Modified Rate Control for Collision-Aware in Minstrel-HT Rate Adaptation Algorithm

Albar, Rizka; Arif, Teuku Yuliar; Munadi, Rizal

doi:10.1109/iceltics.2018.8548800

Cited by 3 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, rate adaptation algorithms have been widely studied and applied in the field of wireless communication. As shown in Table 1 , based on different dimensions, the most common classification methods are as follows: based on the sending end or based on the receiving end; and based on historical statistics or based on current measurements [ 11 ]. The above classification methods are not completely independent, and in practical applications, it is often necessary to cross the two or combine other classification methods to design appropriate rate adaptation algorithms.…”

Section: Related Workmentioning

confidence: 99%

Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks

Yu,

Wang,

Song

et al. 2023

Sensors

View full text Add to dashboard Cite

The IEEE 802.11 standard provides multi-rate support for different versions. As there is no specification on the dynamic strategy to adjust the rate, different rate adaptation algorithms are applied according to different manufacturers. Therefore, it is often hard to interpret the performance discrepancy of various devices. Moreover, the ever-changing channels always challenge the rate adaptation, especially in the scenario with scarce spectrum and low SNR. As a result, it is important to sense the radio environment cognitively and reduce the unnecessary oscillation of the transmission rate. In this paper, we propose an environment-aware robust (EAR) algorithm. This algorithm employs an occasional small packet, designs a rate scheme adaptive to the environment, and enhances the robustness. We verify the throughput of EAR using network simulator NS-3 in terms of station number, motion speed and node distance. We also compare the proposed algorithm with three benchmark methods: AARF, RBAR and CHARM. Simulation results demonstrate that EAR outperforms other algorithms in several wireless environments, greatly improving the system robustness and throughput.

show abstract

Section: Related Workmentioning

confidence: 99%