Xuting Duan1,2, Yuanhao Zhao1,2, Kunxian Zheng1,2,*, Daxin Tian1,2, Jianshan Zhou1,2,3, Jian Gao4
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2127-2140, 2021, DOI:10.32604/cmc.2020.014484
- 26 November 2020
Abstract Dynamic channel assignment (DCA) is significant for extending vehicular ad hoc network (VANET) capacity and mitigating congestion. However, the un-known global state information and the lack of centralized control make channel assignment performances a challenging task in a distributed vehicular direct communication scenario. In our preliminary field test for communication under V2X scenario, we find that the existing DCA technology cannot fully meet the communication performance requirements of VANET. In order to improve the communication performance, we firstly demonstrate the feasibility and potential of reinforcement learning (RL) method in joint channel selection decision and access fallback More >
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