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

Camada 1: Forma de Onda Duplo-Funcional e Banda Base (OTFS / OFDM-Radar / Fractional Fourier Transform / Ambiguity Function): Modulação OTFS e síntese fracionária de chirp alcançando interferência interportadora zero sob severos espalhamentos Doppler.
Camada 2: Massive MIMO e Frontends de Beamforming (140 GHz D-Band / True-Time-Delay (TTD) / Hybrid Analog-Digital Beamforming): Matrizes em fase ativas Sub-THz com mitigação de beam-squint, feixes de dados de comunicação e lóbulos de rastreamento radar simultâneos.
Camada 3: Processamento de Sinal Radar e Nuvem de Pontos 4D (2D-FFT Range-Doppler / MUSIC AoA / CFAR Detection / Micro-Doppler Extraction): Resolução subdecimétrica de alcance e velocidade, detecção CFAR e classificação micro-Doppler de marcha biométrica e hélices de drones.
Camada 4: Orquestração de Sensoriamento de Rede e 3GPP Rel-19 (3GPP Rel-19 ISAC Core / Sensing Function (SF) / Reconfigurable Intelligent Surfaces (RIS)): Redes de radar colaborativas sem células, alocação dinâmica de recursos tempo-frequência equilibrando SLA e tempo de revisita radar.

Sensing Telemetry & Benchmarks: <5 cm (Resolução de Alcance) | 0.1 m/s (Precisão de Velocidade) | <10 ms (Latência de Quadro Radar) | 3GPP Rel-19 (Padrão Global)

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.