TY - GEN
T1 - A Joint Optimization Method for Scheduling and Random Access Based on the Idea of Particle-Based Access in IEEE 802.11ax
AU - Sun, Ke
AU - Li, Bo
AU - Yan, Zhongjiang
AU - Yang, Mao
N1 - Publisher Copyright:
© 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Guarantee of delay
KW - IEEE 802.11ax
KW - Joint optimization of scheduling and random access
KW - Particle access
UR - http://www.scopus.com/inward/record.url?scp=85161360912&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-31275-5_18
DO - 10.1007/978-3-031-31275-5_18
M3 - 会议稿件
AN - SCOPUS:85161360912
SN - 9783031312748
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 172
EP - 185
BT - Smart Grid and Internet of Things - 6th EAI International Conference, SGIoT 2022, Proceedings
A2 - Deng, Der-Jiunn
A2 - Chao, Han-Chieh
A2 - Chen, Jyh-Cheng
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Smart Grid and Internet of Things, SGIoT 2022
Y2 - 19 November 2022 through 20 November 2022
ER -