Graduate Students: Wei Cheng, Zhihui Gao, Yiming Li, Zhenzhou Qi, Samuel Rivera, Chung-Hsuan Tung, Zehao Wang (Duke University)
Undergraduate Students: Scarlett Francini, Zeyu Li, Yi-Chyun Wong (Duke University)
Project Overview
Emerging applications in augmented reality, connected autonomous vehicles, and industrial IoT systems impose demanding requirements on next-generation mobile networks that can hardly be met alone with radio resources below 7 GHz. Therefore, 5G and beyond networks have embraced radios operating in millimeter-wave (mmWave) frequency bands, which offer 25 times or more bandwidth worldwide. On the other hand, mmWave radio networks require the dense deployment of infrastructure nodes to achieve desirable coverage, because mmWave radio signals suffer from high propagation loss and are vulnerable to blockage and mobility. Unfortunately, mmWave infrastructure nodes, e.g., gNodeB in 5G, are made of specialized, dedicated hardware and as a result, their dense deployment would incur formidable capital and operational cost. The goal of the proposed project is to reduce the cost of mmWave radio infrastructure nodes by softwarizing their radio access network (RAN) functions and serving them from data centers close to end users, i.e., edge data centers, therefore facilitating network densification. More importantly, it will allow for previously impossible flexibility in network implementation and configuration as well as efficiency in resource allocation across the network and the edge data center. At the societal level, this project will fuel the ongoing revolution of mobile network virtualization and accelerate the development and deployment of next-generation network systems.
The key insight toward addressing the challenges associated with softwarizing mmWave RANs at the edge is to exploit the massive data parallelism inside the mmWave baseband and its inherent structures, with programmable hardware in all domains. The project targets the following scientific contributions in three interrelated research thrusts. (i) A low-latency software realization of the mmWave physical layer for commodity server clusters suitable for edge deployment. (ii) Adaptive RAN configuration and in-network compression schemes that cope with the limited fronthaul capacity in practice, without substantially increasing the cost of mmWave infrastructure nodes. (iii) Novel sensing and imaging schemes based on mmWave radio signals intended for communications. These include sensing with a single mmWave infrastructure node and sensing that leverages multiple coordinated mmWave nodes to achieve previously impossible coverage and resolution.
Key Results and Outcomes
Softwarization of baseband processing in mmWave vRANs: We designed real-time baseband processing frameworks for single-cell (Savannah) and multi-cell (Nexus) scenarios leveraging heterogneous compute resources including CPUs (Intel’s Xeon processors) and ASICs (Intel’s ACC100 eASICs), with comprehensive power-latency profiling, modeling, and optimization (Qi et al., 2026; Qi et al., 2024; Qi et al., 2023). We also developed DecodeX, a software suite for benchmarking LDPC decoding performance across CPU, GPU, and ASIC platforms (Qi et al., 2026)
Over-the-air (OTA) evaluation of Savannah (Qi et al., 2024) using USRP SDRs in Lab (sub-6 GHz) and the PAWR COSMOS testbed (28 GHz).
Software-defined Python-enhanced RFSoC for wideband radio applications: We designed and implemented SPEAR, an SDR platform based on the Xilinx RFSoC ZCU216 evaluation board capable of supporting real-time, multi-channel (up to 16T16R), wideband (up to 1.25 GHz per channel) radio applications employing the direct RF radio architecture (Cheng et al., 2025; Cheng et al., 2024).
Experimental evaluation of SPEAR+ (Cheng et al., 2025): (a/b) A ZCU216 board connected to two antenna arrays, forming an OTA link at 800 MHz. (c) A ZCU216 board connected to two CHARM modules, forming an OTA link at 135 GHz.
Radio resource allocation and scheduling for communication and sensing: We developed Mambas, an analog multi-user beamforming tailored for mmWave networks employing the array of subarrays (ASA) architecture, supporting simultaneous communication with multiple users located in close proximity, even within the half-power beamwidth of the ASA (Gao et al., 2024). We developed Chameleon, a framework that augments and rapidly switches beamformers during each demodulation reference signal (DMRS) symbol to achieve integrated sensing and communication (ISAC) in 5G mmWave networks, where each beamformer introduces an additional sensing beam toward target angles while maintaining the communication beams toward multiple users (missing reference). We also studied sectorized wireless mesh networks with beam-steering infrastrucuture nodes, characterized their capacity region and sectorization gain via a flow extension ratio, and developed a distributed optimization algorithm that computes near-optimal node sectorization with a 2/3 approximation guarantee to maximize network flow (Promponas et al., 2023; Promponas et al., 2025).
