Performance of Wireless Ad Hoc Network with All the Data Rate of IEEE 802.11b Using NS-3

Sharma, Saurabh; Singh, Alok; Tripathi, Pramod Narayan

doi:10.1007/978-981-19-0312-0_42

Cited by 1 publication

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The threshold update is shown in Figure 1 below. Inferring the packet loss rate 𝑊 for the next window based on the recent performance of the packet loss rate, we obtain Equations ( 2) and (3).…”

Section: Threshold Updatementioning

confidence: 99%

“…Rate selection plays a pivotal role in the implementation of IEEE 802.11 standard. A well-designed rate adaptation algorithm can not only improve data transmission efficiency, but also balance the stability of data transmission [ 3 ]. On the contrary, using inappropriate rate adaptation algorithm can ultimately lead to poor internet experience and even inability to communicate properly.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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: Threshold Updatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%