7 citations · 18 across the 9 of their papers we have counts for
12 papers
On the Adversarial Vulnerability of Neural Receivers with Unrolled LDPC Decoders
Aakash Saini, Jafar Aco Mohammadi, Wolfgang Gerstacker
Neural receivers for 5G New Radio (NR) match classical model-based receivers in link-level performance, but their robustness to adversarial perturbations at the receiver input rema…
Waveform Learning under Phase Noise Impairment for Sub-THz Communications
Dileepa Marasinghe, Le Hang Nguyen, Jafar Mohammadi +3
The large untapped spectrum in sub-THz allows for ultra-high throughput communication to realize many seemingly impossible applications in 6G. Phase noise (PN) is one key hardware…
Constellation Shaping under Phase Noise Impairment for Sub-THz Communications
Dileepa Marasinghe, Le Hang Nguyen, Jafar Mohammadi +3
The large untapped spectrum in the sub-THz allows for ultra-high throughput communication to realize many seemingly impossible applications in 6G. One of the challenges in radio co…
Minimizing Energy Consumption in MU-MIMO via Antenna Muting by Neural Networks with Asymmetric Loss
Nuwanthika Rajapaksha, Jafar Mohammadi, Stefan Wesemann +2
Transmit antenna muting (TAM) in multiple-user multiple-input multiple-output (MU-MIMO) networks allows reducing the power consumption of the base station (BS) by properly utilizin…
Blind Coherent Preamble Detection via Neural Networks
Jafar Mohammadi, Gerhard Schreiber, Thorsten Wild +1
In wireless communications systems, the user equipment (UE) transmits a random access preamble sequence to the base station (BS) to be detected and synchronized. In standardized ce…
Interference Prediction for Low-Complexity Link Adaptation in Beyond 5G Ultra-Reliable Low-Latency Communications
Alessandro Brighente, Jafar Mohammadi, Paolo Baracca +2
Traditional link adaptation (LA) schemes in cellular network must be revised for networks beyond the fifth generation (b5G), to guarantee the strict latency and reliability require…
Turbo-AI: Iterative Machine Learning Based Channel Estimation for 2D Massive Arrays
Yejian Chen, Jafar Mohammadi, Stefan Wesemann +1
Recently, Machine Learning (ML) is recognized as an effective tool for wireless communications and plays an evolutionary role to enhance Physical Layer (PHY) of 5th Generation (5G)…
Interference Distribution Prediction for Link Adaptation in Ultra-Reliable Low-Latency Communications
Alessandro Brighente, Jafar Mohammadi, Paolo Baracca
The strict latency and reliability requirements of ultra-reliable low-latency communications (URLLC) use cases are among the main drivers in fifth generation (5G) network design. L…
Improved Differentially Private Decentralized Source Separation for fMRI Data
Hafiz Imtiaz, Jafar Mohammadi, Rogers Silva +4
Blind source separation algorithms such as independent component analysis (ICA) are widely used in the analysis of neuroimaging data. In order to leverage larger sample sizes, diff…
Distributed Differentially Private Computation of Functions with Correlated Noise
Hafiz Imtiaz, Jafar Mohammadi, Anand D. Sarwate
Many applications of machine learning, such as human health research, involve processing private or sensitive information. Privacy concerns may impose significant hurdles to collab…
Strong Secrecy and Stealth for Broadcast Channels with Confidential Messages
Igor Bjelakovic, Jafar Mohammadi, Sławomir Stańczak
We consider a discrete memoryless broadcast channel consists of two users and a sender. The sender has two independent confidential messages for each user. We extend the work of Li…
A Simple Algorithm for Approximation by Nomographic Functions
Steffen Limmer, Jafar Mohammadi, Slawomir Stanczak
This paper introduces a novel algorithmic solution for the approximation of a given multivariate function by a nomographic function that is composed of a one-dimensional continuous…