7 papers
Multi-modal Data Driven Virtual Base Station Construction for Massive MIMO Beam Alignment
Yijie Bian, Wei Guo, Jie Yang +4
Massive multiple-input multiple-output (MIMO) is a key enabler for the high data rates required by the sixth-generation networks, yet its performance hinges on effective beam manag…
Deep Learning-based Low-Overhead Beam Alignment for mmWave Massive MIMO Systems
Weijie Jin, Jing Zhang, Hengtao He +3
Millimeter-wave massive multiple-input multiple-output systems employ highly directional beamforming to overcome severe path loss, and their performance critically depends on accur…
On the Optimal Integer-Forcing Precoding: A Geometric Perspective and a Polynomial-Time Algorithm
Junren Qin, Fan Jiang, Tao Yang +3
The joint optimization of the integer matrix and the power scaling matrix is central to achieving the capacity-approaching performance of Integer-Forcing…
Data-Driven Deep MIMO Detection:Network Architectures and Generalization Analysis
Yongwei Yi, Xinping Yi, Wenjin Wang +2
In practical Multiuser Multiple-Input Multiple-Output (MU-MIMO) systems, symbol detection remains challenging due to severe inter-user interference and sensitivity to Channel State…
CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors
Shen Fu, Yong Zeng, Zijian Wu +4
Channel knowledge map (CKM) is a promising technology to enable environment-aware wireless communications and sensing with greatly enhanced performance, by offering location-specif…
Channel Estimation for RIS-Aided MU-MIMO mmWave Systems with Practical Hybrid Architecture
Liuchang Zhuo, Cunhua Pan, Hong Ren +4
This paper proposes a correlation-based three-stage channel estimation strategy with low pilot overhead for reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave)…