Jin Nakazato

Jin Nakazato

Tokyo Institute of Technology

H-index: 6

Asia-Japan

About Jin Nakazato

Jin Nakazato, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Tokyo Institute of Technology, specializes in the field of wireless communication, edge computing, Heterogeneous Networks, Mobile Edge Computing, Multi-Access.

His recent articles reflect a diverse array of research interests and contributions to the field:

Optimizing mmWave Beamforming for High-Speed Connected Autonomous Vehicles: An Adaptive Approach

User Scheduling based on Expanded Null-Space for Massive MIMO

Study on the Coverage Extension of Millimeter Wave UAV BS Networks by Using IRS

Laboratory Experiment of Broad-Range Null-Steering for Millimeter-Wave V2I Multiuser MIMO

Location-Based Broad-Range Null-Steering in V2X Multiuser MIMO Transmission

WebRTC over 5 G: A Study of Remote Collaboration QoS in Mobile Environment

Location-aided fast beam tracking algorithm for millimeter-wave V2I

Millimeter-Wave Fast Beam Tracking Enabled by RAN/V2X Cooperation

Jin Nakazato Information

University

Tokyo Institute of Technology

Position

___

Citations(all)

112

Citations(since 2020)

110

Cited By

11

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

1

i10Index(since 2020)

1

Email

University Profile Page

Tokyo Institute of Technology

Jin Nakazato Skills & Research Interests

wireless communication

edge computing

Heterogeneous Networks

Mobile Edge Computing

Multi-Access

Top articles of Jin Nakazato

Optimizing mmWave Beamforming for High-Speed Connected Autonomous Vehicles: An Adaptive Approach

Authors

Ryo Iwaki,Jin Nakazato,Asad Muhammad,Ehsan Javanmardi,Kazuki Maruta,Manabu Tsukada,Hideya Ochiai,Hiroshi Esaki

Published Date

2024/1/6

The commercialization of 5G has been initiated for a while. Furthermore, millimeter wave (mmWave) has been introduced to small cells with small coverage due to its strong linearity and non-winding characteristics. On the other hand, in connected autonomous vehicles (CAV s), where various traffic systems can cooperatively perform recognition, decision-making, and execution, communication is assumed to be always connected. Therefore, to use low latency mm Wave for high-speed moving CAV, existing beamforming cannot follow them at high speed. This paper proposes an improved beam tracking algorithm for high-speed CAVs, which can be evaluated in a more general environment using a traffic simulator. We proposed an adaptive algorithm for a general road environment by increasing the number of beam searches and search dimensions.

User Scheduling based on Expanded Null-Space for Massive MIMO

Authors

Yuki Sasaki,Kabuto Arai,Jin Nakazato,Kazuki Maruta

Journal

IEICE Technical Report; IEICE Tech. Rep.

Published Date

2024/3/6

(in English) This paper proposes a user scheduling scheme for multi-user massive MIMO (MU-mMIMO), particularly effective in time-varying channel environments. MU-MIMO enables spectral efficiency enhancement by multiplexing a number of user terminals (UTs) in the spatial domain.Due to the finite number of base station (BS) antennas, the simultaneous transmission capacity is constrained in MU-MIMO. Therefore, BS must divide UTs into distinct subsets and transmit signals for each subset. When UTs move at high speed, it causes inter-user interference (IUI) and subsequently reduces the spatial multiplexing capability.

Study on the Coverage Extension of Millimeter Wave UAV BS Networks by Using IRS

Authors

Sota Yamamoto,Jin Nakazato,Gia Khanh Tran

Published Date

2024/1/6

This paper focuses on coordinating Intelligent Reflective Surfaces (IRS) and UAV networks to extend coverage while maintaining Line-of-Sight (LoS) conditions. We verify our methodology through numerical analysis in a realistically modeled 3D urban environment. Our results highlight remarkable enhancements in received SINR (Signal-to-Noise ratio) for multiple UEs with the integration of IRS. Therefore, our proposed method effectively enhances coverage in mmWave UAV networks.

