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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書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications影響因子(影響力)




書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications影響因子(影響力)學(xué)科排名




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書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications被引頻次




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書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications年度引用




書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications年度引用學(xué)科排名




書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications讀者反饋




書(shū)目名稱Sparse Signal Processing for Massive MIMO Communications讀者反饋學(xué)科排名

Militia

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

BARGE

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

Directed

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.

Bereavement

Aboveboard

Assignment

精美食品

motor-unit

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,

耐寒

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