activity
20202025
most cited6G White Paper on Edge Intelligence

126 citations · 178 across the 13 of their papers we have counts for

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12 papers · 1 filter

cs.NI2025★ 1 cited

Enhancing V2X Communications with UAV-mounted Reconfigurable Intelligent Surfaces

Salim Janji, Paweł Sroka, Adrian Kliks

This paper addresses the crucial need for reliable wireless communication in vehicular networks, particularly vital for the safety and efficacy of (semi-)autonomous driving amid in…

cs.NI2025★ 3 cited

Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences

Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132

This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…

cs.NI2024★ 2 cited

V2V Path Loss Modeling at 26 GHz Based on Real-Traffic Measurements

Pawel Kryszkiewicz, Adrian Kliks, Pawel Sroka +1

In this letter, we investigate single-slope path loss models complemented with shadowing effects in the context of vehicular communications. We present several models obtained base…

cs.NI2024★ 3 cited

RIS-aided multi-hop backhauling for 5G/6G UAV-assisted access points

Salim Janji, Paweł Sroka

Drones are envisaged as an important part of the future 6G systems. With the possibility of their fast deployment they provide additional connectivity options in form of a hotspot.…

cs.NI2023

Why white noise is not enough? On using radio front-end models while designing 6G PHY

Pawel Kryszkiewicz, Pawel Sroka, Marcin Hoffmann +1

From generation to generation there are increasing requirements for wireless standards both in terms of spectral and energy efficiency. While up to now the layered wireless transce…

cs.NI2023★ 5 cited

Memory Enabled Bumblebee-based Dynamic Spectrum Access for Platooning Environments

Kuldeep S. Gill, Pawel Kryszkiewicz, Pawel Sroka +2

In this paper, we propose a novel memory-enabled non-uniform sampling-based bumblebee foraging algorithm (MEB) designed for optimal channel selection in a distributed Vehicular Dyn…

cs.NI2022★ 12 cited

Path Loss and Shadowing Modeling for Vehicle-to-Vehicle Communications in Terrestrial TV Band

Pawel Kryszkiewicz, Pawel Sroka, Michal Sybis +1

Vehicle platooning is considered as one of the key use cases for vehicle-to-vehicle (V2V) communications. However, its benefits can be realized only with highly reliable wireless t…

cs.NI2022

Distributed Learning for Vehicular Dynamic Spectrum Access in Autonomous Driving

Pawe\{l} Sroka, Adrian Kliks

Reliable wireless communication between the autonomously driving cars is one of the fundamental needs for guaranteeing passenger safety and comfort. However, when the number of com…

cs.NI2022★ 15 cited

Radio Environment Maps for Dynamic Frequency Selection in V2X Communications

Paweł Sroka, Paweł Kryszkiewicz, Adrian Kliks

In this paper, we investigate the concept of database supported Vehicular Dynamic Spectrum Access (VDSA) for platooning. As various researchers show that the 5.9 GHz band, devoted…

cs.NI2022★ 6 cited

Distributed Vehicular Dynamic Spectrum Access for Platooning Environments

Paweł Sroka, Paweł Kryszkiewicz, Michał Sybis +3

In this paper, we propose a distributed Vehicular Dynamic Spectrum Access (VDSA) framework for vehicles operating in platoon formations. Given the potential for significant congest…

cs.NI2021

The Impact of Blocking Cars on Pathloss Within a Platoon: Measurements for 26 GHz Band

Paweł Kryszkiewicz, Adrian Kliks, Paweł Sroka +1

Platooning is considered to be one of the possible prospective implementations of the autonomous driving concept, where the train-of-cars moves together following the platoon leade…

cs.NI2021★ 5 cited

Dynamic Power and Frequency Allocation Scheme for Autonomous Platooning

Paweł Sroka, Adrian Kliks, Michał Sybis +1

In this paper, we consider the use of radio environment maps (REMs) in vehicular dynamic spectrum access (VDSA) for vehicle platooning applications. We propose an algorithm that dy…