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Antenna Grouping Based Feedback Compression for FDD-Based Massive MIMO Systems

机译：基于FDD的大规模MIMO系统中基于天线分组的反馈压缩

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摘要

Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the base station. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the base station. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the base station is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using predesigned patterns. The proposed method modifies the feedback packet by introducing the concept of a to select a suitable group pattern and a to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.
机译：大规模多输入多输出（MIMO）的最新工作表明，通过在基站上部署大量天线可以实现容量增益的潜在突破。为了实现大规模MIMO系统所承诺的性能，准确的发射侧信道状态信息（CSI）应该在基站上可用。尽管可以通过在时分双工（TDD）系统中采用信道互易性来获得发送方CSI，但是对于频分双工（FDD）系统，需要从用户终端到基站的CSI明确反馈。在本文中，我们为基于FDD的大规模MIMO系统提出了一种基于天线分组的反馈减少技术。拟议的算法称为天线组波束成形（AGB），它使用预先设计的模式将多个相关的天线元素映射到单个代表值。所提出的方法通过引入a的概念来修改反馈分组，以选择合适的组模式并量化a的降维信道向量。仿真结果表明，与在相同目标和速率要求下对整个信道矢量进行矢量量化的常规方法相比，该方法可显着降低反馈开销。

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