Evaluation of the Minstrel rate adaptation algorithm in IEEE 802.11g WLANs

Abstract

Rate adaptation varies the transmission rate of a wireless sender to match the wireless channel conditions, in order to achieve the best possible performance. It is a key component of IEEE 802.11 wireless networks. Minstrel is a popular rate adaptation algorithm due to its efficiency and availability in commonly used wireless drivers. However, despite its popularity, little work has been done on evaluating the performance of Minstrel or comparing it to the performance of fixed rates. In this paper, we conduct an experimental study that compares the performance of Minstrel against fixed rates in an IEEE 802.11g testbed. The experiment results show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves from bad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality.I.

Cognitive wireless mesh network without common control channel evaluated in NS-3

“…This algorithm is called Minstreal [23]. Minstrel algorithm classifies transmission rates using integer numbers [0,1,2,3,4,5,6,7, 8,9].…”

Less-than-best-effort service for Community Wireless Networks: Challenges at three layers

“…This flexibility can enable robust frame transmission in the presence of a given SINR (Signal to Interference and Noise Ratio). Choosing the right PHY behavior is automatized using a so-called "Rate Adaptation (RA)" mechanism; common examples of such mechanisms include AMRR [4], SampleRate [5] and Minstrel [6] (these schemes are a part of the well-known madwifi RA suite). In unfavorable conditions, an RA algorithm typically picks a low rate [7] -but the frame transmission time increases at lower rates, thereby reducing the chances for other nodes to access the channel.…”

“…Since the LBE node is not under control in the assumed Community Wireless Network scenario, the upload behavior cannot be controlled, and hence it might seem unnecessary to try to construct a more suitable RA mechanism. However, when channel conditions are worse, RA mechanisms do choose a lower rate [6], and then the suggested improvement could be applied even on downloads. As for uploads, it could be a possibility to at least recommend that LBE users upgrade their system accordingly, and an AP could try to determine whether the upgrade is in place on the other side of the connection by tracking the rates that were chosen.…”

An Enhanced Minstrel Link Adaption Scheme for IEEE 802.11 WLANs

“…Minstrel has been proved to enjoy favorable effect in most slow-varying and low-density indoor channel condition. But when channel varies quickly or in high-density condition, in which random and unexpected collision is frequent, this algorithm has its limitation too, and even inferior to constant-rate algorithm [13,14]. And with the evolution of WLAN and increasing of MCS levels, periodical training itself would have influence on performance.…”