| As an important technology for the deep integration of informatization and industrialization,the Internet of Vehicles(IoV)is one of the most promising fields in the Internet of Things(IoT)system,with the characteristics of significant industrial potential,broad range of applications and strong social benefits.The C-V2X technology,which is mainly promoted by 3 GPP,is based on wireless access in the sub-6GHz band-and can support a data rate of around 50Mb/s.However,in the development of automatic driving technology in the future,the intelligence and automation capabilities of vehicles will be upgraded and developed,and more complex sensors including on-board radar and vision cameras will be used,which requires the IoV to achieve Gbps data rate,millisecondlevel latency,and 99.99%reliability.However,both the IEEE 802.11p and C-V2X wireless access technology cannot support the communication requirements of autonomous driving for transmission rate and latency due to the limited spectrum resources available in the sub-6GHz frequency band.Therefore,it is necessary to explore new spectrum resources to support autonomous driving applications.The millimeter wave(mm Wave)frequency band,with rich spectrum resources,has received widespread attention from both the automotive industry and academia,and has become an important candidate for achieving ultra-high data rates.However,the mm Wave frequency band exhibits large path loss and penetration loss,and its communication link is easily obstructed by large vehicles,pedestrians,and buildings,which makes it difficult to maintain a stable and reliable communication link.Therefore,by combining the sub-6GHz frequency band with the mm Wave frequency band,the reliability of the sub-6GHz frequency band and the high transmission rate of the mm Wave frequency band can complement each other,providing sufficient and reliable communication.This thesis investigates resource allocation schemes that combine the sub-6GHz and mm Wave frequency bands in typical V2V and V2I scenarios to achieve the future demand for high transmission rates and reliability in vehicular networks.Additionally,a mm Wave link availability identification scheme is proposed to address the issue of mmWave blockage.The main contributions of this thesis are as follows:Firstly,in the V2V communication scenario with centralized base station scheduling,a DFAC resource allocation algorithm is proposed that combines high transmission rates of mmWave frequency band with high reliability of sub-6GHz frequency band.we propose a millimeter-wave link availability identification scheme that combines vehicle location information and received signal power intensity,and establish an optimization problem to maximize the number of services that transmit successfully,under the constraints such as transmission rate and latency.To tackle this complex coupled NP-hard problem,decomposition optimization is carried out,and appropriate algorithms are selected for solving in different frequency bands.The simulation results show that compared to the baselines,the proposed DFAC algorithm has higher reliability and lower latency in the mmWave band,and the entire system has higher throughput.This verifies that joint spectrum allocation can further improve the performance of vehicular networks.Secondly,in V2I communication scenarios where base stations cannot achieve full coverage,a utility-based relay selection strategy is proposed to overcome the distance limitation of base stations on vehicles.In this strategy,vehicles register their request signals,locations,speeds and other information through sub-6GHz frequency band.The base station quantifies the relay capability of the vehicle,and uses the utility function to select the most suitable relay base station to forward the downlink data.Theoretical analysis was conducted in terms of two metrics,interruption probability and throughput.Simulation results show that the proposed scheme outperforms the two benchmark schemes in terms of reliability and system throughput. |
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