An Effective Simultaneous Channel Estimation and Sensing Algorithm for MmWave MIMO-OFDM Systems

In this paper, an effective simultaneous channel estimation and sensing algorithm is proposed for millimeter wave (mmWave) multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. The proposed algorithm consists of a two-stage channel estimation scheme and a reliable sensing scheme, which enables high-quality channel estimation and precise sensing in three-dimensional (3D) space. Specifically, the proposed algorithm first puts forward an improved simultaneous orthogonal matching pursuit algorithm that utilizes structural relation between the sparse basis and indexes to implement coarse estimation of multiple parameters. Subsequently, taking the obtained coarse parameters as initial values, optimization of channel parameters is achieved using the idea of maximum likelihood and gradient descent algorithm. Finally, we develop a reliable sensing scheme to realize user localization and mapping of scattering environment in various scenarios. Cramér-Rao bounds (CRBs) of the parameters and positions are also derived and used as a benchmark in simulations. Simulation results demonstrate that compared with the existing algorithms, the proposed algorithm has better channel estimation and sensing performance and is closer to CRBs. Moreover, even in challenging environment with unknown user orientation and clock bias, the proposed algorithm can achieve precise user localization and mapping of scattering environment.