Professor Chao-Kai Wen

Institute of Communications Engineering, Department of Electrical Engineering (joint appointment), Department of Applied Mathematics (joint appointment)

National Sun Yat-sen University, Kaohsiung, Taiwan 804, R.O.C Email: chaokai.wen@mail Please append ".nsysu.edu.tw" to the end of the email.

Hi! I am a Professor of the Institute of Communications Engineering at National Sun Yat-sen University (NSYSU) in Taiwan. I received my Ph.D. from the Institute of Communications Engineering, National Tsing Hua University, Taiwan, in 2004. After obtaining my Ph.D., I spent five years in the industry, working with organizations like the Industrial Technology Research Institute and MediaTek Inc. in Taiwan, before joining NSYSU in 2009. During this period, I specialized in designing wideband digital transceivers.

My research spans multiple disciplines, encompassing communication technology, signal processing, data analysis, and the development of prototypes. I am deeply committed to converting research into practical prototypes and testbeds, many of which have been incorporated by the industry. My work has earned me several industry-university cooperation awards from NSYSU. Additionally, my publications have garnered numerous awards, such as the Best Paper Award at IEEE GLOBECOM 2016, WCSP 2019, IEEE ICC 2022, and the 2023 IEEE Jack Neubauer Memorial Award. I was recognized as one of the Highly Cited Researchers™ by Clarivate and honored as an IEEE Fellow for my contributions to deep learning technology in wireless systems.

In academia, I serve as an editor for prestigious journals, including IEEE Transactions on Wireless Communications, IEEE Transactions on Communications, IEEE Communications Letters, and IEEE Wireless Communications Letters. My editorial work has been recognized with the IEEE COMML Editor Award in 2018, 2021, and 2022, and the 2020 IEEE WCL Best Editor Award. In a leadership capacity, I served as the Director of the Institute of Communication (2018-2021) and as the Vice Dean of the College of Engineering (2020-2023) at NSYSU. Currently, I am the Chair of the IEEE Communications Society Tainan Chapter, a role I have held since 2024, following my tenure as Vice Chair (2022-2023) and my involvement as Vice Chair of the IEEE Broadcast Technology Society Tainan Chapter from 2013 to 2023.

My current research interests are in

Massive MIMO & MIMO testbeds
Deep learning for wireless physical layer (Overview in IEEE Wireless Communications)
Compressed sensing
Smart grid
Secrecy in communication.

News

26 July, 2024

End-User-Centric Collaborative MIMO Demo for 6G Advanced Academic Research Project Results

The trend of using larger antenna arrays continues, but space constraints on user equipment (UE) in FR1 limit user capacity scaling. To address this, we propose UE-CoMIMO, a user-centric collaborative MIMO approach forming a virtual antenna array with multiple fixed or portable devices.
The UE-CoMIMO system (256QAM, 100MHz bandwidth) offers impressive performance, including:

- Compliance with the 5G NR frame structure;

- A base station with 4 spatial atreams;

- A primary UE with 8 antennas (4 at 3.65 GHz and 4 at 7.65 GHz);

- A collaborative UE with 4 antennas for both frequency bands.

For more details, please refer to the following paper.

[ArXiv] End-User-Centric Collaborative MIMO: Performance Analysis and Proof of Concept

24 Aug., 2023

Call for Papers: Digital Twins Meet Artificial Intelligence in 6G

As Guest Editors of IEEE Communication Magazine, along with Xingqin Lin, Jun Zhang, and Hadis Karimipour, we invite your original research submissions for our Special Issue on "Digital Twins and Artificial Intelligence in 6G".

08 Aug., 2023

[arXiv:2308.03016], [IEEE Xplore] Shaping a Smarter Electromagnetic Landscape: IAB, NCR, and RIS in 5G Standard and Future 6G

Enhancing user experience in data speed and reliability is the focus of 5G and beyond networks. Innovations like wireless backhaul and relays are replacing traditional macro base stations. The article summarizes 5G features and ongoing 3GPP Release 18 developments related to intelligent EM entities like IAB, NCR, and RIS. It outlines the expected evolution of wireless networks in architecture, operations, and control signals.

19 July, 2023

Active RIS-Assisted MIMO-OFDM System@FR3 Demo for 6G Advanced Academic Research Project Results

Active RIS-assisted MIMO-OFDM Prototype Conforming to the 5G New Radio Waveform:

- 4x4 MIMO-OFDM System (256QAM, 100MHz Bandwidth, 7.025GHz Carrier Frequency)

- 4 Transmit Antennas on Femtocell Base Station, 4 Receive Antennas on a Compact Phone (8cm x 15cm)

- 4x4 Active RIS (13cm x 13cm)

For more detailed information, please consult the following paper (Please note that the experiments in the paper were conducted at 3.5GHz, while the above demonstration operates at 7GHz) and demo video.

