2 citations · 3 across the 6 of their papers we have counts for
6 papers
Feasibility-Aware Learning-to-Optimize in Wireless Communication Resource Allocation
Hanwen Zhang, Haijian Sun
The emergence of 6G wireless communication enables massive edge device access and supports real-time intelligent services such as the Internet of things (IoT) and vehicle-to-everyt…
HoP: Homeomorphic Polar Learning for Hard Constrained Optimization
Ke Deng, Hanwen Zhang, Jin Lu +1
Constrained optimization demands highly efficient solvers which promotes the development of learn-to-optimize (L2O) approaches. As a data-driven method, L2O leverages neural networ…
Model-based Deep Learning for QoS-Aware Rate-Splitting Multiple Access Wireless Systems
Hanwen Zhang, Mingzhe Chen, Alireza Vahid +2
Next generation communications demand for better spectrum management, lower latency, and guaranteed quality-of-service (QoS). Recently, Artificial intelligence (AI) has been widely…
Model-based Deep Learning for Wireless Resource Allocation in RSMA Communications Systems
Hanwen Zhang, Mingzhe Chen, Alireza Vahid +2
Rate-splitting multiple access (RSMA) has been proven as an effective communication scheme for 5G and beyond. However, current approaches to RSMA resource management require compli…
Exploring Communication Technologies, Standards, and Challenges in Electrified Vehicle Charging
Xiang Ma, Yuan Zhou, Hanwen Zhang +4
As public awareness of environmental protection continues to grow, the trend of integrating more electric vehicles (EVs) into the transportation sector is rising. Unlike convention…
Energy Efficient Robust Beamforming for Vehicular ISAC with Imperfect Channel Estimation
Hanwen Zhang, Haijian Sun, Tianyi He +2
This paper investigates robust beamforming for system-centric energy efficiency (EE) optimization in the vehicular integrated sensing and communication (ISAC) system, where the mob…