Channel Estimation for XL-MIMO Systems With Polar-Domain Multi-Scale Residual Dense Network

被引:19
作者
Lei, Hao [1 ]
Zhang, Jiayi [1 ]
Xiao, Huahua [2 ,3 ]
Zhang, Xiaodan [4 ]
Ai, Bo [5 ]
Ng, Derrick Wing Kwan [6 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[2] ZTE Corp, Shenzhen 518057, Peoples R China
[3] State Key Lab Mobile Network & Mobile Multimedia T, Shenzhen 518057, Peoples R China
[4] Shenzhen Inst Informat Technol, Sch Management, Shenzhen 518172, Peoples R China
[5] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
[6] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
关键词
Near-field communication; XL-MIMO; channel estimation; deep learning; MASSIVE MIMO;
D O I
10.1109/TVT.2023.3311010
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technique to enable versatile applications for future wireless communications. In conventional massive MIMO, the channel is often modeled by the far-field planar-wavefront with rich sparsity in the angular domain that facilitates the design of low-complexity channel estimation. However, this sparsity is not conspicuous in XL-MIMO systems due to the non-negligible near-field spherical-wavefront. To address the inherent performance loss of the angular-domain channel estimation schemes, we first propose the polar-domain multiple residual dense network (P-MRDN) for XL-MIMO systems based on the polar-domain sparsity of the near-field channel by improving the existing MRDN scheme. Furthermore, a polar-domain multi-scale residual dense network (P-MSRDN) is designed to improve the channel estimation accuracy. Finally, simulation results reveal the superior performance of the proposed schemes compared with existing benchmark schemes and the minimal influence of the channel sparsity on the proposed schemes.
引用
收藏
页码:1479 / 1484
页数:6
相关论文
共 20 条
[1]   Real Image Denoising Based on Multi-Scale Residual Dense Block and Cascaded U-Net with Block-Connection [J].
Bao, Long ;
Yang, Zengli ;
Wang, Shuangquan ;
Bai, Dongwoon ;
Lee, Jungwon .
2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), 2020, :1823-1831
[2]   Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation [J].
Chen, Liang-Chieh ;
Zhu, Yukun ;
Papandreou, George ;
Schroff, Florian ;
Adam, Hartwig .
COMPUTER VISION - ECCV 2018, PT VII, 2018, 11211 :833-851
[3]   Hybrid Spherical- and Planar-Wave Modeling and DCNN-Powered Estimation of Terahertz Ultra-Massive MIMO Channels [J].
Chen, Yuhang ;
Yan, Longfei ;
Han, Chong .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2021, 69 (10) :7063-7076
[4]   Channel Modeling and Channel Estimation for Holographic Massive MIMO With Planar Arrays [J].
Demir, Ozlem Tugfe ;
Bjornson, Emil ;
Sanguinetti, Luca .
IEEE WIRELESS COMMUNICATIONS LETTERS, 2022, 11 (05) :997-1001
[5]   Channel Estimation for Extremely Large-Scale Massive MIMO Systems [J].
Han, Yu ;
Jin, Shi ;
Wen, Chao-Kai ;
Ma, Xiaoli .
IEEE WIRELESS COMMUNICATIONS LETTERS, 2020, 9 (05) :633-637
[6]   Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems [J].
Huang, Chongwen ;
Liu, Lei ;
Yuen, Chau ;
Sun, Sumei .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2019, 67 (01) :245-259
[7]   Multiple Residual Dense Networks for Reconfigurable Intelligent Surfaces Cascaded Channel Estimation [J].
Jin, Yu ;
Zhang, Jiayi ;
Huang, Chongwen ;
Yang, Liang ;
Xiao, Huahua ;
Ai, Bo ;
Wang, Zhiqin .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (02) :2134-2139
[8]   Intelligent Near-Field Channel Estimation for Terahertz Ultra-Massive MIMO Systems [J].
Lee, Anho ;
Ju, Hyungyu ;
Kim, Seungnyun ;
Shim, Byonghyo .
2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, :5390-5395
[9]   Channel Estimation via Orthogonal Matching Pursuit for Hybrid MIMO Systems in Millimeter Wave Communications [J].
Lee, Junho ;
Gil, Gye-Tae ;
Lee, Yong H. .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2016, 64 (06) :2370-2386
[10]  
Lei H., 2023, Uplink performance of cell-free extremely large-scale MIMO systems