• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    02/06/2020: ThS. Nguyễn Văn Lý (San Diego State Univ., US), SVM-based Channel Estimation and Data Detection for Massive MIMO Systems with One-Bit ADCs

    The use of low-resolution Analog-to-Digital Converters (ADCs) is a practical solution for reducing cost and power consumption for massive Multiple-Input Multiple-Output (MIMO) systems. However, the severe nonlinearity of low-resolution ADCs causes significant distortions in the received signals and makes the channel estimation and data detection tasks much more challenging. In this talk, we show how Support Vector Machine (SVM), a well-known supervised learning technique in machine learning can be exploited to provide efficient and robust channel estimation and data detection in massive MIMO systems with one-bit ADCs. First, we propose SVM-based channel estimation methods for both uncorrelated and spatially correlated channels. Next, a two-stage detection algorithm is proposed where SVM is further exploited in the first stage. We also propose an SVM-based Joint Channel Estimation and Data Detection (CE-DD) method and an extension to OFDM systems with frequency-selective fading channels. Simulation results show that the proposed methods are efficient, robust, and also outperform existing ones.

    Speaker: Mr. Nguyen Van Ly, San Diego State Univ.

    Time: 15:30, Tuesday, June 02, 2020

    Venue: Webinar – Microsoft Teams


    Ly V. Nguyen received the B.Eng. degree in electronics and telecommunications from the University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam, in 2014, and the M.Sc. degree in advanced wireless communications systems from The CentraleSupélec, University of Paris-Saclay, France, in 2016. He is currently pursuing a Ph.D. degree in a joint doctoral program in computational science with San Diego State University and The University of California, Irvine, CA, USA. He received a Best Paper Award at the IEEE ICC 2020 as the first author. His research interests include wireless communications, signal processing, and machine learning.


    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]