Research Experience

  • Assistant Doctorant, SnT, University of Luxembourg        [Sep 2020 - Mar 2023]
    • Adviser: Dr. Shree Krishna Sharma
    • Research areas: Machine Learning, 5G URLLC, Tactile Internet.
  • Graduate Research Assistant, MNL, Inha University         [Mar 2018 - Present]
    • Thesis: Q-Learning Based Multi-Objective Clustering Algorithm for Cognitive Radio Ad Hoc Networks
    • Adviser: Professor Sang Jo-Yoo
    • Research areas: Cognitive Radio Ad-hoc Networks, Machine Learning.
  • Undergraduate Research Student, Department of ETE, RUET   [Dec 2012 - Dec 2014]
    • Thesis: Effect of signal length in cross-correlation based underwater network size estimation
    • Adviser: Shah Ariful Hoque Chowdhury
    • Research areas: Underwater Wireless Sensor Network.
    • Project: Ultrasonic Proximity Detector

Publications

  1. Md Arman Hossen, and Sang-Jo Yoo, “Q-Learning–Based Multi-Objective Clustering Algorithm for Cognitive Radio Ad-Hoc Networks,” Published in IEEE access Journal (IF: 4.098). [PDF]
  2. Md Arman Hossen, and Sang-Jo Yoo,“Cognitive Radio Network Clustering using Reinforcement Learning,” Korean Institute of Communication Sciences Summer Conference, 2019.6 [PDF]
  3. Md Arman Hossen, S. A. H. Chowdhury, M. S. Anower, S. Hossen, M. F. Pervej, and M. M. Hasan, “Effect of Signal Length in Cross-correlation based Underwater Network Size Estimation,” 2nd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), Savar, Dhaka, Bangladesh, May 2015. [PDF]
  4. M. M. Hasan, A. Paul, S. A. H. Chowdhury, M. F. Pervej, Md Arman Hossen, “Effect of node number in range based node localization technique for underwater communications network,” 17th International Conference on Computer and Information Technology (ICCIT), pp: 413 - 417, Dhaka, Bangladesh, December 2014. [PDF]
  5. M. F. Pervej, T. K. Roy, M. Z. I. Sarker, and Md Arman Hossen, “PAPR Reduction and BER Performance Analysis of SC-FDMA System using DFT and DCT Methods,” in the conference proceedings of 9th international conference of International Forum on Strategic Technology (IFOST), Cox’s Bazar, Bangladesh [PDF]

Research Interests

  • 5G and beyond wireless communication systems
  • Machine Learning
  • Tactile internet
  • 5G URLLC
  • Edge Computing


Work in Progress

  1. Q-learning based resource allocation in 5G wireless commuication
  2. Reinforcement learning based latency minimization in 5G URLLC.
  3. MARL based Grant-free NOMA.

Skills

  • Programming Languages: Python, MATLAB, C (Elementary).
  • Statistical Analysis: Numpy, Scipy, Statsmodels, Scikit-learn.
  • Data Visualization: Matplotlib, Seaborn, Plotly.
  • Dataframe Manipulation: Pandas.
  • Deeplearning Frameworks: Tensorflow (Keras).
  • Development Tools: Jupyter Notebook, PyCharm, Git.