From the 2 of 5 linked papers with an AI index.
5 papers
CRLB-Driven Beamforming and Power Allocation for Multi-BS Cooperative ISAC Networks
Yanpeng Su, Maximilian Lübke, Mengyu Zhang +1
This paper presents a Cramér-Rao lower bound (CRLB)-driven beamforming (BF) and power allocation (PA) framework for cooperative integrated sensing and communication (ISAC) network…
Multi-Agent Reinforcement Learning for Base Station Placement in TDOA-Based Localization
Bastian Perner, Pratik Gajanan Raut, Maximilian Lübke +1
The paper introduces a multi‑agent reinforcement learning system that uses ray‑traced channel impulse responses to place base stations for TDOA localization, achieving modest accur…
On the Feasibility of Passive Bistatic ISAC Based on Unmodified LoRa
Laurenz Taffner, Jonas Bönsch, Norman Franchi +1
Integrated Sensing and Communication (ISAC) enables sensing capabilities by reusing communication signals, making it particularly attractive for large-scale deployments through sig…
On Unified CRLB Framework from Generic Signals to ISAC Waveforms with Virtual Array Sensing
Yanpeng Su, Norman Franchi, Maximilian Lübke
This paper presents a unified Cramér-Rao lower bound (CRLB) framework for signal-level parameters in integrated sensing and communications (ISAC)-enabled radar systems. Starting f…
How connected cars could capture cloud dynamics -- first evidence from two simulation scenarios
Tobias Veihelmann, Philipp Reitz, Maximilian Lübke +1
The rapidly increasing share of fluctuating electricity from photovoltaics calls for accurate approaches to estimate cloud motion, the primary source for the varying power supply.…