTML

Acquiring downlink channel state information (CSI) at the base station is vital for optimizing performance in massive Multiple input multiple output (MIMO) Frequency-Division Duplexing (FDD) systems. While deep learning architectures have been successful in facilitating UE-side CSI feedback and gNB-side recovery, the undersampling issue prior to CSI feedback is often overlooked. This issue, which ...Show More

Physics-Inspired Deep Learning Anti-Aliasing Framework in Efficient Channel State Feedback

Yu-Chien Lin;Yan Xin;Ta-Sung Lee;Jianzhong Charlie Zhang;Zhi Ding

IEEE Transactions on Wireless Communications

Year: 2025 | Volume: 24, Issue: 2 | Journal Article |

O-RAN-Enabled Intelligent Network Slicing to Meet Service-Level Agreement (SLA)

Jiongyu Dai;Lianjun Li;Ramin Safavinejad;Shadab Mahboob;Hao Chen;Vishnu V Ratnam;Haining Wang;Jianzhong Zhang;Lingjia Liu

IEEE Transactions on Mobile Computing

Year: 2025 | Volume: 24, Issue: 2 | Journal Article |

HTML

Network slicing plays a critical role in enabling multiple virtualized and independent network services to be created on top of a common physical network infrastructure. In this paper, we introduce a deep reinforcement learning (DRL)-based radio resource management (RRM) solution for radio access network (RAN) slicing under service-level agreement (SLA) guarantees. The objective of this solution i...Show More

O-RAN-Enabled Intelligent Network Slicing to Meet Service-Level Agreement (SLA)

Jiongyu Dai;Lianjun Li;Ramin Safavinejad;Shadab Mahboob;Hao Chen;Vishnu V Ratnam;Haining Wang;Jianzhong Zhang;Lingjia Liu

IEEE Transactions on Mobile Computing

Year: 2025 | Volume: 24, Issue: 2 | Journal Article |

Multipath Cluster Analysis for Device-to-Device Terahertz Outdoor Measurements

Zihang Cheng;Naveed A. Abbasi;Jorge Gomez-Ponce;Jianzhong Charlie Zhang;Andreas F. Molisch

MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM)

Year: 2024 | Conference Paper |

HTML

Since the terahertz frequency band (0.1–1 THz) has attracted considerable attention for the upcoming sixth-generation (6G) wireless communication systems, accurate models for multipath propagation in this frequency range need to be established. Such models advantageously use the fact that multi-path components (MPCs) occur typically in clusters, i.e., groups of MPCs that have similar delays and an...Show More

Multipath Cluster Analysis for Device-to-Device Terahertz Outdoor Measurements

Zihang Cheng;Naveed A. Abbasi;Jorge Gomez-Ponce;Jianzhong Charlie Zhang;Andreas F. Molisch

MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM)

Year: 2024 | Conference Paper |

3D Beamforming Through Joint Phase-Time Arrays

Ozlem Yildiz;Ahmad AlAmmouri;Jianhua Mo;Younghan Nam;Elza Erkip;Jianzhong Charlie Zhang

2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)

Year: 2024 | Conference Paper |

HTML

High-frequency wideband cellular communications over mmWave and sub-THz offer the opportunity for high data rates. However, it also presents high path loss, resulting in limited coverage. High-gain beamforming from the antenna array is essential to mitigate the coverage limitations. The conventional phased antenna arrays (PAA) cause high scheduling latency owing to analog beam constraints, i.e., o...Show More

3D Beamforming Through Joint Phase-Time Arrays

Ozlem Yildiz;Ahmad AlAmmouri;Jianhua Mo;Younghan Nam;Elza Erkip;Jianzhong Charlie Zhang

2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)

Year: 2024 | Conference Paper |

Diffusion Model Based Channel Estimation

Xiaochuan Ma;Yan Xin;Yong Ren;Daoud Burghal;Hao Chen;Jianzhong Charlie Zhang

2024 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2024 | Conference Paper |

HTML

In this paper, we propose to apply diffusion model based posterior sampling to channel estimation (CE) problems. In the proposed solutions, we employ diffusion models to learn the score functions of the posterior channel data distribution and apply posterior sampling in the reverse process of denoising diffusion probabilistic models (DDPM) and denoising diffusion implicit models (DDIM) to recover ...Show More

Diffusion Model Based Channel Estimation

Xiaochuan Ma;Yan Xin;Yong Ren;Daoud Burghal;Hao Chen;Jianzhong Charlie Zhang

2024 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2024 | Conference Paper |

