基于TS-OMP的IRS辅助毫米波大规模MIMO信道估计方案

doi:10.12305/j.issn.1001-506X.2026.03.32

Abstract

Abstract:

To address the high pilot overhead in channel estimation for intelligent reflecting surface（IRS） assisted large-scale multiple-input multiple-output （MIMO） millimeter-wave systems, a channel estimation scheme based on the triple-structured orthogonal matching pursuit （TS-OMP） is proposed. By exploiting the angular spread characteristics of the channel, the triple-structured sparsity of the beamspace cascaded channel matrix is revealed. Leveraging this structured sparsity, the problem of channel estimation is reformulated as a problem of triple-structured sparse signal recovery. The proposed TS-OMP algorithm addresses this by first estimating the sparse row indices and intra-cluster column offsets for a subset of users. These estimated indices and offsets are then utilized as prior information to estimate the channel state information for all users. Simulation results demonstrate that the performance and pilot overhead of this scheme are significantly better than existing approaches.

Key words: channel estimation, intelligent reflecting surface, compressed sensing, millimeter wave, angular spread

CLC Number:

TN 929.5

Yan LIANG, Weiyang TU, Junqing WANG, Fei LI. IRS assisted millimeter wave massive MIMO channel estimation based on TS-OMP[J]. Systems Engineering and Electronics, 2026, 48(3): 1083-1090.

Figures/Tables 11

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References 19

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算法	计算复杂度
Row-OMP	$ O(KQMN{\bar L_k}{\bar P_{{l_k}}}) $
S-OMP	$ O(KQMNL{\bar L_k}) $
DS-OMP	$ O(KQM) + O(KQNL{\bar P_l}{\bar L_k}^3{\bar P_{{l_k}}}^3) $
TS-OMP	$ O(k'QMNL) + O(k'{N^2}L{\bar P_l}) + O(KQNL{\bar P_l}{\bar L_k}{\bar P_{{l_k}}}) $

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IRS assisted millimeter wave massive MIMO channel estimation based on TS-OMP

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