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Deep Learning-Based CSI Feedback for Beamforming in Single- and Multi-cell Massive MIMO Systems [article]

Jiajia Guo, Chao-Kai Wen, Shi Jin
2020 arXiv   pre-print
We apply it to two representative scenarios: single- and multi-cell systems.  ...  Recently, deep learning (DL) has achieved great success in the CSI feedback.  ...  DL-BASED CSI FEEDBACK FOR BF IN SINGLE-CELL SYSTEMS In this section, we consider the CSI feedback for BF in the single-cell massive MIMO system.  ... 
arXiv:2011.06099v1 fatcat:dgleb2xhqvhsjht6wvonpgdsfa

Beam-space Multiplexing: Practice, Theory, and Trends-From 4G TD-LTE, 5G, to 6G and Beyond [article]

Shanzhi Chen, Shaohui Sun, Guixian Xu, Xin Su, Yuemin Cai
2020 arXiv   pre-print
Finally, the future trends of beam-space multiplexing in 6G and beyond are discussed, including massive beamforming for extremely large-scale MIMO (XL-MIMO), low earth orbit (LEO) satellites communication  ...  In this article, the new term, namely beam-space multiplexing, is proposed for the former multi-layer beamforming for 4G TD-LTE in 3GPP releases.  ...  Dake Liu of Beijing Institute of Technology and the anonymous reviewers for reviewing the manuscript.  ... 
arXiv:2001.05021v1 fatcat:b4chb4guzjbdvg37d52pkfpzka

Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

Hedi Khammari, Irfan Ahmed, Ghulam Bhatti, Masoud Alajmi
2019 Electronics  
In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed.  ...  To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection.  ...  In [12] , authors propose a hybrid beamforming method with unified analog beamformer by Subspace Construction (SC) based on partial CSI in massive MIMO OFDM system.  ... 
doi:10.3390/electronics8101061 fatcat:lqwxlclmizcphdhjxz56hdvyma

Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI [article]

Zhen Gao, Minghui Wu, Chun Hu, Feifei Gao, Guanghui Wen, Dezhi Zheng, Jun Zhang
2022 arXiv   pre-print
In an aerial hybrid massive multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) system, how to design a spectral-efficient broadband multi-user hybrid beamforming  ...  While for FDD systems, we jointly model the downlink pilot transmission, uplink CSI feedback, and downlink hybrid beamforming modules as an E2E neural network.  ...  As for the hybrid beamforming, a hierarchical codebook-based hybrid beamforming scheme was proposed in [22] for single-user MIMO systems.  ... 
arXiv:2201.06778v2 fatcat:xyrh2wi56nczhctudzwwt6hkui

Table of contents

2021 IEEE Transactions on Wireless Communications  
Norisato Suga and Toshihiro Furukawa Distributed Deep Convolutional Compression for Massive MIMO CSI Feedback .......................................... ................................................  ...  Zhiqiang Wei, Yuanxin Cai, Zhuo Sun, Derrick Wing Kwan Ng, Jinhong Yuan, Mingyu Zhou, and Lixin Sun Deep Reinforcement Learning for Multi-Agent Power Control in Heterogeneous Networks .................  ... 
doi:10.1109/twc.2021.3060977 fatcat:74lib7napnalhfjzhzxlg35ryu

2021 Index IEEE Transactions on Wireless Communications Vol. 20

2021 IEEE Transactions on Wireless Communications  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TWC Jan. 2021 96-109 Deep Learning-Based Antenna Selection and CSI Extrapolation in Massive MIMO Systems.  ... 
doi:10.1109/twc.2021.3135649 fatcat:bgd3vzb7pbee7jp75dnbucihmq

Massive MIMO Systems for 5G and Beyond Networks—Overview, Recent Trends, Challenges, and Future Research Direction

Robin Chataut, Robert Akl
2020 Sensors  
We outline recent trends such as terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning for massive MIMO systems.  ...  Additionally, we discuss crucial open research issues that direct future research in massive MIMO systems for 5G and beyond networks.  ...  In massive MIMO systems, the base station estimates the CSI with the help of uplink pilot signals or feedback sent by the user terminal.  ... 
doi:10.3390/s20102753 pmid:32408531 pmcid:PMC7284607 fatcat:xmyhlmst2bconcwlq5oezoc3zu

2020 Index IEEE Transactions on Wireless Communications Vol. 19

2020 IEEE Transactions on Wireless Communications  
Identification for MIMO Systems in Dynamic Environments; TWC June 2020 3643-3657 Huang, C., see Yang, M., TWC Sept. 2020 5860-5874 Huang, D., Tao, X., Jiang, C., Cui, S., and Lu, J  ...  ., and Saad, W., Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach; TWC June 2020 3908-3923 Hu, Y.H., see Xia, M., TWC June 2020 3769-3781 Hua,  ...  ., +, TWC Aug. 2020 5075-5087 Feedback Convolutional Neural Network-Based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis.  ... 
doi:10.1109/twc.2020.3044507 fatcat:ie4rwz4dgvaqbaxf3idysubc54

Unsupervised Deep Learning for Massive MIMO Hybrid Beamforming [article]

