首页|Tensor Decomposition-Based Channel Estimation and Sensing for Millimeter Wave MIMO-OFDM V2I Systems
Tensor Decomposition-Based Channel Estimation and Sensing for Millimeter Wave MIMO-OFDM V2I Systems
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维普
An integrated sensing and communication (ISAC) scheme for a millimeter wave (mmWave) multiple-input multiple-output or-thogonal frequency division multiplexing (MIMO-OFDM) Vehicle-to-Infrastructure (V2I) system is presented,in which both the access point (AP) and the vehicle are equipped with large antenna arrays and employ hybrid analog and digital beamforming structures to com-pensate the path loss,meanwhile compromise between hardware complexity and system performance. Based on the sparse scattering na-ture of the mmWave channel,the received signal at the AP is organized to a four-order tensor by the introduced novel frame structure. A CANDECOMP/PARAFAC (CP) decomposition-based method is proposed for time-varying channel parameter extraction,including angles of departure/arrival (AoDs/AoAs),Doppler shift,time delay and path gain. Then leveraging the estimates of channel parameters,a nonlin-ear weighted least-square problem is proposed to recover the location accurately,heading and velocity of vehicles. Simulation results show that the proposed methods are effective and efficient in time-varying channel estimation and vehicle sensing in mmWave MIMO-OFDM V2I systems.
万方数据
维普
