## 3 Proposed CG-LIB Algorithm and User Vehicle Localization
### User Vehicle Localization
Utilizing the CG-LHB algorithm, we were able to significantly improve spectral efficiency in mmWave MIMO systems. In addition, for user vehicle localization, we considered a channel covariance splitting method and proposed a double-step iterative algorithm that reduces the effect of location error on the passive beamforming. We validated the effectiveness of the proposed algorithms using the conventional algorithms. Hence, the proposed RIS-assisted CG-LHB algorithm can be extended further to the machine learning-based beam alignment and location error minimization solution of the connected autonomous vehicles, which will be explored in future studies. [PERSON] made contributed to the conception and design, acquisition of data, analysis, and interpretation of data. [PERSON] contributed to data collection. [PERSON] supervised the work and helped in the implementation part. All authors have read and agreed to the published version of the manuscript. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1A6A1A03043144). **Institutional Review Board Statement:** Not Applicable. **Informed Consent Statement:** Not Applicable. Figure 8: Average bit–error–rate versus SNR in a RIS system at \(N_{i}=4\), \(N_{t}=8\)\(N_{R}=256\). Figure 9: Channel state information error bound versus the number of RIS elements. ## References

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