一种用于超大规模MIMO下行近场信道估计的联合码本设计OA

As one of the core enabling technologies for 6G,extremely large-scale multiple-input multiple-output(XL-MIMO)technology will significantly expand the range of near-field regions.The spherical wave properties of the near-field channel lead to a significant performance degradation in channel estimation algorithms based on compressed sensing(CS).To address this issue,a jointcodebook design scheme is proposed.The joint codebook is constructed in two parts.The transmit-side codebook is designed through eigenvalue decomposition(EVD)of the near-field downlink channel autocorrelation matrix with a central frequency offset.The tight connection between the eigenvectors of the channel autocorrelation matrix and the modulated discrete prolate spheroidal sequences(MDPSS)is revealed.A fast method for directly calculating the channel autocorrelation matrix is proposed to enable efficient eigenvalue decomposition.The receive-side codebook is constructed through a weighted summation of discrete Fourier transform(DFT)and discrete cosine transform(DCT)codebooks.A hierarchical optimization method is proposed to determine the optimal weighting factors.Simulation results show that the proposed joint codebook reduces storage complexity while achieving better channel estimation performance and robustness.The normalized mean square error performance of channel estimation is,on average,reduced by approximately 10 dB compared with that of traditional codebooks.