Abstract
In this paper, we investigate the channel resource allocation problem in device-to-device (D2D) based VANETs. According to the vehicle density, we first mark the urban transportation scenario into intensive and sparse areas, in which we categorize the communication links as “altruistic” and “ego” links respectively in the consequence of marking results and vehicle attributes. Secondly, the altruistic links are further grouped in terms of an improved spectral clustering algorithm proposed hereby. Moreover, channel resources are dedicated to ego links and different clusters of altruistic links in order to alleviate communication interference and achieve better performance. We formulate an optimization problem of power control for channel resource allocation to maximize the total channel throughput. Fortunately, after reshaping the original problem into a D.C (difference of two convex functions) problem, which can be solved by interior point method, the optimal power allocation method is yielded. Intensive simulations are carried out across various configurations, and the results prove that our scheme has superior performance.
Supported by the Fundamental Research Funds for the Central Universities of China (NO. PA2021GDSK0095).
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Zhang, B., Ding, X., Zheng, H., Zheng, X., Xu, P. (2022). The Link Awareness Driven Resource Allocation Algorithm Based on Scenario Marking and Vehicle Clustering in VANETs. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13471. Springer, Cham. https://doi.org/10.1007/978-3-031-19208-1_17
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DOI: https://doi.org/10.1007/978-3-031-19208-1_17
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