A Tensor-Based High Resolution Millimeter Wave Massive MIMO Channel Parameters Estimation Scheme

Channel estimation is vital for wireless communication and channel sounding. In this paper, we propose a tensor-based high-resolution estimation method for a millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) based channel sounding system with hybrid beamforming (HBF) adopted. At the transmitter (Tx), the OFDM pilot signal is sent with the help of a precoder with random phases. At the receiver (Rx) configured with a random-phased combiner, the received signal is concatenated into a third-order tensor which follows a CANDECOMP/PARAFAC (CP) decomposition to prospect implicit channel information. The CP decomposition is solved by leveraging the Vandermonde structure of the factor matrices, from which the channel parameters are estimated by correlation-based searching. Simulation results with the synthesized channel data illustrate that the proposed tensor-based algorithm can obtain high stability and accuracy. The influence of the pilot sequence length on the accuracy of the proposed algorithm is also discussed. Furthermore, we find that the proposed algorithm is not affected by the quantization bit of the precoder and combiner.