activity
20242026
most citedRISnet: A Domain-Knowledge Driven Neural Network Architecture for RIS Optimization with Mutual Coupling and Partial CSI

17 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IT2026

Scalable Design for RIS-Assisted Multi-User Downlink System Empowered by RSMA under Partial CSI

Yifan Fang, Bile Peng, Yingyang Chen +3

In large-scale reconfigurable intelligent surface (RIS) communication systems, the precise acquisition of channel state information (CSI) is challenging. Consider a practical RIS c…

eess.SP2025

RIS-Assisted NOMA with Partial CSI and Mutual Coupling: A Machine Learning Approach

Bile Peng, Karl-Ludwig Besser, Shanpu Shen +5

Non-orthogonal multiple access (NOMA) is a promising multiple access technique. Its performance depends strongly on the wireless channel property, which can be enhanced by reconfig…

eess.SP2025

A Scalable Machine Learning Approach Enabled RIS Optimization with Implicit Channel Estimation

Bile Peng, Vahid Jamali, Eduard Jorswieck

The reconfigurable intelligent surface (RIS) is considered as a key enabler of the next-generation mobile radio systems. While attracting extensive interest from academia and indus…

eess.SP2024

Distributed Combinatorial Optimization of Downlink User Assignment in mmWave Cell-free Massive MIMO Using Graph Neural Networks

Bile Peng, Bihan Guo, Karl-Ludwig Besser +6

Millimeter wave (mmWave) cell-free massive MIMO (CF mMIMO) is a promising solution for future wireless communications. However, its optimization is non-trivial due to the challengi…

cs.IT2024★ 17 cited

RISnet: A Domain-Knowledge Driven Neural Network Architecture for RIS Optimization with Mutual Coupling and Partial CSI

Bile Peng, Karl-Ludwig Besser, Shanpu Shen +5

Space-division multiple access (SDMA) plays an important role in modern wireless communications. Its performance depends on the channel properties, which can be improved by reconfi…

eess.SP2024

Energy-Efficient Power Allocation in Cell-Free Massive MIMO via Graph Neural Networks

Ramprasad Raghunath, Bile Peng, Eduard A. Jorswieck

CF-mMIMO systems are a promising solution to enhance the performance in 6G wireless networks. Its distributed nature of the architecture makes it highly reliable, provides sufficie…