Abstract
At present, there are some problems in the mechnism of guarantee for the delay of uplink service in IEEE 802.11, 1) Many studies have optimized the expectation of delay of random access, but cannot privide deterministic guarantee of delay. 2) Scheduling access can effiectively provides guarantee for the performance of the delay of service, but there are some very urgent packets that cannot tolerate the waiting time required by scheduling. 3) There are few studies that consider optimal the delay of both scheduling and random access. To solve these problems, this paper proposes a joint optimization method of scheduling and random access, based on the idea of minimum access bandwidth in the theory of particle access and the corresponding access strategy: EDF (Early Deadline First). As a result, the packets created by scheduling users are in the minimum access bandwidth range at each time, and the idle time-frequency resources are distributed as evenly as possible in time. Therefore, the probability of collision between random access users and the resulting long waiting time can be reduced. The simulation results show that under the condition of moderate total traffic, the joint optimization method proposed in this paper can significantly reduce the access delay of random users on the premise of ensuring the delay requirements of scheduling users. The research result of this paper provides a new idea for further optimizing the delay of the scheduling and random users.
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Acknowledgments
This work was supported in part by the National Natural Science Foundations of CHINA (Grant No. 61771390, No. 61771392 and No. 61871322), and Science and Technology on Avionics Integration Laboratory and the Aeronautical Science Foundation of China (Grant No. 201955053002 and No. 20185553035).
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Sun, K., Li, B., Yan, Z., Yang, M. (2023). A Joint Optimization Method for Scheduling and Random Access Based on the Idea of Particle-Based Access in IEEE 802.11ax. In: Deng, DJ., Chao, HC., Chen, JC. (eds) Smart Grid and Internet of Things. SGIoT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-031-31275-5_18
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