Subspace-Orthogonal Channel Estimation and Localization for RIS-assisted SIMO Systems
[1]LI Shuangzhi,WANG Zhen,GUO Xin.Subspace-Orthogonal Channel Estimation and Localization for RIS-assisted SIMO Systems[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-8.[doi:10. 13705 / j. issn. 1671-6833. 2027. 01. 006]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
48
Number of periods:
2027 XX
Page number:
1-8
Column:
Public date:
2027-12-10
- Title:
- Subspace-Orthogonal Channel Estimation and Localization for RIS-assisted SIMO Systems
- Keywords:
- millimeter-wave communication; channel estimation; subspace orthogonality; three-dimensional localization; reconfigurable intelligent surface(RIS)
- CLC:
- TN92TN96
- Abstract:
- : In reconfigurable intelligent surface (RIS) -assisted single-input multiple-output ( SIMO) systems, because the direct path and the RIS cascaded reflected path overlap at the receiver, channel parameter estimation and user localization face high computational complexity and high pilot overhead. To address this challenge, a two-stage low-pilot-overhead channel estimation and localization method was proposed based on subspace-orthogonal separation. In the first stage, an orthogonal projection matrix of the direct channel subspace was constructed. Then the received signal was projected onto its orthogonal complement space. This effectively separated the direct path from the RIS cascaded reflected path. After that, key channel parameters such as spatial frequencies and delays were extracted by methods such as rank-one approximation. In the second stage, the geometric constraint relationship between the channel parameters and the three-dimensional coordinates was used to estimate the user′s 3D position. Theoretical analysis showed that by subspace decoupling and channel parametric representation, the proposed algorithm could complete both channel estimation and localization with only a small number of pilots. Simulation results showed that the proposed algorithm achieved decimeter-level localization accuracy at 0 dB. Under different conditions, both the parameter estimation performance and the localization error could closely follow the theoretical lower bounds, verifying the statistical efficiency and robustness of the algorithm.
- References:
- -
- Similar References:
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Last Update:
2026-10-27
