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Title: Verification of ns-3 Wi-Fi Rate Adaptation Models on AWGN Channels
The performance of Wi-Fi networks depends on the ability of devices to adapt their transmissions to dynamic channel/network conditions. Hence, “Rate Adaptation Algorithms (RAAs)” have been devised to allow nodes to select appropriate modulation and coding schemes (and other parameters) in response to varying channel/network conditions. These algorithms are neither standardized nor typically divulged by vendors, and devising a ‘performance-optimal’ RAA for specific scenario remains an active topic that necessitates a complex, multi-parameter cross-layer (PHY/MAC) approach. The ns-3 network simulator offers detailed models of the Wi-Fi medium access control (MAC) layer, including three reference RAA implementations; however testing and validation of these RAA models has been very limited to date. This paper reports on initial test and validation for ns-3 RAA models via 802.11n/ac/ax simulations. After describing the RAA scope and implementations, we explore and summarize insights from test results as to a) whether the ns-3 RAAs are able to achieve the correct rates as configuration is varied and b) how they respond to step changes in the received signal-to-noise ratio (SNR) as a means for exploring their convergence properties.  more » « less
Award ID(s):
2016379
PAR ID:
10466274
Author(s) / Creator(s):
; ;
Editor(s):
Henderson, Thomas; Imputato, Pasquale; Liu, Yuchen; Gamess, Eric
Date Published:
Journal Name:
WNS3 '23: Proceedings of the 2023 Workshop on ns-3
Page Range / eLocation ID:
109 to 114
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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