activity
20182023
most citedDeep Learning Based Sphere Decoding

89 citations · 138 across the 12 of their papers we have counts for

collaborators

13 papers

eess.SP2023

Cooperative Sense and Avoid for UAVs using Secondary Radar

Mostafa Mohammadkarimi, Raj Thilak Rajan

A cooperative Sense and Avoid (SAA) algorithm for safe navigation of small-sized UAVs within an airspace is proposed in this paper. The proposed method relies upon cooperation betw…

cs.IT2023

Low Complexity Time Synchronization for Zero-padding based Waveforms

Koosha Pourtahmasi Roshandeh, Mostafa Mohammadkarimi, Masoud Ardakani

The discussion on using zero padding (ZP) instead of a cyclic prefix (CP) for enhancing channel estimation and equalization performance is a recurring topic in waveform design for…

cs.IT2023★ 9 cited

Maximum Likelihood Time Synchronization for Zero-padded OFDM

Koosha Pourtahmasi Roshandeh, Mostafa Mohammadkarimi, Masoud Ardakani

Existing Orthogonal Frequency-Division Multiplexing (OFDM) variants based on cyclic prefix (CP) allow for efficient time synchronization, but suffer from lower power efficiency com…

eess.SP2022

Activity Detection for Grant-Free NOMA in Massive IoT Networks

Mehrtash Mehrabi, Mostafa Mohammadkarimi, Masoud Ardakani

Recently, grant-free transmission paradigm has been introduced for massive Internet of Things (IoT) networks to save both time and bandwidth and transmit the message with low laten…

eess.SY2022★ 9 cited

Artificial Potential Field-Based Path Planning for Cluttered Environments

Mosab Diab, Mostafa Mohammadkarimi, Raj Thilak Rajan

In this paper, we study path planning algorithms of resource constrained mobile agents in unknown cluttered environments, which include but are not limited to various terrestrial m…

eess.SY2022★ 5 cited

Joint Ranging and Phase Offset Estimation for Multiple Drones using ADS-B Signatures

Mostafa Mohammadkarimi, Geert Leus, Raj Thilak Rajan

A new method for joint ranging and Phase Offset (PO) estimation of multiple drones/aircrafts is proposed in this paper. The proposed method employs the superimposed uncoordinated A…

cs.IT2022★ 3 cited

Efficient Massive Machine Type Communication (mMTC) via AMP

Mostafa Mohammadkarimi, Masoud Ardakani

We propose efficient and low-complexity multiuser detection (MUD) algorithms for Gaussian multiple access channel (G-MAC) for short-packet transmission in massive machine type comm…

cs.IT2020★ 16 cited

Massive Uncoordinated Multiple Access for Beyond 5G

Mostafa Mohammadkarimi, Octavia A. Dobre, Moe Z. Win

Existing wireless communication systems have been mainly designed to provide substantial gain in terms of data rates. However, 5G and Beyond will depart from this scheme, with the…

eess.SP2020★ 1 cited

An Approximate Maximum Likelihood Time Synchronization Algorithm for Zero-padded OFDM in Channels with Impulsive Gaussian Noise

Koosha Pourtahmasi Roshandeh, Mostafa Mohammadkarimi, Masoud Ardakani

In wireless communication systems, Orthogonal Frequency-Division Multiplexing (OFDM) includes variants using either a cyclic prefix (CP) or a zero padding (ZP) as the guard interva…

eess.SP2019★ 3 cited

Decision Directed Channel Estimation Based on Deep Neural Network k-step Predictor for MIMO Communications in 5G

Mehrtash Mehrabi, Mostafa Mohammadkarimi, Masoud Ardakani +1

We consider the use of deep neural network (DNN) to develop a decision-directed (DD)-channel estimation (CE) algorithm for multiple-input multiple-output (MIMO)-space-time block co…

cs.IT2018★ 3 cited

Signature-based Non-orthogonal Multiple Access (S-NOMA) for Massive Machine-Type Communications in 5G

Mostafa Mohammadkarimi, Muhammad Ahmad Raza, Octavia A. Dobre

The problem of providing massive connectivity in Internet-of-Things (IoT) with a limited number of available resources motivates the non-orthogonal multiple access (NOMA) solutions…

eess.SP2018★ 89 cited

Deep Learning Based Sphere Decoding

Mostafa Mohammadkarimi, Mehrtash Mehrabi, Masoud Ardakani +1

In this paper, a deep learning (DL)-based sphere decoding algorithm is proposed, where the radius of the decoding hypersphere is learned by a deep neural network (DNN). The perform…

eess.SP2018

Doppler Spread Estimation in MIMO Frequency-selective Fading Channels

Mostafa Mohammadkarimi, Ebrahim Karami, Octavia A. Dobre +1

One of the main challenges in high-speed mobile communications is the presence of large Doppler spreads. Thus, accurate estimation of maximum Doppler spread (MDS) plays an importan…