Wireless Communication | Yao Zheng@UHM

NVIDIA Academic Grant Program: OmniPort: Real-Time Semantic Digital Twins via ISAC and AI-RAN for Smart Ports

Sat, 15 Aug 2026 15:29:00 -1000

Executive Summary

OmniPort develops a real-time intelligent wireless and digital-twin platform for safer and more efficient autonomous operations in container ports. Ports are particularly challenging environments for robots because stacked metal containers obstruct GPS and line-of-sight sensors while producing strong wireless multipath. Instead of treating these reflections solely as interference, OmniPort uses integrated sensing and communication (ISAC) to extract information from routine robot uplink signals, enabling around-corner hazard detection and GPS-free robot localization. An AI-RAN then combines these sensing results with robot mobility and network telemetry to predict wireless conditions, dynamically allocate network resources, and maintain low-latency communication for safety-critical operations.

The project integrates these capabilities into an uncertainty-aware semantic digital twin that represents container geometry, robot movement, hazards, and wireless connectivity in real time. Rather than continuously transmitting camera video, operators can supervise robot fleets through a privacy-preserving VR environment generated from this semantic information, with warnings for collision risks, connectivity degradation, and emerging hazards. The platform uses four on-premises NVIDIA RTX PRO 6000 GPUs to support concurrent ISAC processing, AI-RAN control, NVIDIA Isaac Sim/Cosmos-based digital-twin reasoning, and Omniverse VR visualization, targeting an end-to-end control latency below 50 ms. The resulting technologies, software, and datasets are intended to provide a foundation for intelligent robotic operations in Hawaiʻi’s ports and other complex industrial environments.

Optimized IRS Positioning for Phase-Tuned Wireless Physiological Motion Detection

Mon, 10 Nov 2025 00:00:00 +0000

Secure-IRS: Defending Against Adversarial Physical-Layer Sensing in ISAC System

Mon, 10 Nov 2025 00:00:00 +0000

CyberTraining: Pilot: O-RAN-Based Cyberinfrastructure Training for Future-Generation Wireless Communication and Sensing

Sat, 07 Dec 2024 00:00:00 -1000

Executive Summary

The national spectrum strategy emphasizes spectrum infrastructure and workforce development in the full range of operational, technical, and policy roles to establish U.S. leadership in future-generation (FutureG) wireless techniques. However, achieving the strategic goal of spectrum workforce development involves non-trivial challenges, including limited capacity and availability of advanced wireless cyberinfrastructure (CI) and specialized tools, skills, and knowledge sets to develop, manage, and utilize wireless CI. This project responds to the national call for spectrum workforce development and trains the FutureG workforce by extending their research abilities through a novel ?immersed? approach to promote project-based hands-on learning. An open radio access network (O-RAN) wireless testbed will be utilized to allow trainees to practice the operation and programming of FutureG wireless instruments and develop wireless applications. Cloud-based access to the O-RAN testbed and a suite of template projects will be offered to address the technical barriers and complexities of wireless CI access. New course modules, vertical-integration projects, and summer courses will be offered to both student trainees and existing students at PIs? institutions. The training materials will be disseminated through public platforms including the ACCESS Knowledge Base to train a broader and diverse group of wireless professionals.

Specifically, this pilot project includes three tasks: Task 1 is to extend the abilities of wireless professionals with a publicly and remotely accessible wireless CI based on the O-RAN architecture. The CI integrates advanced RF and computing instruments including NI USRP X410 and 2974 supporting sub-6G Hz to mmWave bands, TMYTEK mmWave BBox at 28GHz and 39GHz, phrased-array beamformer and reconfigurable intelligent surface (RIS), and a GPU server with 8x NVIDIA RTX A5000. Task 2 aims at training wireless professionals with the development of AI/ML tools and services to allow automatic wireless data collection and intelligent analytics. Based on this unique CI, Task 3 develops a suite of hands-on projects to train and educate wireless professionals under different scenarios ranging from basic wireless instrument operation to advanced wireless research.

Heart Signal Sensing Using Millimeter-wave OFDM Waveform in FutureG Communications Systems

Mon, 01 Jan 2024 00:00:00 +0000

EE693e (Spec Topics): Wireless Communication and Sensing for Telemedicine

Mon, 02 Aug 2021 10:07:39 -1000

Executive Summary

This course focuses on selected research topics in wireless communication and sensing and is intended for undergraduate, master, and doctoral students who are interested in this field of study. At the end of this course, students will have a in-depth knowledge of the state-of-the-art and open problems, thus enhancing their potential to do research or pursue a career in this rapidly developing area. this course is structured as a research seminar and laboratory where research papers from leading conferences & journals will be presented by the instructor and students. Main topics of this iteration include the study the connections between telemedicine and IoT, mobile sensing, augmented reality, 5G, edge computing, cloud computing, and 3D-printing.

Logistics

CRN

EE693e

85304
Personnel:

Lecturer: Overview the area of study

Presenter¹: students Give presenation and written report of the given paper

Audience²: students Discuss the given paper
Format:

Lecture/Presentation Time Lecture/Presenatation Location Textbook Persentation Report

MW 9:00am-10:15am See Group Group

EE693e
85304


Lecturer:	Overview the area of study
Presenter¹: students	Give presenation and written report of the given paper
Audience²: students	Discuss the given paper

Lecture/Presentation Time	Lecture/Presenatation Location	Textbook	Persentation	Report
MW 9:00am-10:15am		See	Group	Group

Grading Policy

Presentations	Reports	Discussion
40%	40%	20%

Cutoffs

A- B- C-

70% 50% 30%
Proscribed Conduct: Copying or otherwise cheating on homework, lab reports, or exam will result in a failing grade for the course. More details can be found at student conduct code policies,

A-	B-	C-
70%	50%	30%

Schedule

TIME	TOPIC	PAPER/NOTES	REPORT	DUE
Week 01 ( )	Logistic, Telemedicine Overview		NA	NA
Week 02 ( , )	Student Presentations	,		11:59 PM, Sep 12
Week 03 ( )	Telemedicine and Internet of Things		NA	NA
Week 04 ( , )	Student Presentations	,		11:59 PM, Sep 26
Week 05 ( , )	Telemedicine and Wireless Sensing	,	NA	NA
Week 06 ( , )	Student Presentations	,		11:59 PM, Oct 12
Week 07 ( , )	Telemedicine and AR/VR	,	NA	NA
Week 08/09 ( , )	Student Presentations	,		11:59 PM, Oct 24
Week 09 ( )	Telemedicine and 5G		NA	NA
Week 10 ( , )	Student Presentations	,		11:59 PM, Nov 07
Week 11 ( , )	Telemedicine and Edge Computing	,	NA	NA
Week 12 ( , )	Student Presentations	,		11:59 PM, Nov 21
Week 13 ( , )	Telemedicine and Cloud Computing	,	NA	NA
Week 14 ( , )	Student Presentations	,	–	11:59 PM, Nov 05
Week 15 ( , [Dec 01][recording 1201 url])	Telemedicine and 3D-Printing	,	NA	NA
Week 16 ( , )	Student Presentations	,	–	11:59 PM, Dec 19
Week 17	Conclusion	–	NA	NA

Footnotes

Students may work in teams of two or three. each team will be assigned with one paper every other week. each team needs to complete two tasks on each paper: (1) give a in-depth presentation (60 min) and answer all the questions during the q&a (15 min); (2) write a one-page (excluding citations) summary of the paper (in ieee conference format). ↩︎
Students must work alone and complete the following tasks for each presentation: (1) prepare at least one relevent question for the presenter; (3) grade the presenter’s presentation and report. ↩︎