Joint Hybrid Precoding and Combining Design Based Multi-Stage Compressed Sensing Approach for mmWave MIMO Channel Estimation

Although the design of hybrid precoders and combiners separately from the complete channel state information (CSI) offers satisfactory performance, the resulting spatial multiplexing channel may not always be orthogonal during communication. Also, acquiring CSI to design optimal precoders and combiners poses several challenges, particularly in millimeter wave (mmWave) channel estimation, and getting the sensing matrix is equivalent to designing the precoders and combiners. For this, we propose a new iterative method based on alternating minimization to design the optimal sensing matrix (incoherent projection matrix) with the given dictionary to minimize the mutual coherence values ( $\mu _{mx}$ , $\mu _{ave}$ and $\mu _{all}$ ) simultaneously according to the equiangular tight frame (ETF) properties for achieving better-compressed sensing (CS) recovery performance. Then, in order to derive the best hybrid precoders and combiners jointly from the optimally designed sensing matrix, we formulate the optimization design problem as the nearest Kronecker product (NKP) problem. The proposed sensing matrix design works better at lowering the mutual coherence values concurrently with the straightforward shrinkage function, according to simulation findings of mutual coherence values evolution versus outer iteration numbers. In comparison to existing codebook-based hybrid precoder/combiner schemes, the proposed joint hybrid precoder and combiner design improves the performance of the simulation results obtained by multi-stage CS-based mmWave channel estimation in terms of channel estimation accuracy and spectral efficiency (SE).