## 1 Introduction
Unlike traditional DOA estimation systems, when tracking the phase of the reflected signal, a low-cost system with a complete DOA receiver is required. Therefore, the DOA estimation problem in V2X needs to be solved urgently. Also, it is difficult to handle the high-dimensional beam space in mmWave massive MIMO V2X. To decompose high-dimensional beam space, the tensor modeling-based method was proposed for the channel estimation and receiver design of two-hop MIMO V2X communication systems. Accurate high-dimensional channel estimation in highly mobile scenarios became necessary [28]. However, the rank solution corresponding to the canonical polyadic (CP) decomposition is a non-deterministic polynomial (NP) puzzle. A sparse Bayesian tensor of the channel estimation method based on DOA tracking for V2X mmWave massive MIMO systems was proposed [29]. An ultrasonic-assisted tensor channel estimation method for V2X mmWave massive MIMO systems was proposed to improve the safety of cooperative autonomous driving [30]. Ultrasonic-assisted tensor beamforming is a low-cost system capable of decomposing high-dimensional beam space. In order to solve the above problems, a Tucker tensor-based joint beamforming scheme with ultrasonic and RIS-assisted for dual-hop hybrid FSO-mmWave massive MIMO of V2X is proposed. Firstly, to address the occlusion problem in V2X communication, the RIS-assisted mixed FSO-MIMO V2X system is proposed. The FSO system model and mmWave massive MIMO signal model framework are proposed. Secondly, in order to simultaneously consider solving precise direction of arrival (DOA) estimation and low-cost hardware problems, an ultrasonic array signal model is researched. The beamformingof RIS-assisted mmWave massive MIMO V2X with low-cost ultrasonics is designed. The DOA information is obtained via accurate measurement of the target's position and angle information. Thirdly, an ultrasonic-assisted RIS phase shift matrix based on subspace self-organizing iterations is designed. Specifically, the associated bandwidth-efficiency maximization problem is transformed into a series of subproblems, where the subarray of phase shifters and RIS elements is jointly optimized to maximize each subarray's rate. The vehicle motion state is transformed into a two-dimensional model for prior distribution to calculate the particle weights of the RIS phase shift matrix. Finally, since the traditional tensor decomposition corresponding to the rank solution is an NP problem, we conceive a multi-vehicle joint optimization method used to design the hybrid beamforming matrix of the BS and the passive beamforming matrix of the RIS. Multi-vehicle Tucker tensor decomposition is used to describe the high-dimensional beam space. A cascaded channel decomposition method based on SVD (Singular Value Decomposition) is used to achieve the combined matrix beamforming of the BS and vehicles. Our simulation results demonstrate the superiority of the proposed method compared to its traditional counterparts. The rest of the paper is organized as follows. Section 2 introduces the system model. Section 3 presents the ultrasonic and RIS-assisted mmWave massive MIMO V2X joint beamforming problem. Section 4 designs the ultrasonic-assisted RIS phase shift matrix based on subspace self-organizing iterations. Section 5 designs the BS beamforming matrix. In Section 6, the tensor-based design of the user vehicle combination matrix is presented. Section 7 presents the simulation results and, finally, our discussion and summary of the article.