Dynamic MIMO: A Key Enabler for 6G

Md Saifur Rahman;Eko Onggosanusi;Emad Farag;Marian Rudolf;Gilwon Lee;Dalin Zhu;Jianzhong Zhang;Younsun Kim;Hyoungju Ji

2023 IEEE Globecom Workshops (GC Wkshps)

Year: 2023 | Conference Paper |

HTML

The 5G standard can support several features and services that can achieve KPIs such as high data-date, ultrareliability, and low-latency. It however can be too complex due to (a) different levels of abstractions for NW entities and (b) multilayer-based signaling (RRC, MAC CE, and DCI) for components of these abstractions. The implementation of these features/services can therefore be challenging ...Show More

Dynamic MIMO: A Key Enabler for 6G

Md Saifur Rahman;Eko Onggosanusi;Emad Farag;Marian Rudolf;Gilwon Lee;Dalin Zhu;Jianzhong Zhang;Younsun Kim;Hyoungju Ji

2023 IEEE Globecom Workshops (GC Wkshps)

Year: 2023 | Conference Paper |

Machine Learning-Assisted Codebook Design for MMSE Channel Estimation

Xiaowen Tian;Yeqing Hu;Yang Li;Tiexing Wang;Jianzhong Charlie Zhang

2023 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2023 | Conference Paper |

HTML

In order to realize the high spectral efficiency promised by the new radio, the channel estimation algorithm shall be carefully designed to achieve high accuracy. Conventional optimal estimation techniques require the knowledge of secondorder statistics, which is difficult to compute in real-time systems. In this work, we propose a machine learning-assisted codebook design for minimum mean square ...Show More

Machine Learning-Assisted Codebook Design for MMSE Channel Estimation

Xiaowen Tian;Yeqing Hu;Yang Li;Tiexing Wang;Jianzhong Charlie Zhang

2023 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2023 | Conference Paper |

Decentralized Deep Reinforcement Learning Meets Mobility Load Balancing

Hao-Hsuan Chang;Hao Chen;Jianzhong Zhang;Lingjia Liu

IEEE/ACM Transactions on Networking

Year: 2023 | Volume: 31, Issue: 2 | Journal Article |

Cited by: Papers (17)

HTML

Mobility load balancing (MLB) aims to solve the problem of uneven resource utilization in cellular networks. Since network dynamics are usually complicated and non-stationary, conventional model-based MLB methods fail to cover all scenarios of cellular networks. On the other hand, deep reinforcement learning (DRL) can provide a flexible framework to learn to distribute cell load evenly without exp...Show More

Decentralized Deep Reinforcement Learning Meets Mobility Load Balancing

Hao-Hsuan Chang;Hao Chen;Jianzhong Zhang;Lingjia Liu

IEEE/ACM Transactions on Networking

Year: 2023 | Volume: 31, Issue: 2 | Journal Article |

THz Band Channel Measurements and Statistical Modeling for Urban D2D Environments

Naveed A. Abbasi;Jorge Luis Gomez;Revanth Kondaveti;Shahid M. Shaikbepari;Shreyas Rao;Shadi Abu-Surra;Gary Xu;Jianzhong Zhang;Andreas F Molisch

IEEE Transactions on Wireless Communications

Year: 2023 | Volume: 22, Issue: 3 | Journal Article |

Cited by: Papers (40)

HTML

THz band is envisioned to be used in 6G systems to meet the ever-increasing demand for data rate. However, before an eventual system design and deployment can proceed, detailed channel sounding measurements are required to understand key channel characteristics. In this paper, we present a first extensive set of channel measurements for urban outdoor environments that are ultra-wideband, and doubl...Show More

THz Band Channel Measurements and Statistical Modeling for Urban D2D Environments

Naveed A. Abbasi;Jorge Luis Gomez;Revanth Kondaveti;Shahid M. Shaikbepari;Shreyas Rao;Shadi Abu-Surra;Gary Xu;Jianzhong Zhang;Andreas F Molisch

IEEE Transactions on Wireless Communications

Year: 2023 | Volume: 22, Issue: 3 | Journal Article |

MADRL Based Scheduling for 5G and Beyond

Hao–Hsuan Chang;R.B.Sai Sree;Hao Chen;Jianzhong Zhang;Lingjia Liu

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

Year: 2022 | Conference Paper |

Cited by: Papers (3)

HTML

Scheduling in cellular networks plays a critical role and is a key differentiating factor of network performance. The design of scheduling algorithms is challenging since it has to be both computationally efficient to meet the real-time Transmission Time Interval (TTI) requirements and robust to inaccurate/coarse channel-feedback information. Addressing the aforementioned challenges, this paper pr...Show More

