activity
20192022
most citedLearning the Wireless V2I Channels Using Deep Neural Networks

6 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2021

Thinking Out of the Blocks: Holochain for Distributed Security in IoT Healthcare

Shakila Zaman, Muhammad R. A. Khandaker, Risala T. Khan +2

The Internet-of-Things (IoT) is an emerging and cognitive technology which connects a massive number of smart physical devices with virtual objects operating in diverse platforms t…

eess.SP2020

Truly Intelligent Reflecting Surface-Aided Secure Communication Using Deep Learning

Yizhuo Song, Muhammad R. A. Khandaker, Faisal Tariq +2

This paper considers machine learning for physical layer security design for communication in a challenging wireless environment. The radio environment is assumed to be programmabl…

eess.SP20196 cited

Learning the Wireless V2I Channels Using Deep Neural Networks

Tian-Hao Li, Muhammad R. A. Khandaker, Faisal Tariq +2

For high data rate wireless communication systems, developing an efficient channel estimation approach is extremely vital for channel detection and signal recovery. With the trend…

eess.SP20193 cited

Deep Neural Network Based Resource Allocation for V2X Communications

Jin Gao, Muhammad R. A. Khandaker, Faisal Tariq +2

This paper focuses on optimal transmit power allocation to maximize the overall system throughput in a vehicle-to-everything (V2X) communication system. We propose two methods for…

cs.NI2019

A Speculative Study on 6G

Faisal Tariq, Muhammad Khandaker, Kai-Kit Wong +3

While 5G is being tested worldwide and anticipated to be rolled out gradually in 2019, researchers around the world are beginning to turn their attention to what 6G might be in 10+…