[IEEE Xplore], [Demo Video] Active RIS-Assisted MIMO-OFDM System: Analyses and Prototype Measurements

21 May, 2023

UE-CoMIMO: MIMO Evolution Towards 6G

In 6G, limited space in user equipment (UE) hinders the installation of additional antennas, limiting capacity scaling for end-users. To address this, we propose UE-CoMIMO, a collaborative MIMO framework that groups devices to create virtual antennas.
[IEEE Xplore] MIMO Evolution toward 6G: End-User-Centric Collaborative MIMO
[RWS-230111] Device collaborative Tx and Rx, MediaTek Inc., 3GPP RAN-Release 19 Workshop (2023-06-15 - Taipei)

16 February, 2023

8T12R MIMO OFDM @ 7GHz for Taiwan's 6G Academic Research Project

8-spatial-stream MIMO on compact terminals operating at mid-high frequency (7.045GHz) achieves a spectral efficiency of 56 bps/Hz in an indoor open environment, utilizing a 100MHz bandwidth and 1024QAM modulation.
3.5 times higher than the current 4x4 MIMO spectral efficiency of 5G NR at the 3.5GHz frequency band, which is approximately 15 bps/Hz.

13 January, 2023

Hybrid Active-Passive RIS-Aided 4T4R "MIMO" for 5G NR

5G NR at 3.5 GHz
4T4R MIMO OFDM
4 patch antennas at BS, 4 Rx antennas on a compact phone (8cm x 15 cm)
4x4 Hybrid Active-Passive RIS (16cm x 26cm)
5 dB increase in SNR and a 20% increase in spectral efficiency

28 October, 2022

DL-Based CSI Feedback in Massive MIMO Systems

Our paper "Overview of Deep Learning-Based CSI Feedback in Massive MIMO Systems" has been published in IEEE Transactions on Communications. In this paper, we give a detailed overview of the latest research on this topic.
"AI for CSI Feedback Enhancement in 5G-Advanced" has been published in IEEE Wireless Communications. This paper focuses on how industry is using AI to improve feedback for communication systems, specifically as it relates to the new 5G-Advanced standard.

December, 2021

CSI Feedback with Autoencoders

Our proposed method, CsiNet, opens a new avenue in the field of CSI Feedback by incorporating the use of Autoencoders. [Python & Matlab in GitHub]
(RAN#94-e, Dec. 2021) In December 2021, 3GPP approved the Release-18 package at the RAN Plenary meeting. The package included a study item (RP-213599)-Artificial intelligence (AI)/machine learning (ML) for NR air interface. This study item will focus on three identified use cases, including CSI feedback, beam management, and positioning.
MathWorks has included CsiNet in MATLAB 2022b toolbox (Aug. 2022).

8 December, 2020

mmWave Fast Antenna and Beam Switching OTA Demo at GLOBECOM 2020

mmWave smartphone with two subarrays at the 28 GHz
5G NR Frame Structure with beam management (Rel-15)
100 MHz channel width
Modulations from QPSK to 256-QAM
Fast antenna and beam switching (Fast-ABS) mechanism: Using the information of a single receiving array module to predict the receiving performance of other array modules. When the receiving module is blocked, Fast-ABS can quickly perform module and beam switching.

2 September, 2020

12x12 MIMO-OFDM OTA Demo at Taipei Nangang Exhibition Center for MOST B5G/6G Wireless Network Research Project

12x12 MIMO-OFDM based on 5G NR frame structure (Rel. 15)
12- Rx antennas in a compact smartphone for the 3.5 GHz
12-Tx spatial streams over 2 distributed BSs
100 MHz channel width
64-QAM
Achieving 42.9 bps/Hz spectral efficiency on a 5.5 inch screens compact smartphone by using

1) Precoding over two distributed BSs,

2) Smart channel estimator with environment sensing,

3) AI-aided MIMO detector,

4) Joint MIMO detector and LDPC decoder (JDD)

14-17 January, 2020

mmWave Fast Antenna and Beam Switching OTA Demo at 2020 Taiwan Telecommunications Annual Symposium

mmWave smartphone with two subarrays for the 28 GHz
NR Frame Structure (Release 15)
100 MHz channel width
From QPSK to 256-QAM
Fast antenna and beam switching (Fast-ABS) mechanism
Efficient and seamless connectivity under hand blockage

24-26 January, 2019

mmWave Beam Tracking OTA Demo at 2019 Taiwan Telecommunications Annual Meeting

mmWave antenna system in a smartphone for the 28 GHz
NR Frame Structure (Release 15)
100 MHz channel width
256-QAM and 1204-QAM
Fast beam tracking mechanism
Support various performance measurement (e.g., EVM, SNR, throughput, beam pattern )

3 August, 2018

20x16 (or 16x16) MIMO OTA Demo

20 (or 16)-antenna array in the compact smartphone for the 3.5 GHz
16 spatial streams
100 MHz channel width
256-QAM for 20-antennas (or 64QAM for 16-antennas)
62.4 bps/Hz (or 49.7 bps/Hz) spectral efficiency on a compact smartphone with 5.5 inch screens

12 December, 2017

20x14 MIMO OTA Demo at 2017 Industry Outlook Technology Forum

20-antenna array in the compact smartphone for the 3.5 GHz
14 spatial streams
100 MHz channel width
256-QAM
59.5 bps/Hz spectral efficiency on a compact smartphone with 5.5 inch screens

11 August, 2017

16x12 MIMO OTA Demo at 2017 IAET Summer Seminar

16-antenna array in the compact smartphone for the 3.5 GHz
12 spatial streams
100 MHz channel width
256-QAM
53.41 bps/Hz spectral efficiency

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