Laboratory Experiment of Broad-Range Null-Steering for Millimeter-Wave V2I Multiuser MIMO

Authors

Sojin Ozawa,Yuki Sasaki,Ryo Iwaki,Jin Nakazato,Manabu Tsukada,Kazuki Maruta

Journal

IEICE Proceedings Series

Published Date

2024/3/5

This paper demonstrates the practical effectiveness of our proposed broad-range null-steering (BRNS) scheme through indoor experiment using 28-GHz band 4-element array antenna transmission system.For realization of cooperative automated driving, use of millimeter-wave band and multiuser multiple-input multiple-output (MIMO) are essential. However, inter-user interference is an challenging issue to perform spatial multiplexing under mobility environment due to outdated channel state information (CSI). BRNS was previously proposed that additionally nullifies around interfering users based on geometrical information of vehicles that can be obtained through cooperative awareness message (CAM). Its effectiveness have been confirmed through computer simulations, supposing cooperative automated operation in V2X. Our laboratory-experimental result confirms null-steering range can be expanded.

Location-Based Broad-Range Null-Steering in V2X Multiuser MIMO Transmission

Authors

Yuki Sasaki,Sojin Ozawa,Kabuto Arai,Jin Nakazato,Manabu Tsukada,Kazuki Maruta

Journal

IEEE Consumer Communications Networking Conference (CCNC2024)

Published Date

2024/1

This paper proposes an intensive null-steering around the target in angular domain to effectively suppress inter-user interference (IUI) leakage caused by channel varying environment such as vehicular multiuser spatial multiplexing. Multiuser MIMO can enhance spectral efficiency by multiplexing a number of user terminals in spatial domain. Suppose applying multiuser MIMO downlink in vehicle-to-everything (V2X) scenario, vehicles move at high speed which causes IUI. Null-space expansion has been conceived that can improve IUI suppression capability by steering nulls to the past and the present channel states on interfered users. Collective perception in intelligent transport systems (ITS) provides location information of vehicles every 100 ms. Exploiting this feature, this paper proposes angular-domain null-space expansion; broad-range null-steering (BRNS). Computer simulation verifies its effectiveness.

WebRTC over 5 G: A Study of Remote Collaboration QoS in Mobile Environment

Authors

Jin Nakazato,Kousuke Nakagawa,Koki Itoh,Romain Fontugne,Manabu Tsukada,Hiroshi Esaki

Journal

Journal of Network and Systems Management

Published Date

2024/3

The increasing demand for remote collaboration and remote working has become crucial to daily life owing to the Covid-19 pandemic and the development of internet-based video distribution services. Furthermore, low-latency remote collaboration, such as teleoperation and support applications designed for in-vehicle environments, has gained considerable attention. The 5 G technology is considered as a key infrastructure for remote collaboration. This study aimed to evaluate the actual 5 G capability to achieve high quality of service (QoS) for remote collaboration. We designed and implemented a measurement tool to monitor the QoS of remote collaboration under real-world 5 G conditions. We performed measurements encompassing the various 5 G frequency bands. During these experiments, we employed various tools to obtain detailed mobile signal conditions to analyze the relationship between various …

Location-aided fast beam tracking algorithm for millimeter-wave V2I

Authors

Sojin Ozawa,Tokio Ikuta,Yuki Sasaki,Ryo Iwaki,Jin Nakazato,Manabu Tsukada,Hideya So,Kazuki Maruta

Journal

IEICE Communications Express

Published Date

2024/5/1

This article proposes a millimeter-wave fast beam tracking algorithm for moving vehicles, considering a geometry of road environment. Focusing on the fact that vehicle movement is constrained on roads, horizontal and vertical beam directions are determined based on obtainable driving direction and road shape. In addition, we perform a two-pattern beam selection for the vehicle’s forward and rearward directions to estimate the beam tracking speed. By conducting simulations using SUMO, which emulates vehicle movement on various roads, we verified the effective operation of the proposed scheme and confirmed its superiority over the existing beam sweeping approach.