MADRL Based Scheduling for 5G and Beyond

Hao–Hsuan Chang;R.B.Sai Sree;Hao Chen;Jianzhong Zhang;Lingjia Liu

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

Year: 2022 | Conference Paper |

Low-Complexity Channel Matrix Calculation for OTFS Systems with Fractional Delay and Doppler

Zheng Wang;Lingjia Liu;Yang Yi;Robert Calderbank;Jianzhong Zhang

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

HTML

Orthogonal Time Frequency Space (OTFS) modulation has been introduced to manage channel induced high Doppler shifts in mobile communication networks. In an OTFS system, the information carrying symbols are placed in the data frames in the delay-Doppler (DD) domain before transformed into the time domain for transmission. Accordingly, the DD domain channel matrix can be estimated using the correspo...Show More

Low-Complexity Channel Matrix Calculation for OTFS Systems with Fractional Delay and Doppler

Zheng Wang;Lingjia Liu;Yang Yi;Robert Calderbank;Jianzhong Zhang

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

Year: 2022 | Conference Paper |

Path Towards Tbps Communications: LoS MIMO Theory, Simulation and Measurement Analysis

Sandy Saab;Dongjoo Kim;Shadi Abu-Surra;Gary Xu;Jianzhong Zhang

2022 IEEE Globecom Workshops (GC Wkshps)

Year: 2022 | Conference Paper |

Cited by: Papers (3)

HTML

Motivated by increasing the data rates for future 6G networks, we present the first line-of-sight (LoS) multiple-input multiple-output (MIMO) system operating at tera-hertz (THz) frequencies using Samsung’s state-of-the-art equipment. The system performance is analyzed over different transmit and receive distances using the measured error-vector-magnitude (EVM). We further scale our analysis throu...Show More

Path Towards Tbps Communications: LoS MIMO Theory, Simulation and Measurement Analysis

Sandy Saab;Dongjoo Kim;Shadi Abu-Surra;Gary Xu;Jianzhong Zhang

2022 IEEE Globecom Workshops (GC Wkshps)

Year: 2022 | Conference Paper |

Reducing FDD MMU Form Factor With Active Cancellation

Khurram Muhammad;Jin Yuan;Shaomin Zhang;Chance Tarver;Xinguang Xu;Yu Liu;Jie Li;Junghwan Moon;Matthew Tonnemach;Gary Xu;Jianzhong Charlie Zhang

2022 IEEE/MTT-S International Microwave Symposium - IMS 2022

Year: 2022 | Conference Paper |

HTML

In this paper, a multi-channel self-interference cancellation (SIC) technique is proposed to reduce the size of AWS/PCS dual-band 5G FDD massive MIMO base station. Combining two bands with small frequency offset such as PCS and AWS bands in a base station requires modification of frequency duplex cavity filters to provide a wide passband with extremely narrow gap between the passband and the stop ...Show More

Reducing FDD MMU Form Factor With Active Cancellation

Khurram Muhammad;Jin Yuan;Shaomin Zhang;Chance Tarver;Xinguang Xu;Yu Liu;Jie Li;Junghwan Moon;Matthew Tonnemach;Gary Xu;Jianzhong Charlie Zhang

2022 IEEE/MTT-S International Microwave Symposium - IMS 2022

Year: 2022 | Conference Paper |

Open-RAN and Future Intelligent Networks

Pranav Madadi;Caleb Lo;Jeongho Jeon;Joonyoung Cho;Jun-Hyuk Song;Jianzhong Charlie Zhang

2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

HTML

As the pace of global 5G network deployments accelerates, the telecommunications industry strives to move from a conventional vertical stack, closed, hardware-based ecosystem to an open, interoperable, modular, cloud-based ecosystem that leverages software-based implementations of various network entities – including core network functions and base stations. Such an open ecosystem could facilitate...Show More

Open-RAN and Future Intelligent Networks

Pranav Madadi;Caleb Lo;Jeongho Jeon;Joonyoung Cho;Jun-Hyuk Song;Jianzhong Charlie Zhang

2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)

Year: 2022 | Conference Paper |

Extending Uplink Coverage of mmWave and Terahertz Systems Through Joint Phase-Time Arrays

Ahmad Alammouri;Jianhua Mo;Vishnu V. Ratnam;Boon Loong Ng;Robert W. Heath;Juho Lee;Jianzhong Zhang

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (4)

HTML

In this paper, we establish the potential of joint phase-time arrays (JPTAs) for uplink coverage extension in cellular systems. JPTA allows the base station (BS) to create frequency-dependent wide-beams without sacrificing the array gain. In this work, we propose a novel use case of JPTA where the BS exploits the frequency-dependent beams to serve multiple users’ equipment (UEs) at different direc...Show More

