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Mohammad Abrar Shakil Sejan - IEEE Xplore Author Profile
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Mohammad Abrar Shakil Sejan

Publications
2
Citations
4
Publications by Year
20242024
Co-Authors:
Show All Co-Authors (6)
Image of author Mohammad Abrar Shakil Sejan

Mohammad Abrar Shakil Sejan

Affiliation

Department of Electrical Engineering
Sejong University
Seoul, Republic of Korea

Publication Topics

Biography

Mohammad Abrar Shakil Sejan received the B.S. and M.S. degrees in computer science and engineering from Islamic University, Kushtia, Bangladesh, in 2014 and 2016, respectively, and the Ph.D. degree in electronic engineering from Pukyong National University, Busan, Republic of Korea, in February 2022. Currently, he is a Postdoctoral Fellow with the Information and Communication Engineering Department and the Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul, Republic of Korea. His research interests include visible light communication, optical communication, wireless sensor networks, reconfigurable intelligent surfaces, protocol design for communication, modulation techniques in VLC, and the IoT applicatio...
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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