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Md Abdul Aziz - IEEE Xplore Author Profile
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Md Abdul Aziz

Publications
2
Citations
4
Publications by Year
20242024
Co-Authors:
Show All Co-Authors (6)
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Md Abdul Aziz

Affiliation

Department of Information and Communication Engineering
Sejong University
Seoul, Republic of Korea
Department of Convergence Engineering for Intelligent Drone
Sejong University
Seoul, Republic of Korea

Publication Topics

Biography

Md Abdul Aziz (Graduate Student Member, IEEE) received the B.S. and M.S. degrees in electrical and electronic engineering from Islamic University, Kushtia, Bangladesh, in 2014 and 2016, respectively. He is currently pursuing the Ph.D. degree with the Department of Information and Communication Engineering and the Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul, Republic of Korea. His research interests include machine learning, wireless communication, and intelligent reflective surfaces.(Based on document published on 6 May 2024).
Publications
2
Citations
4
Publications by Year
20242024
Co-Authors:
Show All Co-Authors (6)
Author's Published Works

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Bidirectional Deep Learning Decoder for Polar Codes in Flat Fading Channels

Md Abdul Aziz;Md Habibur Rahman;Mohammad Abrar Shakil Sejan;Rana Tabassum;Duck-Dong Hwang;Hyoung-Kyu Song

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
Cited by: Papers (1)
One of the main issues facing in the future wireless communications is ultra-reliable and low-latency communication. Polar codes are well-suited for such applications, and recent advancements in deep learning have shown promising results in enhancing polar code decoding performance. We propose a robust decoder based on a bidirectional long short-term memory (Bi-LSTM) network, which processes seque...Show More

Bidirectional Deep Learning Decoder for Polar Codes in Flat Fading Channels

Md Abdul Aziz;Md Habibur Rahman;Mohammad Abrar Shakil Sejan;Rana Tabassum;Duck-Dong Hwang;Hyoung-Kyu Song

Year: 2024 | Volume: 12 | Journal Article |

Deep Learning Based One Bit-ADCs Efficient Channel Estimation Using Fewer Pilots Overhead for Massive MIMO System

Md Habibur Rahman;Mohammad Abrar Shakil Sejan;Md Abdul Aziz;Rana Tabassum;Jung-In Baik;Hyoung-Kyu Song

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
Cited by: Papers (3)
The massive MIMO approach presents an exciting prospect for the upcoming generation of wireless transmission systems. However, the adoption of actual massive MIMO scenarios is hindered by high hardware expenses and increased energy usage, particularly as the quantity of RF modules expands. To address this issue and make massive MIMO more commercially viable, the design of 1-bit analog-to-digital c...Show More

Deep Learning Based One Bit-ADCs Efficient Channel Estimation Using Fewer Pilots Overhead for Massive MIMO System

Md Habibur Rahman;Mohammad Abrar Shakil Sejan;Md Abdul Aziz;Rana Tabassum;Jung-In Baik;Hyoung-Kyu Song

Year: 2024 | Volume: 12 | Journal Article |

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