Akhtar Husain

Work place: Department of Computer Science & Information Technology, Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 243006, India

E-mail: akhtarhusain@mjpru.ac.in


Research Interests: Communications, Wireless Communication, Wireless Networks


Akhtar Husain received his B.E. degree in Computer Science & Engineering from Uttarakhand Technical University, Dehradun, India in 1996 and M.Tech in Computer Science & Engineering from NITTTR, Panjab University, Chandigarh, India in 2009. He received the Ph.D. from Indian Institute of Technology (IIT Roorkee), Roorkee, India in 2017. He is currently an Associate Professor with the Department of Computer Science & Engineering at MJP Rohilkhand University, Bareilly, Uttar Pradesh, India, India. His research interests include Fuzzy Logic, Cloud Computing, Wireless Communication.

Author Articles
Reinforcement Learning Based Efficient Power Control and Spectrum Utilization for D2D Communication in 5G Network

By Chellarao Chowdary Mallipudi Saurabh Chandra Prateek Prateek Rajeev Arya Akhtar Husain Shamimul Qamar

DOI: https://doi.org/10.5815/ijcnis.2023.04.02, Pub. Date: 8 Aug. 2023

There are billions of inter-connected devices by the help of Internet-of-Things (IoT) that have been used in a number of applications such as for wearable devices, e-healthcare, agriculture, transportation, etc. Interconnection of devices establishes a direct link and easily shares the information by utilizing the spectrum of cellular users to enhance the spectral efficiency with low power consumption in an underlaid Device-to-Device (D2D) communication. Due to reuse of the spectrum of cellular devices by D2D users causes severe interference between them which may impact on the network performance. Therefore, we proposed a Q-Learning based low power selection scheme with the help of multi-agent reinforcement learning to detract the interference that helps to increase the capacity of the D2D network. For the maximization of capacity, the updated reward function has been reformulated with the help of a stochastic policy environment. With the help of a stochastic approach, we figure out the proposed optimal low power consumption techniques which ensures the quality of service (QoS) standards of the cellular devices and D2D users for D2D communication in 5G Networks and increase the utilization of resources. Numerical results confirm that the proposed scheme improves the spectral efficiency and sum rate as compared to Q-Learning approach by 14% and 12.65%.

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