Beamspace Channel Estimation for the Millimeter-wave Massive MIMO Systems: Dual Loops-based Iteration Reduction Algorithms

• Published in: IEEE transactions on vehicular technology pp. 1 - 12
• Main Authors: Zhu, Lijun, Li, Zheng, An, Zeliang, Chu, Zheng, Zhu, Zhengyu, Chen, Gaojie, Li, Yonghui
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: Accuracy; Antenna arrays; beamspace channel estimation; Channel estimation; dual-loop; FISTAB; iterative reduction algorithm; Lenses; Massive MIMO; Matching pursuit algorithms; Millimeter wave communication; mmWave; Radio frequency; Signal processing algorithms; Vectors
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2025.3612767

In the millimeter-wave (mmWave) massive multipleinput multiple-output (MIMO) channel estimation problem blue employing lens antenna arrays, conventional compressed sensing algorithms demand numerous matrix-vector multiplications per iteration, thereby incurring substantial computational complexity. To address this challenge, we propose dual-loop beamspace channel estimation strategies that leverage the sparsity of the mmWave beamspace channel, formulating the estimation problem as a sparse signal recovery task. First, we design an effective dual-loop algorithm based on the ℓ 1 minimization problem to tackle the channel estimation problem. In the outer loop, an ℓ 1 - based iterative reduction algorithm (ℓ 1 -IRA) reduces the largescale channel estimation problem to a series of small-scale subproblems by exploiting the sparsity of the beamspace channel. In the inner loop, the fast iterative shrinkage thresholding algorithm with backtracking (FISTAB) algorithm is used to solve these subproblems efficiently. Furthermore, conventional compressed sensing algorithms exhibit favorable performance in weakly correlated systems but suffer from significant performance degradation in strongly correlated scenarios. To mitigate this limitation, we design an ℓ 1−2 minimization problem-based IRA (ℓ 1−2 -IRA) for the beamspace channel estimation problem. Finally, simulation results show that the proposed dual loop methods significantly reduce pilot overhead and improve beamspace channel estimation accuracy compared to conventional channel estimation techniques.