Millimeter-Wave Fast Beam Tracking Enabled by RAN/V2X Cooperation

Authors

Kazuki Maruta,Jin Nakazato,Kengo Suzuki,Hu Dou,Ryo Iwaki,Sojin Ozawa,Yuki Sasaki,Hideya So,Manabu Tsukada

Published Date

2024/2/19

Automated driving has the same limitations as human drivers because it functions as a replacement for humans and operates based on local information using onboard sensors and computers. Cooperative automated vehicles (CAVs) are expected to achieve both safety and efficiency, which could not be achieved by imitating human driving, by sharing sensor information from roadside equipment and other vehicles. Since such sensor information is enormous, it is desirable to utilize mm W, which are capable of high-capacity transmission. However, wireless communication systems for CAV have the challenge of radio quality degradation due to vehicle movement. Our research project aims to realize stable millimeter-wave transmission by incorporating open radio access network (O- RAN) and vehicle-to-everything (V2X) functions. This paper presents the overall proposed concept and an example of validation; we …

Multi-IRS-Assisted mmWave UAV-BS Network for Coverage Extension

Authors

Sota Yamamoto,Jin Nakazato,Gia Khanh Tran

Journal

Sensors

Published Date

2024/3/21

In the era of Industry 5.0, advanced technologies like artificial intelligence (AI), robotics, big data, and the Internet of Things (IoT) offer promising avenues for economic growth and solutions to societal challenges. Digital twin technology is important for real-time three-dimensional space reproduction in this transition, and unmanned aerial vehicles (UAVs) can support it. While recent studies have explored the potential applications of UAVs in nonterrestrial networks (NTNs), bandwidth limitations have restricted their utility. This paper addresses these constraints by integrating millimeter wave (mmWave) technology into UAV networks for high-definition video transmission. Specifically, we focus on coordinating intelligent reflective surfaces (IRSs) and UAV networks to extend coverage while maintaining virtual line-of-sight (LoS) conditions essential for mmWave communication. We present a novel approach for integrating IRS into Beyond 5G/6G networks to enhance high-speed communication coverage. Our proposed IRS selection method ensures optimal communication paths between UAVs and user equipment (UE). We perform numerical analysis in a realistically modeled 3D urban environment to validate our approach. Our results demonstrate significant improvements in the received SNR for multiple UEs upon the introduction of IRSs, and they confirm the feasibility of coverage extension in mmWave UAV networks.

Proof-of-Concept of Digital Twin for Road Safety Assisted by B5G Heterogeneous MEC Network

Authors

Kazuma Nonomura,Kui Wang,Gunhee Cho,Hiroki Matsuo,Jin Nakazato,Zongdian Li,Tao Yu,Kei Sakaguchi

Published Date

2024/1/6

The commercialization of 5G has been initiated for a while. Yet, we haven't seen wide penetrations of the disruptive applications as promised, like the extended reality (XR), internet of vehicles (IoV), telesurgery, etc. Digital twins (DTs) are one of these highly anticipated applications. However, DTs demand all 5G capabilities, including enhanced mobile broadband (eMBB), ultra-reliable and low latency communications (URLLC), and massive machine type communication (mMTC) simultaneously, which makes their implementation more challenging. Owing to the advanced sensing, communication, and computing networks for beyond 5G (B5G) and 6G at Tokyo Institute of Technology, we are able to build a real-time DT on campus and demonstrate two smart mobility applications for safety and traffic efficiency, respectively, by utilizing DT-derived knowledge. Our demonstrations will convince society of the values and …

RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning

Authors

Raphael Trumpp,Ehsan Javanmardi,Jin Nakazato,Manabu Tsukada,Marco Caccamo

Journal

arXiv preprint arXiv:2403.07129

Published Date

2024/3/11

The interactive decision-making in multi-agent autonomous racing offers insights valuable beyond the domain of self-driving cars. Mapless online path planning is particularly of practical appeal but poses a challenge for safely overtaking opponents due to the limited planning horizon. Accordingly, this paper introduces RaceMOP, a novel method for mapless online path planning designed for multi-agent racing of F1TENTH cars. Unlike classical planners that depend on predefined racing lines, RaceMOP operates without a map, relying solely on local observations to overtake other race cars at high speed. Our approach combines an artificial potential field method as a base policy with residual policy learning to introduce long-horizon planning capabilities. We advance the field by introducing a novel approach for policy fusion with the residual policy directly in probability space. Our experiments for twelve simulated racetracks validate that RaceMOP is capable of long-horizon decision-making with robust collision avoidance during overtaking maneuvers. RaceMOP demonstrates superior handling over existing mapless planners while generalizing to unknown racetracks, paving the way for further use of our method in robotics. We make the open-source code for RaceMOP available at http://github.com/raphajaner/racemop.

Iterative Resolution with IPv6 Packets Failing

Authors

Momoka Yamamoto,Jin Nakazato,Manabu Tsukada,Hiroshi Esaki

Published Date

2023/7/24

The exhaustion of IPv4 addresses has driven the rapid adoption of IPv6 networks, which has created challenges in the domain name resolution process, particularly for IPv6-only iterative resolvers. This paper presents an experimental analysis to quantify the extent of this problem, revealing a significantly lower success rate of name resolution using IPv6-only resolvers (64.1%) compared to IPv4-only resolvers (98.8%). By analysing the success rates and percentages of A and AAAA records for the top 1,000,000 domains in the Tranco list, we identify the limitations of IPv6-only iterative resolvers and highlight the urgent need for comprehensive solutions to improve DNS resolution in IPv6-only networks. Our findings emphasise the importance of full IPv6 adoption for improved compatibility in IPv6-only environments, and serve as a basis for addressing the challenges faced by IPv6-only networks.

Network Performance Analysis and Visualization for Cooperative Automated Driving

Authors

Koichi Kambara,Ehsan Javanmardi,Jin Nakazato,Yamada Syunya,Hiroaki Takada,Yousuke Watanabe,Kenya Sato,Manabu Tsukada

Journal

IEICE Technical Report; IEICE Tech. Rep.

Published Date

2023/2/14

(in English) In recent years, cooperative automated driving has been attracting attention to improve traffic safety and streamline traffic flow. Cooperative automated driving is a system in which an automated vehicle communicates with surrounding vehicles and roadside units installed on the road to share information and tasks that the vehicle's onboard sensors cannot recognize. One of the critical requirements for cooperative automated driving is that all vehicles receive appropriate messages at appropriate times. For this purpose, measurement and visualization of network performance are essential. Knowing the communication performance in advance allows an automated vehicle to select appropriate cognitive methods and plan its route. Therefore, we propose a communication performance analysis and visualization system that considers geographical characteristics for cooperative automated driving. The …

An Extended Kalman Filter Enabled Beam Tracking Framework in Intersection Management

Authors

Dou Hu,Jin Nakazato,Ehsan Javanmardi,Muhammad Asad,Manabu Tsukada

Journal

European Conference on Networks and Communications (EuCNC) 6G Summit

Published Date

2023/6

Recently, vehicle-to-everything (V2X) has been attracting attention for its potential to improve traffic safety and increase traffic volume worldwide, improving the accuracy of data and parameters collected from moving vehicles is widely discussed in the V2X. The most common technique of GPS may not be efficient during some specific scenarios, like some intersections full of skyscrapers, or some special terrains with obstacles. In such cases, GPS technology has a longer detection period and lower tracking accuracy, so beam tracking can be a fast and efficient solution in these circumstances. Therefore we propose an anti-diverge extend Kalman filter-enabled beam tracking method in V2X to help the intersection management. The numerical results show that our method has the ability to resist the Kalman filter’s divergence and can detect data in an accurate manner.

