Cascaded Channel Estimation for RIS Assisted mmWave MIMO Transmissions

Channel estimation is challenging for the reconfigurable intelligence surface (RIS) assisted millimeter wave (mmWave) communications. Since the number of coefficients of the cascaded channels in such systems is closely dependent on the product of the number of base station antennas and the number of RIS elements, the pilot overhead would be prohibitively high. We propose a cascaded channel estimation framework for an RIS assisted mmWave multiple-input multiple-output system, where the wideband effect on transmission model is considered. Then, we transform the wideband channel estimation into a parameter recovery problem and use a few pilot symbols to detect the channel parameters by the Newtonized orthogonal matching pursuit algorithm. Moreover, the Cramer-Rao lower bound on the channel estimation is introduced. Numerical results show the effectiveness of the proposed channel estimation scheme.

[1]  Xiaojun Yuan,et al.  Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO , 2019, IEEE Journal on Selected Areas in Communications.

[2]  Shi Jin,et al.  Sparse Bayesian Learning for the Time-Varying Massive MIMO Channels: Acquisition and Tracking , 2019, IEEE Transactions on Communications.

[3]  Hai Lin,et al.  Beam Squint and Channel Estimation for Wideband mmWave Massive MIMO-OFDM Systems , 2019, IEEE Transactions on Signal Processing.

[4]  Sundeep Prabhakar Chepuri,et al.  Channel Estimation in Reconfigurable Intelligent Surface Assisted mmWave MIMO Systems , 2020, ArXiv.

[5]  Feifei Gao,et al.  Angle Domain Channel Estimation in Hybrid Millimeter Wave Massive MIMO Systems , 2018, IEEE Transactions on Wireless Communications.

[6]  Henk Wymeersch,et al.  Channel Estimation for RIS-Aided mmWave MIMO Channels , 2020, ArXiv.

[7]  Octavia A. Dobre,et al.  Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication , 2020, IEEE Transactions on Communications.

[8]  Behrouz Maham,et al.  Modeling RIS Empowered Outdoor-to-Indoor Communication in mmWave Cellular Networks , 2021, IEEE Transactions on Communications.

[9]  Shi Jin,et al.  Fast Antenna and Beam Switching Method for mmWave Handsets With Hand Blockage , 2021, IEEE Transactions on Wireless Communications.

[10]  Shi Jin,et al.  Efficient Downlink Channel Reconstruction for FDD Multi-Antenna Systems , 2018, IEEE Transactions on Wireless Communications.

[11]  H. Vincent Poor,et al.  Present and Future of Reconfigurable Intelligent Surface-Empowered Communications [Perspectives] , 2021, IEEE Signal Processing Magazine.

[12]  Caijun Zhong,et al.  Location Information Aided Multiple Intelligent Reflecting Surface Systems , 2020, IEEE Transactions on Communications.

[13]  Jihong Park,et al.  RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks , 2020, IEEE Access.

[14]  Junho Lee,et al.  Channel Estimation via Orthogonal Matching Pursuit for Hybrid MIMO Systems in Millimeter Wave Communications , 2016, IEEE Transactions on Communications.