DFT Based Beam-Time Delay Sparse Channel Representation for Channel State Information (CSI) Compression in 5G FDD Massive MIMO Systems

Luis Suarez, N. Ryabov, V. Lyashev, Alexander Sherstobitov
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引用次数: 7

Abstract

Massive MIMO is currently a very hot topic for mobile R&D industry due to its large capabilities of high throughput and enhanced coverage for multiple users simultaneously. In the following article a proposal for dealing with the Channel State Information (CSI) overhead for FDD MIMO systems is presented. The idea consists of using a Multidimensional Discrete Fourier Transform (DFT) compression, which exploits the frequency and spatial correlations in order to provide a fully sparse Beam-Time Delay Channel Representation. The proposed idea provides high scalability in a long range of channel compression regimes while presents low computational complexity. Simulation results are presented showing the feasibility of implementation for Full dimensional massive MIMO systems.
基于DFT的5G FDD大规模MIMO系统中信道状态信息压缩的波束时间延迟稀疏信道表示
大规模MIMO以其大容量、高吞吐量和增强的多用户同时覆盖能力而成为当前移动研发领域的热门课题。在接下来的文章中,提出了一种处理FDD MIMO系统信道状态信息(CSI)开销的建议。该思想包括使用多维离散傅立叶变换(DFT)压缩,利用频率和空间相关性来提供完全稀疏的波束时间延迟信道表示。所提出的思想在长范围的信道压缩机制中提供了高可扩展性,同时具有较低的计算复杂度。仿真结果表明了该方法在全维大规模MIMO系统中实现的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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