Triple-Structured Sparsity-Based Channel Feedback for RIS-Assisted MU-MIMO System
Author:
Affiliation:
1. Department of Electronic Engineering, Tsinghua University, Beijing, China
Funder
Tsinghua University–China Mobile Research Institute Joint Innovation Center
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/9771287/09695409.pdf?arnumber=9695409
Reference13 articles.
1. The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications
2. Triple-Structured Compressive Sensing-based Channel Estimation for RIS-aided MU-MIMO Systems
3. Matrix Analysis and Applications
4. Machine learning inspired energy-efficient hybrid precoding for mmWave massive MIMO systems
5. On the Performance of Channel-Statistics-Based Codebook for Massive MIMO Channel Feedback
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2. Implementing intelligent‐based sparse channel estimation in Multi User‐Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing system with hybridized optimization algorithm;International Journal of Communication Systems;2024-05-11
3. Data Augmentation for Bridging the Delay Gap in DL-Based Massive MIMO CSI Feedback;IEEE Wireless Communications Letters;2024-05
4. RISNet: A DL-Based High Accuracy CSI Feedback Approach for RIS-Aided FDD Systems;Lecture Notes in Electrical Engineering;2024
5. Secure RIS-Aided MISO-NOMA System Design in the Presence of Active Eavesdropping;IEEE Internet of Things Journal;2023-11-15
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