The Subarray MUSIC for Direction of Arrival Estimation in Hybrid Analog-digital System
Yan Ling Zhou, Guodong Wang, Yanyan Li, Xiaoxuan Chen, Na Meng · 2024
The emerging hybrid analog-digital system (HADS) has gained significant attention for future millimeter-wave communications due to its potential to substantially reduce power consumption and hardware costs. However, traditional subspace-based direction of arrival (DOA) estimation algorithms, such as the multiple signal classification (MUSIC) algorithm, cannot be directly applied in HADS. The beam sweeping algorithm (BSA) was initially proposed to enable subspace-based DOA estimation in this context, but it is computationally intensive due to the need for high-dimensional matrix reconstruction. To address this issue, we propose a subarray MUSIC algorithm for DOA estimation in HADS (HADS-SMUSIC), which offers low computational complexity without the requirement for high-dimensional matrix reconstruction. By directly collecting the beamformed signal from each subarray, we establish a signal model for the subarrays that shares the same array manifold as a uniform linear array. This allows us to leverage subarray signals to construct both the signal and noise subspaces for MUSIC. Simulation experiments are conducted to validate the performance of the proposed algorithm.