# A Novel QoS-Aware A-MPDU Aggregation Scheduler for Unsaturated IEEE802.11n/ac WLANs

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## Abstract

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## 1. Introduction

- The model is based on the aggregation level-dependent collision probability considering the gathering procedure.
- The average and variance of the access delay for transmissions using RTS/CTS mechanisms on error-prone channels are discussed and the effect on the queuing behaviors is given.
- A model for the end-to-end delay, gathering delay, queuing delay, and collisions is developed.
- An algorithm that can search for the optimal aggregation level more quickly by narrowing the candidate range of aggregation levels is proposed.

## 2. Background and Related Works

#### 2.1. The A-MPDU Aggregation and Black Acknowledgement

#### 2.2. The RTS/CTS Mechanism

#### 2.3. Related Works

## 3. Methods

#### 3.1. The End-to-End Delay

#### 3.2. The Access Delay

## 4. Algorithms

- (1)
- Those aggregation levels whose $pa$ is equal to 1 can be removed in advance. As the back-off procedure is executed in units of A-MPDU and the overhead of idle and conflicting slots is independent of the aggregation levels, the average service time per packet is shortened when the aggregation level increases. Consequently, $pa$ is in descending order according to Equation (20), and we can locate the smallest aggregation level whose $pa$ is less than 1 in advance through the binary search method.
- (2)
- According to Equation (2), the gathering delay ascends with the increase of the aggregation levels. Therefore, before the end-to-end delay is calculated, the gathering delay is compared with the best end-to-end delay at that point. If the gathering delay is greater than the currently best end-to-end delay, it is clear that the end-to-end delay containing the gathering delay is greater.
- (3)
- According to the model, ${\overrightarrow{\alpha}}_{s}\left(e\right)$ and ${\overrightarrow{\alpha}}_{\infty}\left(e\right)$ only depend on the PER and the candidate aggregation level which are limited values. Therefore, the derivation of these distributions is preferred to be implemented offline and the results are stored in a look-up table with all possible PER and L. When calculating the end-to-end delay, the algorithm can fetch the distributions from the table by indexing with given PER and L.

Algorithm 1. Searching for the optimal aggregation level. |

Require:$\lambda $ { The packet arrival rate.} |

Require: Bit error rates (BERs) in all stations{The BERs in the channel can be estimated using the signal to noise ratio (SNR).} |

Require: N{The number of active stations in the wireless local area network (WLAN).} |

Ensure:${A}_{l}$ {The optimal aggregation level.} |

procedure LowerBoundSearch($\lambda ,BERs,n$) |

${L}_{min}\Leftarrow 1$; |

Calculate $pa$ with aggregation level $L={L}_{min}$, using Equation (20); |

if $pa==1$ then |

$left\Leftarrow 1$; |

${L}_{min}\Leftarrow 64$; |

Calculate $pa$ with aggregation level $L={L}_{min}$, using Equation (20); |

if $pa<1$ then |

$right\Leftarrow W$; |

while right - left > 1 do |

${L}_{min}\Leftarrow (left+right)/2$; |

Calculate $pa$ with aggregation level $L={L}_{min}$, using Equation (20); |

if $pa<1$ then |

$right\Leftarrow {L}_{min}$; |

else |

$left\Leftarrow {L}_{min}$; |

end if |

end while |

end if |

end if |

return${L}_{min}$ |

end procedure |

procedureOptimalAggregationLevelSearch(
$\lambda ,BERs,n,{L}_{min}$) |

$L\Leftarrow {L}_{min}$; |

$\gamma $ is calculated with aggregation level L, using Equation (23); |

while${\gamma}^{K}>Th{r}_{loss}\phantom{\rule{3.33333pt}{0ex}}and\phantom{\rule{3.33333pt}{0ex}}L\le W$do |

