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Titlebook: Sparse Signal Processing for Massive MIMO Communications; Zhen Gao,Yikun Mei,Li Qiao Book 2024 Beijing Institute of Technology Press 2024

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樓主
發(fā)表于 2025-3-21 17:56:35 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Sparse Signal Processing for Massive MIMO Communications
編輯Zhen Gao,Yikun Mei,Li Qiao
視頻videohttp://file.papertrans.cn/874/873414/873414.mp4
概述Is the first book to apply sparse signal processing in wireless communication systems systematically.Describes the physical (PHY) layer algorithm design in detail with considerable open-source codes.G
圖書封面Titlebook: Sparse Signal Processing for Massive MIMO Communications;  Zhen Gao,Yikun Mei,Li Qiao Book 2024 Beijing Institute of Technology Press 2024
描述The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. As the number of antennas has been increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.
出版日期Book 2024
關(guān)鍵詞Massive MIMO; Orthogonal frequency division multiplexing; Wireless channel; Channel estimation; Sparse s
版次1
doihttps://doi.org/10.1007/978-981-99-5394-3
isbn_softcover978-981-99-5396-7
isbn_ebook978-981-99-5394-3
copyrightBeijing Institute of Technology Press 2024
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沙發(fā)
發(fā)表于 2025-3-21 20:18:08 | 只看該作者
Book 2024increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instruc
板凳
發(fā)表于 2025-3-22 01:07:38 | 只看該作者
formance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.978-981-99-5396-7978-981-99-5394-3
地板
發(fā)表于 2025-3-22 06:04:25 | 只看該作者
Subspace-Based Super-Resolution Sparse Channel Estimation in MIMO-OFDM Systems,ral channel correlation leads to the relatively unchanged sparsity pattern during several OFDM symbols. Taking advantage of these characteristics, the considered scheme outperforms existing state-of-the-art methods, and reduces the pilot overhead through joint signal processing across different antennas.
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發(fā)表于 2025-3-23 04:16:33 | 只看該作者
Compressive Sensing CSI Acquisition and Feedback in FDD Massive MIMO Systems,e training overhead and pilot design, aiming at accurately estimating and feeding back the downlink CSI with significantly reduced overhead. In particular, a compressive sensing based adaptive CSI acquisition scheme is introduced by exploiting the spatially common sparsity of massive MIMO channels,
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發(fā)表于 2025-3-23 09:26:56 | 只看該作者
Compressive Sensing Sparse Channel Estimation in Broadband Millimeter-Wave Massive MIMO Systems,ness, which leads to challenges in channel estimation (CE). Simultaneously, the frequency-selective fading (FSF) characteristic of practical mmWave channels cannot be ignored. Therefore, this chapter introduces a multi-user uplink CE scheme tailored for mmWave massive MIMO systems considering FSF ch
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