5 papers
Nexus: Efficient and Scalable Multi-Cell mmWave Baseband Processing with Heterogeneous Compute
Zhenzhou Qi, Chung-Hsuan Tung, Zhihui Gao +1
The rapid adoption of 5G New Radio (NR), particularly in the millimeter-wave (mmWave) spectrum, imposes stringent demands on the flexibility, scalability, and efficiency of baseban…
Chameleon: Integrated Sensing and Communication with Sub-Symbol Beam Switching in mmWave Networks
Zhihui Gao, Zhecun Liu, Tingjun Chen
Next-generation cellular networks are envisioned to integrate sensing capabilities with communication, particularly in the millimeter-wave (mmWave) spectrum, where beamforming usin…
BatStation: Toward In-Situ Radar Sensing on 5G Base Stations with Zero-Shot Template Generation
Zhihui Gao, Zhecun Liu, Tingjun Chen
The coexistence between incumbent radar signals and commercial 5G signals necessitates a versatile and ubiquitous radar sensing for efficient and adaptive spectrum sharing. In this…
Machine Intelligence on Wireless Edge Networks
Sri Krishna Vadlamani, Kfir Sulimany, Zhihui Gao +2
Machine intelligence on edge devices enables low-latency processing and improved privacy, but is often limited by the energy and delay of moving and converting data. Current system…
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency
Zhihui Gao, Sri Krishna Vadlamani, Kfir Sulimany +2
Modern edge devices, such as cameras, drones, and Internet-of-Things nodes, rely on deep learning to enable a wide range of intelligent applications, including object recognition,…