TY - JOUR
T1 - Intelligent Surface Aided D2D-V2X System for Low-Latency and High-Reliability Communications
AU - Gu, Xiaohui
AU - Zhang, Guoan
AU - Ji, Yancheng
AU - Duan, Wei
AU - Wen, Miaowen
AU - Ding, Zhiguo
AU - Ho, Pin Han
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grants 61971245 and 61801249 and in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, and in part by the Guang dong Basic and Applied Basic Research Project under Grant 2021B1515120067
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2022/11/1
Y1 - 2022/11/1
N2 - With low-cost energy consumption, the reconfigurable intelligent surface (RIS) technique is a potential solution to the real-time data processing for intelligent transportation systems (ITSs). In this paper, an intelligent transmissive surface is introduced into the vehicular communications, enabling vehicle-to-infrastructure (V2I) signals to penetrate the intelligent RIS to access the base station (BS) on the opposite side of the vehicle. Considering that the vehicle-to-vehicle (V2V) communication reuses the spectrum spanned for V2I link, we investigate the ergodic capacity optimization problem for the vehicle performing V2I communications with the assistance of RIS, while meeting the low-latency and high-reliability requirements of the V2V link. The RIS transmission coefficients and power allocation of vehicles are jointly optimized, for the management of the desired and undesired vehicular communication links. Moreover, the expression of optimal phase shifts is derived in a closed-form, which reveals that the performance gain brought by RIS is proportional to the number of intelligent elements, while inversely proportional to the distance from vehicle-to-BS, in a quadratic form. Moreover, in the case of discrete phase shifts, an intelligent algorithm is proposed for the beamforming design at RIS. Afterwards, with the objective to maximize the ergodic capacity of the V2I link, the optimal power allocation is also proposed. Simulation results confirm the accuracy of the proposed resource allocation strategy, and that the system performance in terms of the ergodic V2I capacity can be significantly improved by the RIS.
AB - With low-cost energy consumption, the reconfigurable intelligent surface (RIS) technique is a potential solution to the real-time data processing for intelligent transportation systems (ITSs). In this paper, an intelligent transmissive surface is introduced into the vehicular communications, enabling vehicle-to-infrastructure (V2I) signals to penetrate the intelligent RIS to access the base station (BS) on the opposite side of the vehicle. Considering that the vehicle-to-vehicle (V2V) communication reuses the spectrum spanned for V2I link, we investigate the ergodic capacity optimization problem for the vehicle performing V2I communications with the assistance of RIS, while meeting the low-latency and high-reliability requirements of the V2V link. The RIS transmission coefficients and power allocation of vehicles are jointly optimized, for the management of the desired and undesired vehicular communication links. Moreover, the expression of optimal phase shifts is derived in a closed-form, which reveals that the performance gain brought by RIS is proportional to the number of intelligent elements, while inversely proportional to the distance from vehicle-to-BS, in a quadratic form. Moreover, in the case of discrete phase shifts, an intelligent algorithm is proposed for the beamforming design at RIS. Afterwards, with the objective to maximize the ergodic capacity of the V2I link, the optimal power allocation is also proposed. Simulation results confirm the accuracy of the proposed resource allocation strategy, and that the system performance in terms of the ergodic V2I capacity can be significantly improved by the RIS.
KW - D2D
KW - high reliability
KW - Intelligent transmissive surface
KW - low latency
KW - V2X communi-cations
UR - https://www.scopus.com/pages/publications/85134265755
U2 - 10.1109/TVT.2022.3189627
DO - 10.1109/TVT.2022.3189627
M3 - Article
AN - SCOPUS:85134265755
SN - 0018-9545
VL - 71
SP - 11624
EP - 11636
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 11
ER -