Propagation Delay Optimization by Game Theory for Autonomous Vehicles Networks
Autonomous vehicles (AVs) are the actual technology challenge of intelligent vehicles or robots. Many AVs or an AV team should connect between them and with a remote control station by wireless communication ensured by wireless networks. When considering AVs as users in wireless networks, they assum...
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Published in: | 2021 44th International Conference on Telecommunications and Signal Processing (TSP) pp. 403 - 407 |
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Main Authors: | , , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
26-07-2021
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Subjects: | |
Online Access: | Get full text |
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Summary: | Autonomous vehicles (AVs) are the actual technology challenge of intelligent vehicles or robots. Many AVs or an AV team should connect between them and with a remote control station by wireless communication ensured by wireless networks. When considering AVs as users in wireless networks, they assume the CSMA protocol to access the medium and avoid packet collisions by a monitoring mechanism based on sensing carriers. However, despite CSMA wireless networks, transmissions could suffer from collisions that disturb the network according to the number of active users. Here each user needs to gain the channel and accomplish its packet transmission in the shortest delay. Therefore, users are selfish, and each one tries all time to satisfy its utility without regarding the other users' utilities which could create many collisions and decrease the transmission throughput. In such situations, game theory is beneficial to manage users' behavior to acquire individual satisfaction and general network equilibrium. This paper presents a CSMA game model based on game theory to analyze and manage wireless networks composed of multiple autonomous vehicles (AVs), assuming CSMA Mac protocol and erasure coding (EC) to recover collided packets. At the network equilibrium, the collusion rate decreases and decreases, consequently the overall transmission delay. |
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DOI: | 10.1109/TSP52935.2021.9522601 |