Extending Uplink Coverage of mmWave and Terahertz Systems Through Joint Phase-Time Arrays

Ahmad Alammouri;Jianhua Mo;Vishnu V. Ratnam;Boon Loong Ng;Robert W. Heath;Juho Lee;Jianzhong Zhang

Year: 2022 | Volume: 10 | Journal Article |

End-to-End Dynamic Gesture Recognition Using MmWave Radar

Anum Ali;Priyabrata Parida;Vutha Va;Saifeng Ni;Khuong Nhat Nguyen;Boon Loong Ng;Jianzhong Charlie Zhang

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (5)

HTML

Millimeter-wave (mmWave) radar sensors are a promising modality for gesture recognition as they can overcome several limitations of optic sensors typically used for gesture recognition. These limitations include cost, battery consumption, and privacy concerns. This work focuses on finger level (called micro) gesture recognition using mmWave radar. We propose a set of 6 micro-gestures that are not ...Show More

End-to-End Dynamic Gesture Recognition Using MmWave Radar

Anum Ali;Priyabrata Parida;Vutha Va;Saifeng Ni;Khuong Nhat Nguyen;Boon Loong Ng;Jianzhong Charlie Zhang

Year: 2022 | Volume: 10 | Journal Article |

PolarDenseNet: A Deep Learning Model for CSI Feedback in MIMO Systems

Pranav Madadi;Jeongho Jeon;Joonyoung Cho;Caleb Lo;Juho Lee;Jianzhong Zhang

ICC 2022 - IEEE International Conference on Communications

Year: 2022 | Conference Paper |

Cited by: Papers (10)

HTML

In multiple-input multiple-output (MIMO) systems, the high-resolution channel information (CSI) is required at the base station (BS) to ensure optimal performance, especially in the case of multi-user MIMO (MU-MIMO) systems. In the absence of channel reciprocity in frequency division duplex (FDD) systems, the user needs to send the CSI to the BS. Often the large overhead associated with this CSI f...Show More

PolarDenseNet: A Deep Learning Model for CSI Feedback in MIMO Systems

Pranav Madadi;Jeongho Jeon;Joonyoung Cho;Caleb Lo;Juho Lee;Jianzhong Zhang

ICC 2022 - IEEE International Conference on Communications

Year: 2022 | Conference Paper |

Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G

Vishnu V. Ratnam;Jianhua Mo;Ahmad Alammouri;Boon Loong Ng;Jianzhong Zhang;Andreas F. Molisch

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (13)

HTML

Hybrid beamforming is an attractive solution to build cost-effective and energy-efficient transceivers for millimeter-wave and terahertz systems. However, conventional hybrid beamforming techniques rely on analog components that generate a frequency flat response such as phase-shifters and switches, which limits the flexibility of the achievable beam patterns. As a novel alternative, this paper pr...Show More

Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G

Vishnu V. Ratnam;Jianhua Mo;Ahmad Alammouri;Boon Loong Ng;Jianzhong Zhang;Andreas F. Molisch

Year: 2022 | Volume: 10 | Journal Article |

End-to-end 6G Terahertz Wireless Platform with Adaptive Transmit and Receive Beamforming

Shadi Abu-Surra;Wonsuk Choi;SungTae Choi;Eunyoung Seok;Dongjoo Kim;Navneet Sharma;Siddharth Advani;Vitali Loseu;Kitaek Bae;Ilju Na;Ali A. Farid;Mark J. W. Rodwell;Gary Xu;Jianzhong Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

Cited by: Papers (15)

HTML

6G is envisioned to provide ultimate experience for all through hyper-connectivity involving humans and everything, with unprecedented requirements and expectations [1]. In this vision, terahertz (THz) technology is a leading candidate to realize the 6G requirements. This paper presents the latest development and results of a terahertz wireless prototyping platform, which is being developed in Sam...Show More

End-to-end 6G Terahertz Wireless Platform with Adaptive Transmit and Receive Beamforming

Shadi Abu-Surra;Wonsuk Choi;SungTae Choi;Eunyoung Seok;Dongjoo Kim;Navneet Sharma;Siddharth Advani;Vitali Loseu;Kitaek Bae;Ilju Na;Ali A. Farid;Mark J. W. Rodwell;Gary Xu;Jianzhong Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems

Khuong N. Nguyen;Anum Ali;Jianhua Mo;Boon Loong Ng;Vutha Va;Jianzhong Charlie Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

Cited by: Papers (12)

