A Block Sparsity Based Channel Estimation Technique for mmWave Massive MIMO with Beam Squint Effect

Multiple-input multiple-output (MIMO) millimeter wave (mmWave) communication is a key technology for next generation wireless networks. As the number of antennas becomes larger and the transmission bandwidth becomes wider, the array steering vectors would vary at different subcarriers, causing the beam squint effect. In this case, the conventional channel model is no longer applicable, especially for the mmWave massive MIMO system. In this paper, we first explain the influence of the beam squint effect from the array signal processing perspective and then investigate the angle-delay sparsity of mmWave transmission. We next design a compressive sensing (CS) algorithm based on shift-invariant block-sparsity that can jointly compute the off-grid angles, the off-grid delays, and the complex gains of the multi-path channel. Compared to either the conventional channel model, or the existing on-grid algorithms, the proposed one more accurately reflects the mmWave channel and is shown to yield better performance of uplink channel estimation.