{'fraction_non_alphanumeric': 0.026455026455026454, 'fraction_numerical': 0.0, 'mean_word_length': 5.753246753246753, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Robust Transmission for Reconfigurable Intelligent Surface Aided Millimeter Wave Vehicular Communications With Statistical CSI

The integration of reconfigurable intelligent surface (RIS) into millimeter wave (mmWave) vehicular communications offers the possibility to unleash the potential of future proliferating vehicular applications. However, the high-mobility-induced rapidly varying channel state information (CSI) has been making it challenging to obtain the accurate instantaneous CSI (I-CSI) and to cope with the incurable high signaling overhead. The situation may become worse when the RIS with a large number of passive reflecting elements is deployed. To overcome this challenge, we investigate in this paper a robust transmission scheme for the time-varying RIS-aided mmWave vehicular communications, in which, specifically, a multi-antenna base station (BS) serves vehicle user equipments (VUEs) with the help of RIS at the mmWave frequency. The uplink average achievable rate is maximized relying only upon the imperfect knowledge of statistical CSI. Considering the time-varying characteristics, we first propose an effective transmission protocol by reasonably configuring the time-scale of CSI acquisition in order to significantly relax the frequency of channel information updates, which constitutes one of the most critical issues in RIS-aided vehicular communications. Then, the formulated resource allocation problem is discussed in the single- and multi-VUE case, respectively. To be specific, for the single-VUE case, a closed-form expression of the average rate is derived by extracting the statistical characteristics of mmWave channels, and an alternating optimization (AO)-based algorithm is proposed. For the multi-VUE case, we develop an efficient algorithm, called JAPMC, to circumvent the unavailability of the closed-form of the objective function and probabilistic constraint by constructing quadratic surrogates of that. Simulation results confirm the effectiveness and robustness of our proposed algorithms as compared to benchmark schemes.