TY - GEN
T1 - DPSS-Based Codebook Design for Near-Field XL-MIMO Channel Estimation
AU - Liu, Shicong
AU - Yu, Xianghao
AU - Gao, Zhen
AU - Ng, Derrick Wing Kwan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is essential for beamforming and data detection, the unique characteristics of near-field channels pose additional challenges to the effective acquisition of channel state information. In this paper, we propose a novel codebook design, which allows efficient near-field channel estimation with significantly reduced codebook size. Specifically, we consider the eigen-problem based on the near-field electromagnetic wave transmission model. Moreover, we derive the general form of the eigenvectors associated with the near-field channel matrix, revealing their noteworthy connection to the discrete prolate spheroidal sequence (DPSS). Based on the proposed near-field codebook design, we further introduce a two-step channel estimation scheme. Simulation results demonstrate that the proposed codebook design not only achieves superior sparsification performance of near-field channels with a lower leakage effect, but also significantly improves the accuracy in compressive sensing channel estimation.
AB - Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is essential for beamforming and data detection, the unique characteristics of near-field channels pose additional challenges to the effective acquisition of channel state information. In this paper, we propose a novel codebook design, which allows efficient near-field channel estimation with significantly reduced codebook size. Specifically, we consider the eigen-problem based on the near-field electromagnetic wave transmission model. Moreover, we derive the general form of the eigenvectors associated with the near-field channel matrix, revealing their noteworthy connection to the discrete prolate spheroidal sequence (DPSS). Based on the proposed near-field codebook design, we further introduce a two-step channel estimation scheme. Simulation results demonstrate that the proposed codebook design not only achieves superior sparsification performance of near-field channels with a lower leakage effect, but also significantly improves the accuracy in compressive sensing channel estimation.
UR - http://www.scopus.com/inward/record.url?scp=85202894553&partnerID=8YFLogxK
U2 - 10.1109/ICC51166.2024.10622872
DO - 10.1109/ICC51166.2024.10622872
M3 - Conference contribution
AN - SCOPUS:85202894553
T3 - IEEE International Conference on Communications
SP - 3864
EP - 3870
BT - ICC 2024 - IEEE International Conference on Communications
A2 - Valenti, Matthew
A2 - Reed, David
A2 - Torres, Melissa
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 59th Annual IEEE International Conference on Communications, ICC 2024
Y2 - 9 June 2024 through 13 June 2024
ER -