activity
20192022
most citedChannel Estimation for RIS-Aided mmWave MIMO Channels

28 citations · 32 across the 13 of their papers we have counts for

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10 papers · 1 filter

eess.SP2022

Joint Estimation of Clustered User Activity and Correlated Channels with Unknown Covariance in mMTC

Hamza Djelouat, Markus Leinonen, Markku Juntti

This paper considers joint user identification and channel estimation (JUICE) in grant-free access with a \emph{clustered} user activity pattern. In particular, we address the JUIC…

eess.SP2022

Joint Coherent and Non-Coherent Detection and Decoding Techniques for Heterogeneous Networks

Leatile Marata, Onel Luis Alcaraz López, Hamza Djelouat +3

Cellular networks that are traditionally designed for human-type communication (HTC) have the potential to provide cost effective connectivity to machine-type communication (MTC).…

eess.SP20224 cited

On-Demand AoI Minimization in Resource-Constrained Cache-Enabled IoT Networks with Energy Harvesting Sensors

Mohammad Hatami, Markus Leinonen, Zheng Chen +2

We consider a resource-constrained IoT network, where multiple users make on-demand requests to a cache-enabled edge node to send status updates about various random processes, eac…

eess.SP2021

Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

Abolfazl Zakeri, Mohammad Moltafet, Markus Leinonen +1

We consider a multi-source relaying system where the sources independently and randomly generate status update packets which are sent to the destination with the aid of a bufferaid…

eess.SP2021

Exploiting Spatial Correlation for Pilot Reuse in Single-Cell mMTC

Lucas Ribeiro, Markus Leinonen, Hanan Al-Tous +2

As a key enabler for massive machine-type communications (mMTC), spatial multiplexing relies on massive multiple-input multiple-output (mMIMO) technology to serve the massive numbe…

eess.SP2021

Iterative Reweighted Algorithms for Joint User Identification and Channel Estimation in Spatially Correlated Massive MTC

Hamza Djelouat, Markus Leinonen, Markku Juntti

Joint user identification and channel estimation (JUICE) is a main challenge in grant-free massive machine-type communications (mMTC). The sparse pattern in users' activity allows…