# Evaluation of Rate Adaptation Algorithms in IEEE 802.11 Networks
## 2 Related Work
### Implicit Feedback
At the end of the sampling period, Minstrel-HT collects three data rate options: best throughput, second best throughput, and best probability. Subsequently, in the non-sampling period, MPDUs are sent using the best data rate until the maximum number of retransmissions is reached in the case of packet loss then the second best data rate is used. Similarly, if the second best data rate experiences packet loss, the best probability data rate is used. The evaluation in [13] showed that in some conditions Minstrel-HT fails to enhance throughput, especially in a non-fading channel when the quality of the channel changes back from bad to good. MiRA [16] is a rate adaptation that is used for Multiple-Input and Multiple-Output (MIMO) channels. It overcomes MPDU loss by applying a zigzag rate adaptation between intra-mode and inter-mode. MiRA first performs probing on the rate in MIMO intra-mode. In case goodput fails to be increased in intra-mode, MiRA zigzags to inter-mode MIMO, the probing mechanism only starts if significant changes occur in the measured moving average goodput of the current rate. The probing interval of MiRA is also adapted, which limits the probing number when goodput is low. MiRA also considers frame aggregation and Block Acknowledgement schemes when performing the best data rate probing. It also includes a collision aware mechanism where the sender detects collision if it satisfies the condition that the aggregate frame has experienced at least one retry and the loss ratio of its sub-frames is less than 10%. If collision exists, it triggers the adaptive RTS/CTS mechanism. The main drawback of MiRA is the introduction of an overhead when using the RTS/CTS mechanism. RAMAS [17] is a credit based approach. The data rates are grouped into two groups: modulation and enhancement groups. The modulation group consists of the different MCS values. The enhancement group consists of spatial stream, guard interval, and channel width. RAMAS uses credit-based algorithms, which relies on the packets success and failure statistics, to adapt these groups independently of each other and combines the results together in order to decide the overall feature setting. In each group, different rules are applied to increase or decrease the data rate sequentially. The main drawback of RAMAS is that it performs poorly, because its credit based scheme is conservative in adapting the number of streams and aggressive in adapting the MCS. This mismatch causes RAMAS to often operate at suboptimal settings with single stream and high MCS values leading to higher losses and reduced performance, as shown in the evaluations in [18]. [PERSON] [19] addresses 802.11 ax exploiting the Basic Service Set (BSS) Color Scheme. It increases the transmission opportunities by using adaptive Overlapping Basic Service Set/Preamble-Detection (OBSS/PD) thresholds which leads to a higher contention level inside a BSS and jointly adjusts the transmit power level. A statistical study is done during an interval of 100 ms and during a cycle of 1s were success and failure of packet transmissions are recorded and compared to the success and failure thresholds. It is then decided whether to increase or decrease either the rate, the OBSS/PD threshold, or the transmission power, depending on the statistical results collected. The main drawback of Damysus is relying on packet loss ratio thresholds. In [20] several experiments were done in order to verify that there is no single best Packet Loss Ratio (PLR) threshold that can help to achieve the maximum throughput.