activity
20082023
most citedPower Scaling of Uplink Massive MIMO Systems with Arbitrary-Rank Channel Means

640 citations · 4.4k across the 114 of their papers we have counts for

collaborators

117 papers

eess.SY2023

A Partially Observable Deep Multi-Agent Active Inference Framework for Resource Allocation in 6G and Beyond Wireless Communications Networks

Fuhui Zhou, Rui Ding, Qihui Wu +3

Resource allocation is of crucial importance in wireless communications. However, it is extremely challenging to design efficient resource allocation schemes for future wireless co…

cs.IT2023

Active RIS-Assisted MIMO-OFDM System: Analyses and Prototype Measurements

De-Ming Chian, Feng-Ji Chen, Yu-Chen Chang +5

In this study, we develop an active reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) prototyp…

cs.IT2023★ 2 cited

Analytical Characterization of Coverage Regions for STAR-RIS-aided NOMA/OMA Communication Systems

Farshad Rostami Ghadi, F. Javier Lopez-Martinez, Kai-Kit Wong

We provide an analytical characterization of the coverage region of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided two-user downlink…

cs.IT2023★ 1 cited

A Novel Channel Model for Reconfigurable Intelligent Surfaces with Consideration of Polarization and Switch Impairments

De-Ming Chian, Chao-Kai Wen, Chi-Hung Wu +2

Future wireless networks require the ability to actively adjust the wireless environment to meet strict performance indicators. Reconfigurable Intelligent Surface (RIS) technology…

eess.SP2023

Resource Allocation for Cell-Free Massive MIMO-aided URLLC Systems Relying on Pilot Sharing

Qihao Peng, Hong Ren, Mianxiong Dong +3

Resource allocation is conceived for cell-free (CF) massive multi-input multi-output (MIMO)-aided ultra-reliable and low latency communication (URLLC) systems. Specifically, to sup…

cs.IT2023★ 35 cited

Deep Learning Based Predictive Beamforming Design

Juping Zhang, Gan Zheng, Yangyishi Zhang +2

This paper investigates deep learning techniques to predict transmit beamforming based on only historical channel data without current channel information in the multiuser multiple…