Hamed Hojatian, Jeremy Nadal, Jean-Francois Frigon, Francois Leduc-Primeau
2020 arXiv   pre-print
This paper proposes a novel RSSI-based unsupervised deep learning method to design the hybrid beamforming in massive MIMO systems.  ...  Hybrid beamforming is a promising technique to reduce the complexity and cost of massive multiple-input multiple-output (MIMO) systems while providing high data rate.  ...  RSSI-BASED HYBRID BEAMFORMING WITH DEEP NEURAL NETWORK In this section, we propose a novel RSSI-based method to design the HBF for massive MIMO systems.  ... 
arXiv:2007.00038v2 fatcat:xhxkbh3375frxl7ieh63u6fxjm

Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems

Muddasar Naeem, Giuseppe De Pietro, Antonio Coronato
2021 Sensors  
MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the most promising 5G wireless communication systems technology due to their high system throughput and data rate.  ...  Second, potential RL and DL applications for different MIMO issues, such as detection, classification, and compression; channel estimation; positioning, sensing, and localization; CSI acquisition and feedback  ...  Single-cell and multi-cell scenarios are also discussed in [210] in terms of CSI feedback for BF to optimize the BF performance gain instead of the feedback accuracy.  ... 
doi:10.3390/s22010309 pmid:35009848 pmcid:PMC8749942 fatcat:2w4th63dtrdyboa6rmhr5rcvja

Predicting Future CSI Feedback For Highly-Mobile Massive MIMO Systems [article]

Yu Zhang, Ahmed Alkhateeb, Pranav Madadi, Jeongho Jeon, Joonyoung Cho, Charlie Zhang
2022 arXiv   pre-print
Massive multiple-input multiple-output (MIMO) system is promising in providing unprecedentedly high data rate.  ...  In this paper, we develop a deep learning based channel prediction framework that proactively predicts the downlink channel state information based on the past observed channel sequence.  ...  Contribution: In this paper, we develop a novel 3-D convolutional neural network (CNN) based deep learning framework for predicting the future CSI in a massive MIMO-OFDM system.  ... 
arXiv:2202.02492v1 fatcat:n6ly46n4xreujkdl7pyy7qhb6y

2019 Index IEEE Wireless Communications Letters Vol. 8

2019 IEEE Wireless Communications Letters  
., +, LWC Dec. 2019 1563-1566 Feedback Deep Autoencoder Based CSI Feedback With Feedback Errors and Feedback Delay in FDD Massive MIMO Systems.  ...  ., +, LWC June 2019 857-860 Deep Learning-Based CSI Feedback Approach for Time-Varying Massive MIMO Channels.  ... 
doi:10.1109/lwc.2019.2961756 fatcat:bwxehcl4ejew7a6m66prb6s4z4

Interplay Between NOMA and Other Emerging Technologies: A Survey

Mojtaba Vaezi, Gayan Amarasuriya, Yuanwei Liu, Ahmed Arafa, Fang Fang, Zhiguo Ding
2019 IEEE Transactions on Cognitive Communications and Networking  
Index Terms-NOMA, massive MIMO, mmWave, cooperative communications, cognitive radio, energy harvesting, mobile edge computing, physical layer security, visible light communications, machine learning, deep  ...  NOMA can be flexibly combined with many existing wireless technologies and emerging ones including multiple-input multiple-output (MIMO), massive MIMO, millimeter wave communications, cognitive and cooperative  ...  Full CSI acquisition and feedback may be prohibitively complicated for analog precoding based mmWave massive MIMO [18] , [57] .  ... 
doi:10.1109/tccn.2019.2933835 fatcat:5utwrrgtujbsrf7q5yngpcodie

Surveying on MIMO Technology for Future Wireless Communication

Sandeepkumar Kulkarni, Department of Electronics and Instrumentation, Gulbarga University, Gulbarga (Karnataka), India., Dr. Raju Yanamshetti Kulkarni, Department of Electronics and Communication Engineering, Gulbarga University, Gulbarga (Karnataka), India.
2021 International journal of recent technology and engineering  
Massive MIMO is an extension of traditional MIMO with the exception that the BSs in massive MIMO are equipped with large number of antennas, usually hundred or more.  ...  Using massive MIMO technique also increases reliability of the links, reduces noise effects, and mitigates and interference.  ...  Role of Machine learning in massive MIMO network: Recently, the concept of Machine Learning/Deep Learning are very popular and handy for several human-made intelligent applications such as processing of  ... 
doi:10.35940/ijrte.d6525.1110421 fatcat:ishagldm6naivf2ygzvdodj7ny

Over-the-Air Computing for Wireless Data Aggregation in Massive IoT [article]

Guangxu Zhu and Jie Xu and Kaibin Huang and Shuguang Cui
2020 arXiv   pre-print
Conventional WDA techniques that are designed based on a separated-communication-and-computation principle encounter difficulty in accommodating the massive access under the limited radio resource and  ...  sensing, learning, and control.  ...  including power control, spatial multiplexing, channel feedback, and multi-cell cooperation.  ... 
arXiv:2009.02181v2 fatcat:akrt55jgjbhh3i26q2gz5fs6fi
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