activity
20222026
most citedVEDLIoT: Very Efficient Deep Learning in IoT

13 citations · 28 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2026

Vehicular Wireless Positioning -- A Survey

Sharief Saleh, Satyam Dwivedi, Russ Whiton +9

The rapid advancement of connected and autonomous vehicles has driven a growing demand for precise and reliable positioning systems capable of operating in complex environments. Me…

eess.SP2024★ 2 cited

Fundamental Trade-Offs in Monostatic ISAC: A Holistic Investigation Towards 6G

Musa Furkan Keskin, Mohammad Mahdi Mojahedian, Jesus O. Lacruz +5

This paper undertakes a holistic investigation of two fundamental trade-offs in monostatic OFDM integrated sensing and communication (ISAC) systems-namely, the time-frequency trade…

eess.SP2023★ 2 cited

Integrated Sensing and Communications with MIMO-OTFS

Musa Furkan Keskin, Carina Marcus, Olof Eriksson +3

Orthogonal time frequency space (OTFS) is a promising alternative to orthogonal frequency division multiplexing (OFDM) for high-mobility communications. We propose a novel multiple…

cs.AR2023★ 10 cited

VEDLIoT -- Next generation accelerated AIoT systems and applications

Kevin Mika, René Griessl, Nils Kucza +29

The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propo…

eess.SP2023★ 1 cited

Experimental Validation of Single BS 5G mmWave Positioning and Mapping for Intelligent Transport

Yu Ge, Hedieh Khosravi, Fan Jiang +10

Positioning with 5G signals generally requires connection to several base stations (BSs), which makes positioning more demanding in terms of infrastructure than communications. To…

eess.SP2022

On the Impact of Phase Noise on Monostatic Sensing in OFDM ISAC Systems

Musa Furkan Keskin, Carina Marcus, Olof Eriksson +2

Phase noise (PN) can become a major bottleneck for integrated sensing and communications (ISAC) systems towards 6G wireless networks. In this paper, we consider an OFDM ISAC system…

cs.AR2022★ 13 cited

VEDLIoT: Very Efficient Deep Learning in IoT

Martin Kaiser, Rene Griessl, Nils Kucza +33

The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also deali…