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…
Resource Allocation for Mutualistic Symbiotic Radio with Hybrid Active-Passive Communications
Hong Guo, Yinghui Ye, Haijian Sun +2
Mutualistic SR is a communication paradigm that offers high spectrum efficiency and low power consumption, where the SU transmits information by modulating and backscattering the P…
Revolutionizing Symbiotic Radio: Exploiting Tradeoffs in Hybrid Active-Passive Communications
Rui Xu, Yinghui Ye, Haijian Sun +2
Symbiotic radio (SR), a novel energy- and spectrum-sharing paradigm of backscatter communications (BC), has been deemed a promising solution for ambient Internet of Things (A-IoT),…
Optimizing Wireless Resource Management and Synchronization in Digital Twin Networks
Hanzhi Yu, Yuchen Liu, Zhaohui Yang +2
In this paper, we investigate an accurate synchronization between a physical network and its digital network twin (DNT), which serves as a virtual representation of the physical ne…
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…
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…