Modeling and optimization of optical fronthaul: We studied both component- and network-level modeling and optimization of reconfigurable optical fronthaul that serves as the underlying infrastructure connecting base stataions with (edge) data centers. Through a series of lab experiments and field trials, we demonstrated reliable quality of transmission (QoT) estimation in the optical layer and co-existence of heterogeneous fronthaul traffics including 5G, wideband spectrum sensing based on analog radio-over-fiber (ARoF), and 400 GbE coherent optics (Wang et al., 2026; Sasai et al., 2025; Wang et al., 2025; Wang et al., 2024; Wang et al., 2024; Mano et al., 2023; Huang et al., 2023).
Field trial using the COSMOS testbed with dark fiber connecting two edge sites, supporting coexistence of 400 GbE coherent optics, analog radio-over-fiber (ARoF), and DAS-based fiber sensing signals.
This project fuels the ongoing revolution of mobile network virtualization and accelerate the development and deployment of next-generation network systems. Specifically, it expedites the adoption of mmWave radios, resulting in more capable, more efficient, and more cost-effective mobile networks. We leverage our ongoing collaborations with industry leaders to ensure a timely transfer of technologies into industry and a broad impact on the commercial development of mobile network, edge and cloud computing. By softwarizing wireless network functions at the lowest layer, this project provides a meeting ground for software systems and wireless communication research and creates timely content for teaching Computer Science majors about wireless physical layer. The project also provides a platform to engage undergraduate students and high-school students in wireless and computing research.
References
2026
MobiCom
Wireless
Systems
Nexus: Efficient and Scalable Multi-Cell mmWave Baseband Processing with Heterogeneous Compute
Zhenzhou Qi, Chung-Hsuan Tung, Zhihui Gao, and Tingjun Chen
In Proc. ACM International Conference on Mobile Computing and Networking (MobiCom’26), 2026
@inproceedings{qi2026nexus,title={Nexus: Efficient and Scalable Multi-Cell mmWave Baseband Processing with Heterogeneous Compute},author={Qi, Zhenzhou and Tung, Chung-Hsuan and Gao, Zhihui and Chen, Tingjun},booktitle={Proc. ACM International Conference on Mobile Computing and Networking (MobiCom'26)},year={2026},topic_primary={Wireless},topic_secondary={Systems}}
HotMobile
Wireless
Systems
DecodeX: Exploring and Benchmarking of LDPC Decoding across CPU, GPU, and ASIC Platforms
@inproceedings{qi2026decodex,title={{DecodeX}: Exploring and Benchmarking of LDPC Decoding across CPU, GPU, and ASIC Platforms},author={Qi, Zhenzhou and Yao, Yuncheng and Li, Yiming and Tung, Chung-Hsuan and Zheng, Junyao and Zhuo, Danyang and Chen, Tingjun},booktitle={Proc. ACM Workshop on Mobile Computing Systems and Applications (HotMobile'26)},year={2026},topic_primary={Wireless},topic_secondary={Systems}}
JOCN
Optics
AI/ML
Scalable ML Models and Cascaded Learning for Efficient Multi-Span OSNR and GSNR Prediction
Zehao Wang, Agastya Raj, Giacomo Borraccini, Shaobo Han, Yue-Kai Huang, Ting Wang, Marco Ruffini, Dan Kilper, and Tingjun Chen
IEEE/Optica Journal of Optical Communications and Networking, 2026
Invited Paper to the JOCN Special Issue on Invited/Top-Rated Papers from IEEE/Optica OFC’25
@article{wang2026scalable,title={Scalable ML Models and Cascaded Learning for Efficient Multi-Span OSNR and GSNR Prediction},author={Wang, Zehao and Raj, Agastya and Borraccini, Giacomo and Han, Shaobo and Huang, Yue-Kai and Wang, Ting and Ruffini, Marco and Kilper, Dan and Chen, Tingjun},journal={IEEE/Optica Journal of Optical Communications and Networking},volume={18},number={1},pages={A88--A99},year={2026},publisher={IEEE},topic_primary={Optics},topic_secondary={AI/ML}}
2025
MILCOM
Wireless
Systems
SPEAR+: Streaming-Based Multi-Channel SDR Implementation Using the RFSoC Platform
Wei Cheng, Zhihui Gao, Jose Guajardo, Hesham Beshary, Ali Niknejad, and Tingjun Chen
In Proc. IEEE Military Communications Conference (MILCOM’25), 2025