HTML

Beam management (BM), i.e., the process of finding and maintaining a suitable transmit and receive beam pair, can be challenging, particularly in highly dynamic scenarios. Side-information, e.g., orientation, from on-board sensors can assist the user equipment (UE) BM. In this work, we use the orientation information coming from the inertial measurement unit (IMU) for effective BM. We use a data-d...Show More

Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems

Khuong N. Nguyen;Anum Ali;Jianhua Mo;Boon Loong Ng;Vutha Va;Jianzhong Charlie Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

5G New Radio and Non-Terrestrial Networks: Reaching New Heights

Qiaoyang Ye;Caleb Lo;Jeongho Jeon;Chance Tarver;Matthew Tonnemacher;Jeongho Yeo;Joonyoung Cho;Gary Xu;Younsun Kim;Jianzhong Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

Cited by: Papers (7)

HTML

As the need for limitless connectivity surges, non-terrestrial networks (NTN) will play a central role in fifth generation (5G) and beyond communications. The 3rd Gener-ation Partnership Project (3GPP) defines NTN as networks, or segments of networks, using an airborne or space-borne vehicle as a relay node or base station. An NTN-enhanced cellular network supplements a conventional terrestrial ce...Show More

5G New Radio and Non-Terrestrial Networks: Reaching New Heights

Qiaoyang Ye;Caleb Lo;Jeongho Jeon;Chance Tarver;Matthew Tonnemacher;Jeongho Yeo;Joonyoung Cho;Gary Xu;Younsun Kim;Jianzhong Zhang

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

Year: 2022 | Conference Paper |

Model-driven Machine Learning Approach for Mobility Classification in Intelligent 5G Network

Tiexing Wang;Yeqing Hu;Yang Li;Junmo Sung;Rui Wang;Jianzhong Charlie Zhang

2022 IEEE Wireless Communications and Networking Conference (WCNC)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

HTML

Channel information is essential to unleash the benefits of 5G New Radio (NR) by enabling network intelligence that adapts transmissions to users’ channels. In this paper, we propose model-driven feature design and use support vector machine (SVM) to classify users’ speed range. Our model-driven features are designed based on stochastic channel modeling. Multiple features are derived from time-dom...Show More

Model-driven Machine Learning Approach for Mobility Classification in Intelligent 5G Network

Tiexing Wang;Yeqing Hu;Yang Li;Junmo Sung;Rui Wang;Jianzhong Charlie Zhang

2022 IEEE Wireless Communications and Networking Conference (WCNC)

Year: 2022 | Conference Paper |

Distributed FD-MIMO (D-FD-MIMO): from Concept to Field Test

Jin Yuan;Yu Liu;Yeqing Hu;Gary Xu;Jianzhong Charlie Zhang

2022 IEEE Radio and Wireless Symposium (RWS)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

HTML

This paper presents the next evolution of FD-MIMO technology for beyond 5G, where antennas of the FD-MIMO system are placed in a distributed manner. This system, referred to as Distributed FD-MIMO (D-FD-MIMO) system, is capable of providing higher cell average throughput as well as more uniform user experience compared to the conventional FD-MIMO system. System level simulations results show that ...Show More

Distributed FD-MIMO (D-FD-MIMO): from Concept to Field Test

Jin Yuan;Yu Liu;Yeqing Hu;Gary Xu;Jianzhong Charlie Zhang

2022 IEEE Radio and Wireless Symposium (RWS)

Year: 2022 | Conference Paper |

MIMO Evolution toward 6G: Modular Massive MIMO in Low-Frequency Bands

Jeongho Jeon;Gilwon Lee;Ahmad A.I. Ibrahim;Jin Yuan;Gary Xu;Joonyoung Cho;Eko Onggosanusi;Younsun Kim;Juho Lee;Jianzhong Charlie Zhang

IEEE Communications Magazine

Year: 2021 | Volume: 59, Issue: 11 | Magazine Article |

Cited by: Papers (47)

HTML

As the pace of global 5G network deployments accelerates, now is the moment for the cellular industry to realize 6G cellular communication. In this article, modular massive multiple-in-put multiple-output (mmMIMO) is presented as one candidate technology for 6G to improve the spectral efficiency in low-frequency bands. The 5G New Radio pushed the boundary of the cellular system's operating frequen...Show More

MIMO Evolution toward 6G: Modular Massive MIMO in Low-Frequency Bands

Jeongho Jeon;Gilwon Lee;Ahmad A.I. Ibrahim;Jin Yuan;Gary Xu;Joonyoung Cho;Eko Onggosanusi;Younsun Kim;Juho Lee;Jianzhong Charlie Zhang

IEEE Communications Magazine

Year: 2021 | Volume: 59, Issue: 11 | Magazine Article |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Test Whats new message.