2 citations · 3 across the 6 of their papers we have counts for
6 papers
MLE-based Device Activity Detection under Rician Fading for Massive Grant-free Access with Perfect and Imperfect Synchronization
Wang Liu, Ying Cui, Feng Yang +2
Most existing studies on massive grant-free access, proposed to support massive machine-type communications (mMTC) for the Internet of things (IoT), assume Rayleigh fading and perf…
Low-overhead Beam Training Scheme for Extremely Large-Scale RIS in Near-field
Wang Liu, Cunhua Pan, Hong Ren +3
Extremely large-scale reconfigurable intelligent surface (XL-RIS) has recently been proposed and is recognized as a promising technology that can further enhance the capacity of co…
Deep Learning Based Beam Training for Extremely Large-Scale Massive MIMO in Near-Field Domain
Wang Liu, Hong Ren, Cunhua Pan +1
Extremely large-scale massive multiple-input-multiple-output (XL-MIMO) is regarded as a promising technology for next-generation communication systems. In order to enhance the beam…
Long-Term CSI-based Design for RIS-Aided Multiuser MISO Systems Exploiting Deep Reinforcement Learning
Hong Ren, Cunhua Pan, Liang Wang +2
In this paper, we study the transmission design for reconfigurable intelligent surface (RIS)-aided multiuser communication networks. Different from most of the existing contributio…
Joint Optimization of Preamble Selection and Access Barring for Random Access in MTC with General Device Activities
Wang Liu, Ying Cui, Feng Yang +2
Most existing random access schemes for machine-type communications (MTC) simply adopt a uniform preamble selection distribution, irrespective of the underlying device activity dis…
Joint Optimization of Preamble Selection and Access Barring for MTC with Correlated Device Activities
Wang Liu, Ying Cui, Lianghui Ding +4
Most existing works on random access for machine-type communication (MTC) assume independent device activities. However, in several Internet-of-Things (IoT) applications, device ac…