Flowsim: A modular simulation platform for microscopic behavior analysis of City-Scale connected autonomous vehicles

Authors

Ye Tao,Ehsan Javanmardi,Jin Nakazato,Manabu Tsukada,Hiroshi Esaki

Published Date

2023/9/24

As connected autonomous vehicles (CAVs) become increasingly prevalent, there is a growing need for simulation platforms that can accurately evaluate CAV behavior in large-scale environments. In this paper, we propose Flowsim, a novel simulator specifically designed to meet these requirements. Flowsim offers a modular and extensible architecture that enables the analysis of CAV behaviors in large-scale scenarios. It provides researchers with a customizable platform for studying CAV interactions, evaluating communication and networking protocols, assessing cybersecurity vulnerabilities, optimizing traffic management strategies, and developing and evaluating policies for CAV deployment. Flowsim is implemented in pure Python in approximately 1,500 lines of code, making it highly readable, understandable, and easily modifiable. We verified the functionality and performance of Flowsim via a series of …

協調型自動運転のためのネットワーク状態分析・可視化

Authors

神原滉一, 中里仁, 山田峻也, 高田広章, 渡辺陽介, 佐藤健哉, 塚田学

Journal

映像情報メディア学会技術報告= ITE technical report

Published Date

2023

In recent years, cooperative automated driving has been attracting attention to improve traffic safety and streamline traffic flow. Cooperative automated driving is a system in which an automated vehicle communicates with surrounding vehicles and roadside units installed on the road to share information and tasks that the vehicle’s onboard sensors cannot recognize. One of the critical requirements for cooperative automated driving is that all vehicles receive appropriate messages at appropriate times. For this purpose, measurement and visualization of network performance are essential. Knowing the communication performance in advance allows an automated vehicle to select appropriate cognitive methods and plan its route. Therefore, we propose a communication performance analysis and visualization system that considers geographical characteristics for cooperative automated driving. The system stores the communication performance of a location once passed by a vehicle in the cloud so that the next vehicle that passes by the same location can see the communication performance in advance.

Potential field-based path planning with interactive speed optimization for autonomous vehicles

Authors

Pengfei Lin,Ehsan Javanmardi,Jin Nakazato,Manabu Tsukada

Published Date

2023/10/16

Path planning is critical for autonomous vehicles (AVs) to determine the optimal route while considering constraints and objectives. The potential field (PF) approach has become prevalent in path planning due to its simple structure and computational efficiency. However, current PF methods used in AVs focus solely on the path generation of the ego vehicle while assuming that the surrounding obstacle vehicles drive at a preset behavior without the PF-based path planner, which ignores the fact that the ego vehicle's PF could also impact the path generation of the obstacle vehicles. To tackle this problem, we propose a PF-based path planning approach where local paths are shared among ego and obstacle vehicles via vehicle-to-vehicle (V2V) communication. Then by integrating this shared local path into an objective function, a new optimization function called interactive speed optimization (ISO) is designed to …

Localizability Estimation for Autonomous Driving: A Deep Learning-Based Place Recognition Approach

Authors

Kazuto Matsumoto,Ehsan Javanmardi,Jin Nakazato,Manabu Tsukada

Published Date

2023/12/11

In recent years, research and development aimed at the societal implementation of autonomous driving have attracted increasing attention. Localization, which involves obtaining information about the surrounding environment from sensor data and estimating the vehicle's position, is necessary for realizing autonomous driving. Localization based on 3D Light detection and ranging (LiDARs) and high definition (HD) maps, called map-matching, gained more attention in recent years because of its accuracy and wide availability of HD maps. In this method, the input scan from LiDAR is matched with HD map features to obtain the accurate position of the ego vehicle. However, in this method, the localization accuracy may decrease when the surrounding area does not have distinctive features. In this study, we proposed a method based on deep learning to estimate localization accuracy for autonomous driving. In …

