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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Zhen Gao,Yikun Mei,Li Qiao levels of individuals and within entire countries across the world. Nevertheless, very soon after the acknowledgment that literacy concerns vast domains of human life, the need to explore specific niches arose, where research or best practices implementation could thrive in the context of such comp

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Zhen Gao,Yikun Mei,Li Qiaoe the investigation and prosecution of those suspected of grave breaches of human rights. The chapter focuses on three principal questions. First, it addresses the growing interest in recent decades in seeking justice in supranational courts for cases of human rights violations. Second, the chapter

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Introduction,nclude compressed sensing, matching pursuit, and message passing algorithms. These techniques can be used to design efficient algorithms for channel estimation (CE), detection, and precoding, and can significantly reduce the computational complexity of massive MIMO systems while maintaining high per

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Compressive Sensing Sparse Channel Estimation in FDD Massive MIMO Systems,aptive pilot scheme is introduced to further reduce pilot overhead. Additionally, the discussion on the CE scheme is extended from the single-cell scenario to the multi-cell scenario for wider applications. Numerical results confirm that the considered scheme achieves accurate channel estimation wit

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Compressive Sensing Massive IoT Access in Massive MIMO Systems with Media Modulation,tured sparsity of media modulation-based symbols in each time slot to improve detection performance. Simulation results demonstrate the superiority of the considered scheme over state-of-the-art solutions.