$\gamma $ is calculated with aggregation level L, using Equation (23); |

$L++$; |

end while |

${D}_{e2e,opt}$ is calculated with aggregation level L, using Equation (1); |

${A}_{l}\Leftarrow {L}_{min}$; |

Calculate ${D}_{gather}$ with new aggregation level L+1, using (2); |

while${D}_{gather}<{D}_{e2e,opt}\phantom{\rule{3.33333pt}{0ex}}and\phantom{\rule{3.33333pt}{0ex}}L\le W$ do |

$L++$; |

${D}_{e2e}$ is calculated with aggregation level L, using Equation (1); |

if ${D}_{e2e}<{D}_{e2e,opt}$ then |

${A}_{l}\Leftarrow L$; |

${D}_{e2e,opt}\Leftarrow {D}_{e2e}$; |

end if |

Calculate ${D}_{gather}$ with new aggregation level L+1, using Equation (2); |

end while |

return ${A}_{l}$ |

end procedure |

## 5. Performance Evaluation

#### 5.1. The Validation of the Proposed Model and Algorithm

#### 5.2. The Performance Evaluation of the Proposed Scheduler

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 1.**The aggregate media access control (MAC) protocol data unit (A-MPDU) aggregation mechanism.

**Figure 4.**An example of the access procedure under the error prone channels. RTS/CTS (request to send/clear to send).

**Figure 6.**The state diagram for the retransmission stage corresponding to the A-MPDU frame transmitted at time t.

**Figure 9.**The optimal aggregation levels and the candidate ranges under different conditions. (

**a**) The optimal aggregation levels and the candidate ranges under different data rates. (

**b**) The optimal aggregation levels and the candidate ranges under different numbers of stations. (

**c**) The optimal aggregation levels and the candidate ranges under different bit error rates (BERs).

**Figure 10.**The optimal end-to-end delay under different conditions. (

**a**) The optimal end-to-end delay under different data rates. (

**b**) The optimal end-to-end delay under different numbers of stations. (

**c**) The optimal end-to-end delay under different BERs.

Data Rate | Frame Rate | Average Frame Size |
---|---|---|

5 Mbps | 60 fps | 10,341 bytes |

Parameter | Value |
---|---|

W | 64 |

retry limit | 4 |

maximum back-off stage | 2 |

minimum contention window (CW) size | 8 |

$le{n}_{MACheader}$ | 78 bytes |

$le{n}_{payload}$ | 36 + 1472 bytes |

$\sigma \left(The\phantom{\rule{3.33333pt}{0ex}}slot\phantom{\rule{3.33333pt}{0ex}}time\right)$ | 9 $\mathsf{\mu}$s |

${T}_{DIFS}$ | 43 $\mathsf{\mu}$s |

${T}_{SIFS}$ | 16 $\mathsf{\mu}$s |

${T}_{BACK}$ | 32 $\mathsf{\mu}$s |

${T}_{BACKfail}$ | 76 $\mathsf{\mu}$s |

${T}_{PHYheader}$ | 48 $\mathsf{\mu}$s |

${T}_{RTS}$ | 42 $\mathsf{\mu}$s |

${T}_{CTS}$ | 44 $\mathsf{\mu}$s |

${T}_{CTSfail}$ | 76 $\mathsf{\mu}$s |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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**MDPI and ACS Style**

Lu, C.; Wu, B.; Ye, T.
A Novel QoS-Aware A-MPDU Aggregation Scheduler for Unsaturated IEEE802.11n/ac WLANs. *Electronics* **2020**, *9*, 1203.
https://doi.org/10.3390/electronics9081203

**AMA Style**

Lu C, Wu B, Ye T.
A Novel QoS-Aware A-MPDU Aggregation Scheduler for Unsaturated IEEE802.11n/ac WLANs. *Electronics*. 2020; 9(8):1203.
https://doi.org/10.3390/electronics9081203

**Chicago/Turabian Style**

Lu, Cong, Bin Wu, and Tianchun Ye.
2020. "A Novel QoS-Aware A-MPDU Aggregation Scheduler for Unsaturated IEEE802.11n/ac WLANs" *Electronics* 9, no. 8: 1203.
https://doi.org/10.3390/electronics9081203