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• W2971567219 abstract "Next-generation (5G) vehicular networks will support various network applications, leading to specific requirements and challenges for wireless access technologies. This trend has motivated the development of the long-term evolution-vehicle (LTE-V) network, a 5G cellular-based vehicular technology. Due to the limited bandwidth for vehicular communications, it is important to efficiently utilize slim spectrum resources in vehicular networks. In this paper, we introduce a cloud radio access network (C-RAN)-based vehicular network architecture, named C-VRAN, which facilitates efficient management and centralized processing of vehicular networks. Furthermore, we propose a discrete cosine transform (DCT)-based data compression scheme for C-VRAN to enhance the effective data rate of the fronthaul network. This scheme first uses DCT to perform time-frequency conversion of LTE-V I/Q data and then utilizes the Lloyd-Max algorithm to quantify data in the frequency domain before finally selecting an appropriate coding scheme to achieve better performance. Simulation results show that the proposed scheme can achieve 3 times compression ratio within 1% error vector amplitude distortion, and it also has strong independence and versatility, allowing it to be used as a standalone module for the current LTE-V system." @default.
• W2971567219 created "2019-09-12" @default.
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• W2971567219 date "2019-11-01" @default.
• W2971567219 modified "2023-09-23" @default.
• W2971567219 title "A Novel DCT-Based Compression Scheme for 5G Vehicular Networks" @default.
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• W2971567219 doi "https://doi.org/10.1109/tvt.2019.2939619" @default.
• W2971567219 hasPublicationYear "2019" @default.
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