ISACHub Centralized 6G ISAC Supercomputing & Radar Processing

ISACHub formalizes centralized Cloud-RAN baseband pooling, GPU-accelerated radar supercomputing, real-time 3D dynamic city mapping, and multi-tower track fusion.

ISACHub Centralized Supercomputing & Radar Processing Stack

ISAC Core: Hub Core — Cloud-RAN GPU Pool & Multi-Tower Fusion

6G ISAC Nodes & Beamforming Subsystems

Heterogeneous GPU/FPGA C-RAN
Real-Time 3D City Twin Engine
Multi-Static Kalman Track Fuser
Ambiguity Function Tensor Accelerator
High-Throughput NVLink Fabric

Architectural Layers & Waveform Pipelines

Schicht 1: Dual-Funktionale Wellenform & Basisband (OTFS / OFDM-Radar / Fractional Fourier Transform / Ambiguity Function): OTFS-Modulation und fraktionierte Chirp-Synthese zur Vermeidung von Inter-Carrier-Interferenzen bei starken Doppler-Spreizungen.
Schicht 2: Massive MIMO & Beamforming-Frontends (140 GHz D-Band / True-Time-Delay (TTD) / Hybrid Analog-Digital Beamforming): Sub-THz-Phased-Array-Architekturen mit True-Time-Delay-Kompensation, simultanen Datenstrahlen und hochpraezisen Radar-Trackingkeulen.
Schicht 3: Radarsignalverarbeitung & 4D-Punktwolken (2D-FFT Range-Doppler / MUSIC AoA / CFAR Detection / Micro-Doppler Extraction): Subdezimeter-Entfernungs- und Geschwindigkeitsaufloesung, CFAR-Zieldetektion und Mikro-Doppler-Klassifizierung von Drohnenrotoren.
Schicht 4: Netzwerksensorik-Orchestrierung & 3GPP Rel-19 (3GPP Rel-19 ISAC Core / Sensing Function (SF) / Reconfigurable Intelligent Surfaces (RIS)): Zellfreie kollaborative Radarnetze und dynamische Ressourcenallokation zum Ausgleich von Kommunikations-SLA und Radar-Abtastraten.

Sensing Telemetry & Benchmarks: <5 cm (Entfernungsaufloesung) | 0.1 m/s (Geschwindigkeitsgenauigkeit) | <10 ms (Radar-Bildlatenz) | 3GPP Rel-19 (Globaler Standard)

Cloud-RAN Baseband Pooling & 3D City Maps in ISACHub

Processing raw radar streams from thousands of urban base station antenna elements requires massive supercomputing clusters. ISACHub establishes the centralized Cloud-RAN architecture where GPU server farms ingest raw radar feeds to maintain living 3D digital twins of entire metropolitan regions.

Core Engineering Areas

Cloud-RAN Baseband Pooling and GPU Acceleration — Pooling baseband processing from hundreds of remote radio heads onto centralized GPU data centers connected via low-latency optical fiber.
City-Scale Dynamic Environmental 3D Mapping — Maintaining a continuously updated 3D digital replica of urban infrastructure by synthesizing multi-tower radar reflections.
Multi-Cell Distributed Kalman Track Fusion — Centralized multi-static tracking engines combining raw radar detections from up to ten surrounding base stations to eliminate tracking dropouts.