FDD无蜂窝大规模MIMO系统CSI反馈及预编码研究

张德坤; 白宝明

doi:10.11959/j.issn.1000-0801.2024253

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FDD无蜂窝大规模MIMO系统CSI反馈及预编码研究

研究与开发 | 更新时间：2024-12-30

- FDD无蜂窝大规模MIMO系统CSI反馈及预编码研究
- Research on CSI feedback and precoding in FDD cell-free massive MIMO systems
- 电信科学 2024年40卷第12期页码：63-73
- 作者机构：
  
  1.西安电子科技大学空天地一体化综合业务网全国重点实验室，陕西西安 710071
  2.中兴通讯股份有限公司，广东深圳 518055
- 作者简介：
  
  [ "张德坤（1990- ），男，西安电子科技大学空天地一体化综合业务网全国重点实验室博士生，中兴通讯股份有限公司算法工程师，中国通信学会高级会员，主要研究方向为大规模MIMO、无线资源管理、天线校准等。" ]
  [ "白宝明（1967- ），男，博士，西安电子科技大学空天地一体化综合业务网全国重点实验室教授，主要研究方向为无线通信、MIMO技术、信息论与信道编码等。" ]
- 基金信息：
  
  国家重点研发计划项目(2021YFA000500)
- DOI：10.11959/j.issn.1000-0801.2024253
  中图分类号： TN929.5
- 收稿日期：2024-09-22，
  
  修回日期：2024-11-25，
  
  纸质出版日期：2024-12-20
- 稿件说明：
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张德坤,白宝明.FDD无蜂窝大规模MIMO系统CSI反馈及预编码研究[J].电信科学,2024,40(12):63-73.

ZHANG Dekun,BAI Baoming.Research on CSI feedback and precoding in FDD cell-free massive MIMO systems[J].Telecommunications Science,2024,40(12):63-73.
张德坤,白宝明.FDD无蜂窝大规模MIMO系统CSI反馈及预编码研究[J].电信科学,2024,40(12):63-73. DOI： 10.11959/j.issn.1000-0801.2024253.

ZHANG Dekun,BAI Baoming.Research on CSI feedback and precoding in FDD cell-free massive MIMO systems[J].Telecommunications Science,2024,40(12):63-73. DOI： 10.11959/j.issn.1000-0801.2024253.

摘要

实现频分复用（frequency division duplexing，FDD）无蜂窝大规模多输入多输出（multiple input multiple output，MIMO）系统的下行系统容量最大化，关键在于设计既具有高成形增益又能强效抑制多用户间干扰的预编码矩阵，而精准的下行链路信道状态信息（channel state information，CSI）的获取则是计算预编码矩阵的基础。FDD制式由于上下行链路不具备完美互易性，故低开销、高精度的下行CSI获取是业界难题。为此，提出了一种基于共址空间用户簇的CSI测量和反馈方案，同时设计了联合簇级CSI反馈的两段式预编码优化方案。首先，基于上下行统计互易性计算获得等效下行空间相关性，利用用户反馈的信道质量和等效空间相关性联合构建了共址空间用户簇。其次，基于大尺度衰落特征和CSI导频端口能力约束，设计了CSI相干测量动态方案，以及共址空间簇的统计CSI反馈方案，显著地降低了反馈开销。最后，在CSI测量阶段通过簇间用户统计协方差矩阵设计了大尺度缓变干扰消除预编码，在下行调度阶段基于信号泄露噪声比（signal-to-leakage-and-noise ratio，SLNR）算法设计了簇内实时多用户干扰消除预编码，二者级联构成每个用户的下行预编码优化权值。仿真结果表明，提出的CSI反馈优化方案相对于文献中主路径增益信息反馈策略降低反馈开销34%，两段式预编码优化方案相对于SLNR预编码提升FDD无蜂窝大规模MIMO频谱效率10.8%。

Abstract

For frequency division duplexing (FDD) cell-free massive multiple input multiple output (MIMO) systems

maximizing downlink capacity relies on designing a precoding matrix that achieves high beamforming gain and effectively suppresses multi-user interference. The accurate acquisition of downlink channel state information (CSI) is essential for calculating precoding matrix. However

due to the imperfect reciprocity between uplink and downlink in FDD systems

securing low-overhead and high-precision downlink CSI remains an industry challenge. Therefore

a CSI measurement and feedback scheme on the basis of co-located spatial user clusters was proposed

along with a two-stage precoding optimization scheme that integrated cluster-level CSI feedback. Firstly

equivalent downlink spatial correlation was obtained based on the calculation of uplink and downlink statistical reciprocity

and co-located space user clusters were jointly constructed using the downlink channel quality and equivalent spatial correlation. Secondly

a dynamic CSI coherent measurement scheme was designed based on large-scale fading characteristics and CSI pilot port capacity constraints

and a statistical CSI feedback scheme for co-located space clusters was developed

significantly reducing feedback overhead. Finally

during the CSI measurement phase

large-scale slowly varying interference elimination precoding was designed using the statistical covariance matrix between cluster users. During the downlink scheduling phase

real-time multi-user interference elimination precoding within clusters was designed on the basis of the signal-to-leakage-and-noise ratio (SLNR) algorithm. The two were cascaded to form the optimized downlink precoding weight values for each user. Simulation results show that the proposed CSI feedback optimization scheme reduces the feedback overhead by 34% compared with the path gain information feedback strategy in the literature

and the two-stage precoding optimization scheme improves the FDD non-cellular massive MIMO spectral efficiency by 10.8% compared with the SLNR precoding.

关键词

Keywords

references

NGO H Q , ASHIKHMIN A , YANG H , et al . Cell-free massive MIMO versus small cells [J ] . IEEE Transactions on Wireless Communications , 2017 , 16 ( 3 ): 1834 - 1850 .