@inproceedings{cheng2025spear+,title={{SPEAR+}: Streaming-Based Multi-Channel {SDR} Implementation Using the {RFSoC} Platform},author={Cheng, Wei and Gao, Zhihui and Guajardo, Jose and Beshary, Hesham and Niknejad, Ali and Chen, Tingjun},booktitle={Proc. IEEE Military Communications Conference (MILCOM'25)},year={2025},topic_primary={Wireless},topic_secondary={Systems}}
TON
Wireless
On the Optimization and Stability of Sectorized Wireless Networks
Panagiotis Promponas, Tingjun Chen, and Leandros Tassiulas
@article{promponas2025on,title={On the Optimization and Stability of Sectorized Wireless Networks},author={Promponas, Panagiotis and Chen, Tingjun and Tassiulas, Leandros},journal={IEEE/ACM Transactions on Networking},volume={33},number={6},pages={3228--3243},year={2025},publisher={IEEE/ACM},doi={10.1109/TON.2025.3583267},topic_primary={Wireless}}
JLT
Optics
Systems
Optical Link Tomography: First Field Trial and 4D Extension
@article{sasai2025optical,title={Optical Link Tomography: First Field Trial and 4D Extension},author={Sasai, Takeo and Borraccini, Giacomo and Huang, Yue-Kai and Nishizawa, Hideki and Wang, Zehao and Chen, Tingjun and Sone, Yoshiaki and Takahashi, Minami and Matsumura, Tatsuya and Nakamura, Masanori and others},journal={IEEE/Optica Journal of Lightwave Technology},volume={43},number={24},pages={10776--10787},year={2025},publisher={IEEE},doi={10.1109/JLT.2025.3620127},topic_primary={Optics},topic_secondary={Systems}}
OFC
Optics
AI/ML
Multi-Span OSNR and GSNR Prediction Using Cascaded Learning
Zehao Wang, Giacomo Borraccini, Andrea D’Amico, Yue-Kai Huang, Ting Wang, Dan Kilper, Koji Asahi, and Tingjun Chen
In Proc. IEEE/Optica Optical Fiber Communications Conference (OFC’25), 2025
@inproceedings{wang2025multi,title={Multi-Span OSNR and GSNR Prediction Using Cascaded Learning},author={Wang, Zehao and Borraccini, Giacomo and D'Amico, Andrea and Huang, Yue-Kai and Wang, Ting and Kilper, Dan and Asahi, Koji and Chen, Tingjun},booktitle={Proc. IEEE/Optica Optical Fiber Communications Conference (OFC'25)},year={2025},doi={10.1364/OFC.2025.Tu3I.6},topic_primary={Optics},topic_secondary={AI/ML}}
2024
MobiCom
Wireless
Systems
Savannah: Efficient mmWave Baseband Processing with Minimal and Heterogeneous Resources
Zhenzhou Qi, Chung-Hsuan Tung, Anuj Kalia, and Tingjun Chen
In Proc. ACM International Conference on Mobile Computing and Networking (MobiCom’24), 2024
@inproceedings{qi2024savannah,title={Savannah: Efficient {mmWave} Baseband Processing with Minimal and Heterogeneous Resources},author={Qi, Zhenzhou and Tung, Chung-Hsuan and Kalia, Anuj and Chen, Tingjun},booktitle={Proc. ACM International Conference on Mobile Computing and Networking (MobiCom'24)},year={2024},doi={10.1145/3636534.3690707},topic_primary={Wireless},topic_secondary={Systems}}
WiNTECH
Wireless
Systems
SPEAR: Software-defined Python-Enhanced RFSoC for Wideband Radio Applications
Wei Cheng, Zhihui Gao, and Tingjun Chen
In Proc. ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization (WiNTECH’24), 2024
@inproceedings{gao2024mambas,title={Mambas: Maneuvering Analog Multi-User Beamforming Using an Array of Subarrays in {mmWave} Networks},author={Gao, Zhihui and Qi, Zhenzhou and Chen, Tingjun},booktitle={Proc. ACM International Conference on Mobile Computing and Networking (MobiCom'24)},year={2024},doi={10.1145/3636534.3649390},topic_primary={Wireless},topic_secondary={Systems}}
OFC
Optics
AI/ML
Multi-Span Optical Power Spectrum Prediction Using ML-based EDFA Models and Cascaded Learning
Zehao Wang, Yue-Kai Huang, Shaobo Han, Ting Wang, Dan Kilper, and Tingjun Chen
In Proc. IEEE/Optica Optical Fiber Communications Conference (OFC’24), 2024
Top-Scored Paper, Corning Outstanding Student Paper Competition Finalist
@inproceedings{wang2024multi,title={Multi-Span Optical Power Spectrum Prediction Using {ML}-based {EDFA} Models and Cascaded Learning},author={Wang, Zehao and Huang, Yue-Kai and Han, Shaobo and Wang, Ting and Kilper, Dan and Chen, Tingjun},booktitle={Proc. IEEE/Optica Optical Fiber Communications Conference (OFC'24)},year={2024},topic_primary={Optics},topic_secondary={AI/ML}}
