Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 241100009-6.doi: 10.11896/jsjkx.241100009

• Network & Communication • Previous Articles     Next Articles

Redundancy Compression Strategy in Cooperative Perception Services Based on Value ofInformation

WANG Ruijia1, SHEN Zhen2, LI Junjie2, DING Lei1,2   

  1. 1 The 36 Research Laboratory of China Electronics Technology Group,Jiaxing,Zhejiang 314033,China
    2 School of Telecommunications Engineering,Xidian University,Xi’an 710071,China
  • Online:2025-11-15 Published:2025-11-10
  • Supported by:
    National Natural Science Foundation of China(62371381)

Abstract: Connected andAutonomous Vehicles(CAVs) leverage Vehicle-to-Everything(V2X) communication and 6G sensor data to enable Cooperative Perception Services(CPS).In road environments,multiple CAVs may simultaneously perceive and share information about the same object.This results in the exchange of significant amounts of irrelevant and redundant information within the V2X network,leading to additional communication overhead.To address this issue,a redundancy compression strategy based on the Value of Information(VoI) is proposed.Firstly,the value of perception information is quantified through mathematical methods.Then,when a CAV sends an upload request to the base station,the VoI is aggregated at the base station.Subsequently,CPS satisfaction is formulated as a maximization problem under the control of the base station,which is solved using a Simulated Annealing(SA) algorithm.This strategy enables the base station to optimally control the information uploaded by CAVs,maximizing the utility of cooperative perception and minimizing redundancy in the V2X network.Simulation results show that compared to existing strategies,the proposed approach effectively reduces target redundancy,achieving an average reduction in transmission delay by 22.3% and improving CPS quality by 21.6%.

Key words: CAV, 6G, Value of information, Redundancy compression strategy, Information fusion

CLC Number: 

  • TP391
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