ZHANG J Y , CHEN S F , LIN Y , et al . Cell-free massive MIMO: a new next-generation paradigm [J ] . IEEE Access , 2019 , 7 : 99878 - 99888 .

郭劭 , 潘鹏 , 范耀宗 . CF-mMIMO系统中一种基于用户极坐标的低复杂度导频分配算法 [J ] . 电信科学 , 2023 , 39 ( 7 ): 1 - 10 .

GUO S , PAN P , FAN Y Z . A low complexity pilot assignment algorithm based on user polar coordinates in CF-mMIMO systems [J ] . Telecommunications Science , 2023 , 39 ( 7 ): 1 - 10 .

王东明 . 面向6G的无蜂窝大规模MIMO无线传输技术 [J ] . 移动通信 , 2021 , 45 ( 4 ): 10 - 15 .

WANG D M . Wireless transmission techniques of cell-free massive MIMO for 6G mobile communications [J ] . Mobile Communications , 2021 , 45 ( 4 ): 10 - 15 .

LEE G , RAHMAN M S , ONGGOSANUSI E . CSI feedback for distributed MIMO [C ] // Proceedings of the 2022 IEEE Wireless Communications and Networking Conference (WCNC) . Piscataway : IEEE Press , 2022 : 2154 - 2159 .

JIN Y , ZHANG J Y , JIN S , et al . Channel estimation for cell-free mmWave massive MIMO through deep learning [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 10 ): 10325 - 10329 .

JINDAL N . MIMO broadcast channels with finite-rate feedback [J ] . IEEE Transactions on Information Theory , 2006 , 52 ( 11 ): 5045 - 5060 .

LEE B , CHOI J , SEOL J Y , et al . Antenna grouping based feedback compression for FDD-based massive MIMO systems [J ] . IEEE Transactions on Communications , 2015 , 63 ( 9 ): 3261 - 3274 .

SHEN W Q , DAI L L , SHI Y , et al . Joint channel training and feedback for FDD massive MIMO systems [J ] . IEEE Transactions on Vehicular Technology , 2016 , 65 ( 10 ): 8762 - 8767 .

LIANG H W , CHUNG W H , KUO S Y . FDD-RT: a simple CSI acquisition technique via channel reciprocity for FDD massive MIMO downlink [J ] . IEEE Systems Journal , 2018 , 12 ( 1 ): 714 - 724 .

YIN H F , GESBERT D . A partial channel reciprocity-based codebook for wideband FDD massive MIMO [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 9 ): 7696 - 7710 .

LIU Y S , SIMEONE O . Learning how to transfer from uplink to downlink via hyper-recurrent neural network for FDD massive MIMO [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 10 ): 7975 - 7989 .

KIM S , CHOI J W , SHIM B . Downlink pilot precoding and compressed channel feedback for FDD-based cell-free systems [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 6 ): 3658 - 3672 .

CHENG X , WANG C X , WANG H M , et al . Cooperative MIMO channel modeling and multi-link spatial correlation properties [J ] . IEEE Journal on Selected Areas in Communications , 2012 , 30 ( 2 ): 388 - 396 .

ZHOU T , TAO C , SALOUS S , et al . Geometry-based multi-link channel modeling for high-speed train communication networks [J ] . IEEE Transactions on Intelligent Transportation Systems , 2020 , 21 ( 3 ): 1229 - 1238 .

ZHANG L , CHEN X Y , ZHOU Z H , et al . A novel 3D non-stationary multi-frequency multi-link wideband MIMO channel model [C ] // Proceedings of the 2020 International Conference on Wireless Communications and Signal Processing (WCSP) . Piscataway : IEEE Press , 2020 : 1016 - 1021 .

GUO J J , WEN C K , JIN S . Deep learning-based CSI feedback for beamforming in single- and multi-cell massive MIMO systems [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 7 ): 1872 - 1884 .

LIU S C , GAO Z , HU C , et al . Model-driven deep learning based precoding for FDD cell-free massive MIMO with imperfect CSI [C ] // Proceedings of the 2022 International Wireless Communications and Mobile Computing (IWCMC) . Piscataway : IEEE Press , 2022 : 696 - 701 .

胡亚婷 , 史恩宇 , 许柏恺 , 等 . RIS辅助去蜂窝大规模MIMO系统低复杂度预编码算法设计 [J ] . 无线电通信技术 , 2024 , 50 ( 2 ): 245 - 252 .

HU Y T , SHI E Y , XU B K , et al . Low complexity precoding algorithm design for RIS-aided cell-free massive MIMO systems [J ] . Radio Communications Technology , 2024 , 50 ( 2 ): 245 - 252 .

苏俊 , 张磊 , 何斌 , 等 . 5G多天线增强关键技术研究 [J ] . 移动通信 , 2023 , 47 ( 9 ): 110 - 116 .

SU J , ZHANG L , HE B , et al . Study on 5G MIMO enhancement key technologies [J ] . Mobile Communications , 2023 , 47 ( 9 ): 110 - 116 .

NGUYEN L D , DUONG T Q , NGO H Q , et al . Energy efficiency in cell-free massive MIMO with zero-forcing precoding design [J ] . IEEE Communications Letters , 2017 , 21 ( 8 ): 1871 - 1874 .

ALBREEM M A , AL HABBASH A H , ABU-HUDROUSS A M , et al . Overview of precoding techniques for massive MIMO [J ] . IEEE Access , 2021 , 9 : 60764 - 60801 .

ZHANG P , ZHANG J Y , XIAO H H , et al . Joint distributed precoding and beamforming for RIS-aided cell-free massive MIMO systems [J ] . IEEE Transactions on Vehicular Technology , 2024 , 73 ( 4 ): 5994 - 5999 .

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