JLT
Optics
Systems
Field Trial of Coexistence and Simultaneous Switching of Real-Time Fiber Sensing and Coherent 400 GbE in a Dense Urban Environment
Zehao Wang, Yue-Kai Huang, Ezra Ip, Zhenzhou Qi, Gil Zussman, Dan Kilper, Koji Asahi, Hideo Kageshima, Yoshiaki Aono, and Tingjun Chen
IEEE/Optica Journal of Lightwave Technology, 2024
Invited Paper to the JLT Special Issue on Top-Scored Papers from IEEE/Optica OFC’23
@article{wang2024field,title={Field Trial of Coexistence and Simultaneous Switching of Real-Time Fiber Sensing and Coherent 400 {GbE} in a Dense Urban Environment},author={Wang, Zehao and Huang, Yue-Kai and Ip, Ezra and Qi, Zhenzhou and Zussman, Gil and Kilper, Dan and Asahi, Koji and Kageshima, Hideo and Aono, Yoshiaki and Chen, Tingjun},journal={IEEE/Optica Journal of Lightwave Technology},volume={42},number={4},pages={1304--1311},year={2024},publisher={IEEE/Optica},doi={10.1109/JLT.2023.3319166},topic_primary={Optics},topic_secondary={Systems}}
2023
WiNTECH
Wireless
Systems
Programmable Millimeter-wave MIMO Radios with Real-Time Baseband Processin
Zhenzhou Qi, Zhihui Gao, Chung-Hsuan Tung, and Tingjun Chen
In Proc. ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization (WiNTECH’23), 2023
@inproceedings{qi2023programmable,title={Programmable Millimeter-wave MIMO Radios with Real-Time Baseband Processin},author={Qi, Zhenzhou and Gao, Zhihui and Tung, Chung-Hsuan and Chen, Tingjun},booktitle={Proc. ACM Workshop on Wireless Network Testbeds, Experimental evaluation \& CHaracterization (WiNTECH'23)},year={2023},topic_primary={Wireless},topic_secondary={Systems}}
MobiHoc
Wireless
Optimizing Sectorized Wireless Networks: Model, Analysis, and Algorithm
Panagiotis Promponas, Tingjun Chen, and Leandros Tassiulas
In Proc. ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc’23), 2023
@inproceedings{promponas2023optimizing,title={Optimizing Sectorized Wireless Networks: Model, Analysis, and Algorithm},author={Promponas, Panagiotis and Chen, Tingjun and Tassiulas, Leandros},booktitle={Proc. ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc'23)},year={2023},topic_primary={Wireless}}
ECOC
Optics
Systems
First Field Demonstration of Automatic WDM Optical Path Provisioning over Alien Access Links for Data Center Exchange
Toru Mano, Thomas Lima, Yue-Kai Huang, Zehao Wang, Wataru Ishida, Ezra Ip, Andrea D’Amico, Seiji Okamoto, Takeru Inoue, Hideki Nishizawa, Vittorio Curri, Gil Zussman, Daniel Kilper, Tingjun Chen, Ting Wang, Koji Asahi, and Koichi Takasugi
In Proc. European Conference and Exhibition on Optical Communication (ECOC’23), 2023
@inproceedings{mano2023first,title={First Field Demonstration of Automatic {WDM} Optical Path Provisioning over Alien Access Links for Data Center Exchange},author={Mano, Toru and Ferreira de Lima, Thomas and Huang, Yue-Kai and Wang, Zehao and Ishida, Wataru and Ip, Ezra and D'Amico, Andrea and Okamoto, Seiji and Inoue, Takeru and Nishizawa, Hideki and Curri, Vittorio and Zussman, Gil and Kilper, Daniel and Chen, Tingjun and Wang, Ting and Asahi, Koji and Takasugi, Koichi},booktitle={Proc. European Conference and Exhibition on Optical Communication (ECOC'23)},year={2023},topic_primary={Optics},topic_secondary={Systems}}
OFC
Optics
Systems
Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and 400GbE Supporting DCI and 5G Mobile Services
Yue-Kai Huang, Zehao Wang, Ezra Ip, Zhenzhou Qi, Gil Zussman, Dan Kilper, Koji Asahi, Hideo Kageshima, Yoshiaki Aono, and Tingjun Chen
In Proc. IEEE/Optica Optical Fiber Communications Conference (OFC’23), 2023
@inproceedings{huang2023field,title={Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and {400GbE} Supporting {DCI} and {5G} Mobile Services},author={Huang, Yue-Kai and Wang, Zehao and Ip, Ezra and Qi, Zhenzhou and Zussman, Gil and Kilper, Dan and Asahi, Koji and Kageshima, Hideo and Aono, Yoshiaki and Chen, Tingjun},booktitle={Proc. IEEE/Optica Optical Fiber Communications Conference (OFC'23)},year={2023},topic_primary={Optics},topic_secondary={Systems}}
