Exhibits
Catch a glimpse of the energy and insights that defined last year’s Brooklyn 6G Summit.
Media coverage
Exhibitors Demos
- KDDI Research Inc.Demo: Intelligent Energy-Efficient Extreme MIMO for 6G FR3
- KeysightDemo: AI Target Identification with OFDM Radar
- VIAVI SolutionsDemo 1: AI-Enabled Service Assurance for 6G: Lab to Field
Demo 2: Enabling Robustness With AI for Essential 6G Infrastructure - EmersonDemo: Wireless System Power Monitoring with NI USRP and NI cRIO
- Anritsu CompanyDemo 1: Artificial Intelligence-Driven High-Order MIMO Antenna Systems Verification
Demo 2: Monostatic, Bistatic and Multi-Static JCAS Measurements in Real-World Indoor Environments - NextG Wireless Lab, NC State University / All Things IntelligenceDemo 1 (NC State): AI5GTest: AI-driven Specification-Aware Automated Testing of 5G O-RAN Components
Demo 2 (NC State): O-DSM: An Open Dynamic Spectrum Management Framework for Cellular-Radar Coexistence in Mid-band Frequencies
Demo 3 (ATI): NeuralSmith: ML Engineering Simplified! - Pi-RadioDemo: Spectrum Sharing
- IEEEDemo: Dynamic Automation and Orchestration to ensure Quality of Service in 5G Networks
- VTT Technical Research Centre of FinlandDemo 1: Industrial XR Digital Twin for Enhanced Remote Maintenance
Demo 2: Quantum Assisted 5-bit OTTD for 6G Beam Steering - Northeastern UniversityDemo: Toward AI-RAN: Transforming RAN Design and Operations with Automation and LLMs
- OULU, FinlandDemo: Machine Learning-Assisted Reflective RIS for 6G ISAC
- NVIDIA / Northeastern UniversityDemo: Real-Time GPU-accelerated O-RAN dApp on NVIDIA ARC-OTA
- NVIDIA / OULU, FinlandDemo: Multimodal Digital Twins for 6G RAN in Dynamic Environments
- NVIDIADemo: NVIDIA Sionna Research Kit
- NYU WIRELESSDemo 1: Mitigating Blockages in Line-of-Sight Paths Using FR3 Frequency Agility
Demo 2: Multi-Frequency FR3 Localization - NYU WIRELESSDemo 1: Smart, Connected Wearables for the Visually Impaired
Demo 2: COSMOS Remote Access FR3 Software Defined Radio - NYU WIRELESSDemo 1: Four-Port On-Wafer RFIC Characterization and Measurements up to 330 GHz at the NYU THz Lab
Demo 2: NYURay: Physics-Based Wireless Ray Tracer for Site-Specific Deterministic Channel Modeling - NYU WIRELESSDemo: Comprehensive Radio Propagation Measurements and Standardized Point-Data Representation of Results
- Demo: OmniPHY Axon: A Live AI-Native Air Interface Demonstration for 6GDeepSig
- WiMNet – Columbia UniversityDemo: A Full-Duplex Link with Adaptive Self-Interference Cancellation
- Skylo TechnologiesDemo: Direct-to-Device (D2D) Satellite Connectivity Powered by Skylo
- Nokia Bell LabsDemo: HybridDeepRx: 6G AI Receiver for Distorted Signals
- Nokia Bell LabsDemo: Sensing and FR3 Communication Channel Modeling
- Nokia TechnologiesDemo: Volumetric Communication
- Nokia TechnologiesDemo: Spatial Audio for Voice Communication
- MediaTekDemo 1: Intelligent Device Edge Cloud Services
Demo 2: Next Generation ISAC with Efficient TDM Active Radar
Demo 3: A new low PAPR Waveform for 6G Coverage Enhancement - NICTDemo: Ultra-Spot-based THz/mmWave Communication
- NokiaTesting 7 GHz Mobile System in US (Live Demo)
Media coverage
Posters Exhibition
- NYU WIRELESSMultiband Sensing in FR3 with Background Dense Multipath Components
- University of DelawareDistributed RF-Photonic System for Coherent mmWave Cell-Free MIMO Communication
- Yonsei UniversityTo showcase 6G AI-on-RAN: Uncertainty-Aware Hybrid Inference for Wireless Robotic Manipulation
- UT AustinSelf-Nomination: Decentralized Deep Learning for CSI Feedback Reduction in MU-MIMO Systems
- NYULearning-Based Signal Recovery in Nonlinear Systems with Spectrally Separated Interference
- UT AustinTowards Crowd-sourced Digital Twins for Beamforming Optimization in XR Communications
- NYUExtending the Low Latency Slice Beyond the 5G Network
- NYUWe May Not Need Multipath TCP (MPTCP) Variants in 6G Dual-Connectivity to Achieve Per-Packet Load Balancing
- Columbia UniversityIntelligent 5G "All-G" Networks Designed and Integrated for Global Operations
- NYU WIRELESSCombining Capacity and Reliability via Inter-Frequency Handovers
- Duke UniversityWireless Digital Twins and ML Models for High-Fidelity RF Signal Mapping
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