Overcoming Environmental Challenges in CAVs through MEC-based Federated Learning

Authors

Zekun Wang,Jin Nakazato,Muhammad Asad,Ehsan Javanmardi,Manabu Tsukada

Published Date

2023/7/4

Connected autonomous vehicles (CAVs), through vehicle-to-everything communication and computing resources, enable the vital exchange of information. Although deep learning is crucial in this landscape, it requires extensive and intricate datasets covering all potential scenarios. Furthermore, this situation poses a hazard, as the likelihood of accidents associated with imbalanced datasets increases, particularly in scenarios where processing analysis is compromised due to fluctuating weather conditions. We propose a Federated Learning (FL) framework undergirded by Multi-Access Edge Computing (MEC) to counter these challenges. This local device-focused framework enhances task-specific models’ caching and continual updating across various conditions. In a more specific sense, edge nodes (ENs) operate as MEC, each caching multiple dedicated models and serving as the aggregator as part of the FL …

Semantic Digital Twin for interoperability and comprehensive management of data assets

Authors

Kazuma Inokuchi,Jin Nakazato,Manabu Tsukada,Hiroshi Esaki

Published Date

2023/6/26

Fusion of the real and virtual worlds is essential for applying digital technology to the infrastructure of human life. A digital twin is one of the technologies that aim to integrate real and virtual space. It creates a digital world with high fidelity to reality by accumulating exhaustive information from sensors to improve simulation and prediction accuracy. However, traditional digital twins have data asset management challenges owing to the physical, temporal, and structural heterogeneity of their objects. In this paper, we propose two metadata schemas that leverage semantics to construct a designer-oriented digital twin. Moreover, we implemented a viewer that reproduced the office-like demonstration field to verify the application of the proposed ontology. The proposed method enables a generic description of the dynamic behaviors of any entity by integrating physical twins faithful to the real world with virtual models …

See List of Professors in Jin Nakazato University(Tokyo Institute of Technology)

Jin Nakazato FAQs

What is Jin Nakazato's h-index at Tokyo Institute of Technology?

The h-index of Jin Nakazato has been 6 since 2020 and 6 in total.

What are Jin Nakazato's top articles?

The articles with the titles of

Optimizing mmWave Beamforming for High-Speed Connected Autonomous Vehicles: An Adaptive Approach

User Scheduling based on Expanded Null-Space for Massive MIMO

Study on the Coverage Extension of Millimeter Wave UAV BS Networks by Using IRS

Laboratory Experiment of Broad-Range Null-Steering for Millimeter-Wave V2I Multiuser MIMO

Location-Based Broad-Range Null-Steering in V2X Multiuser MIMO Transmission

WebRTC over 5 G: A Study of Remote Collaboration QoS in Mobile Environment

Location-aided fast beam tracking algorithm for millimeter-wave V2I

Millimeter-Wave Fast Beam Tracking Enabled by RAN/V2X Cooperation

...

are the top articles of Jin Nakazato at Tokyo Institute of Technology.

What are Jin Nakazato's research interests?

The research interests of Jin Nakazato are: wireless communication, edge computing, Heterogeneous Networks, Mobile Edge Computing, Multi-Access

What is Jin Nakazato's total number of citations?

Jin Nakazato has 112 citations in total.

What are the co-authors of Jin Nakazato?

The co-authors of Jin Nakazato are Kei Sakaguchi, Gia Khanh Tran, Tao YU.

    Co-Authors

    H-index: 27
    Kei Sakaguchi

    Kei Sakaguchi

    Tokyo Institute of Technology

    H-index: 17
    Gia Khanh Tran

    Gia Khanh Tran

    Tokyo Institute of Technology

    H-index: 10
    Tao YU

    Tao YU

    Tokyo Institute of Technology

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