5 citations · 11 across the 6 of their papers we have counts for
19 papers · 1 filter
A Survey on Machine and Deep Learning for Optical Communications
M. A. Amirabadi, S. A. Nezamalhosseini, M. H. Kahaei +1
The ever-growing complexity of optical communication systems and networks demands sophisticated methodologies to extract meaningful insights from vast amounts of heterogeneous data…
Joint Power and Gain Allocation in MDM-WDM Optical Communication Networks Based on Enhanced Gaussian Noise Model
Mohammad Ali Amirabadi, Mohammad Hossein Kahaei, S. Alireza Nezamalhosseini
Achieving reliable communication over different channels and modes is one of the main goals of Mode Division Multiplexing-Wavelength Division Multiplexing (MDM-WDM) communication n…
Deep Reinforcement Learning-based Anti-jamming Power Allocation in a Two-cell NOMA Network
Sina Yousefzadeh Marandy, Mohammad Ali Amirabadi, Mohammad Hossein Kahaei +1
The performance of Non-orthogonal Multiple Access (NOMA) system dramatically decreases in the presence of inter-cell interference. This condition gets more challenging if a smart j…
Three novel efficient Deep Learning-based approaches for compensating atmospheric turbulence in FSO communication system
M. A. Amirabadi
One of the main problems encountered with Free Space Optical (FSO) Communication system is the atmospheric turbulence. Although many solutions exist for combating this effect, they…
Deep learning for channel estimation in FSO communication system
M. A. Amirabadi
Perfect channel estimation is very hard, time/ power consuming, and expensive; so it is not preferred (e.g. in mobile) communication systems. This paper seeks for new, cheap, low c…
A deep learning based solution for imperfect CSI problem in correlated FSO communication channel
M. A. Amirabadi
Imperfect channel state information (CSI) at the receiver, which is due to channel estimation error, is one of the main problems toward achieving optimum detection. This paper pres…