# Acknowledgement Corruption: A New Aspect of Physical Layer Capture in IEEE 802.11 Networks

Authors: Jung-Han Han; Hyoung-Gyu Choi; Seung-Jae Han
Journal: Wireless Communications and Mobile Computing
 (2018)

---

## Abstract

Even if a collision occurs in IEEE 802.11 network, a transmission may be successfully decoded at the receiver if the signal strength of one transmission is sufficiently stronger than the other transmission. This phenomenon is called “Physical Layer Capture” (PLC). While existing works have considered PLC between data frames, in this paper we investigate the case that an ACK frame collides with the unfinished transmission of other data frames after the occurrence of PLC between data frames. As a result of this collision, the ACK frame may be corrupted and the corresponding data frame needs to be retransmitted. We call this phenomenon “ACK Corruption” (AC). We identify the characteristic of AC via extensive experiments and simulations. Our study reveals that AC can occur in all IEEE 802.11 variants and its chance is dependent upon the relative signal strength between the stations and the MCS setting used. Further, we devise a way to avoid AC occurrence and evaluate its effectiveness.


---

## Body

## 1. Introduction

When two or more transmissions collide on the same channel in IEEE 802.11 network, usually all the transmissions fail. However, if the signal strength of a transmission is sufficiently higher than other transmissions, that transmission succeeds while others fail. This phenomenon is calledPhysical Layer Capture(PLC).PLC in IEEE 802.11 has been extensively studied both analytically (e.g., [1–4]) and experimentally (e.g., [5–10]). In the existing studies, however, only the collision between data frames is considered.In this paper, a new aspect of PLC, which we callAcknowledgement Corruption (AC), is investigated. AC occurs when a 802.11 ACK frame collides with data frame(s). So far, such collision has been studied only in the context of the hidden node problem. For example, in [11], the loss of ACK due to the collision with the transmission by the hidden nodes in the adjacent cells is studied. Note that “carrier sensing” of 802.11 MAC does not work when the hidden node problem exists. In [12], the loss of ACK due to the hidden node problem is studied in multihop wireless networks. In [13], the loss of data frames by the interference from ACK transmission in adjacent cells due to the hidden node problem is studied. In [14], ACK loss caused by non-802.11 devices that do not employ carrier sensing is studied.In general, when there is no hidden node problem, ACK loss occurs very rarely since the 802.11 MAC guarantees exclusive transmission of ACK frame and ACK transmission is highly reliable as low-order MCS (Modulation Coding Scheme) is applied for ACK transmission, which guarantees robust transmission of ACK frame even at the presence of relatively severe noise.In this paper, unlike the existing works, we consider a single WiFi cell with no hidden node. The target scenario of this paper is as follows. Suppose that there occur simultaneous transmissions of two (or more) data frames in the same WiFi cell. If the signal strengths of these two transmissions are sufficiently different, one data frame with stronger signal strength will be successfully delivered to its receiver thanks to PLC despite the collision. When the transmission of the stronger data frame is completed, the receiver will generate an ACK frame. At this point, it is possible that the other data frame, which has weaker signal strength, is still under transmission. Note that, unlike Ethernet, ongoing transmissions are not interrupted even if a collision occurs in 802.11. Now, the ACK frame for the stronger transmission will collide with the residual transmission of data frame of the weaker signal strength. Depending on the relative signal strength of the ACK frame, the ACK frame may be corrupted as a result of the collision.The occurrence of AC is conditioned on PLC (i.e., AC may occur only after the occurrence of PLC) and AC occurs during a very short duration. To assess the properties of AC, we perform carefully designed experiments and simulations. In our experiments, each 802.11 node is monitored by using a dedicated sniffer to catch all the transmissions from each node even if collision occurs. The sniffers which are placed right next to each 802.11 node record all the transmission attempts regardless of the transmission result (i.e., success or failure). We perform comprehensive experiments by varying the location settings and transmission bit rates. For large scale evaluation, we rely on simulations.The results indicate that the chance of AC occurrences is dependent on many factors and is very high when certain conditions are met. We compare the properties of AC in 802.11a and 802.11n networks, which exhibit differences primarily due to the use of frame aggregation feature. Then we further investigate the properties of AC by focusing on how AC would affect the throughput of the 802.11 nodes. Based on the insight obtained from this investigation, we suggest an AC avoidance scheme to prevent (or reduce) AC occurrence and improve the overall throughput of the 802.11 network. Fairness among 802.11 nodes is also considered in this scheme.The rest of this paper is organized as follows. In Section2, we describe the necessary conditions for AC occurrence. In Section 3, we describe the experimental evaluation setting used in the paper and confirm the validity of the measurements. In Section 4, we present the results of 802.11a experiments. In Section 5, we present the results of 802.11n experiments, putting particular emphasis on the impact of frame aggregation on the occurrence of AC. In Section 6, we propose an AC avoidance scheme and evaluate its effectiveness. We conclude the paper in Section 7.


## 2. When Does “ACK Corruption (AC)” Occur?

In 802.11 MAC, ACK does not compete with regular data frames and therefore ACK does not normally collide with data frames. Barring the existence of the hidden node problem, the collision between ACK and a data frame occurs only after PLC between data frames occurs. AC occurs if the data frame is strong enough to corrupt ACK. The situation of AC occurrence in the 802.11 b/g/a networks is depicted in Figure1. In Figure 2, the AC occurrence in the 802.11 n/ac networks where frame aggregation is applied is depicted. Only the collision involving two transmissions is considered in Figures 1 and 2 for simplicity, though the collision among more than two nodes is also possible.Figure 1
ACK Corruption in IEEE 802.11 b/g/a networks.Figure 2
ACK Corruption in IEEE 802.11 n/ac networks.Suppose that two user stations are connected to an 802.11 AP. One station is positioned nearer to the AP than the other station. We call the station that locates near the AP as“Near node” and the station locates far from the AP as“Far node.” For AC occurrence, first of all, the data frame ofNear node must be successfully received despite the collision withFar node, which means PLC. As a result, ACK is generated by the AP towardNear node. Meanwhile, the transmission ofFar node fails and ACK will not be generated for it. Suppose that theFar node’s transmission lasts long enough, and this unfinished transmission collides with the ACK towardNear node. If theFar node’s transmission is strong enough as compared with the ACK, the ACK transmission will fail and the retransmission ofNear node will be triggered.Formally, there are three necessary conditions for the occurrence of AC. Firstly, PLC between data frames must occur and thus one of the data frames is successfully delivered to its receiver. Secondly, the other transmission should last long enough to cause collision with the ACK frame for the successful transmission. Thirdly, the signal strength of the failed data transmission should be strong enough to corrupt the ACK frame. If the signal strength of the ACK frame is sufficiently strong, another PLC that favors the ACK transmission will occur and ACK transmission will succeed (i.e., AC does not occur).Throughout the paper, we use the following notations to represent the SNR relationship between nodes.SNRA→B denotes the SNR (Signal-to-Noise Ratio) of the transmission by the A, when measured at B. For instance, SNRFar→AP denotes the SNR (Signal-to-Noise Ratio) of the transmission byFar node, when measured at the AP. (SNRA→C-SNRB→C) denotes the difference of SNR between A and B, which is measured at C. For instance, (SNRFar→Near-SNRAP→Near) denote the difference of SNR between AP andFar node, which are measured atNear node. Figure 3 illustrates some examples. In essence, if (SNRNear→AP-SNRFar→AP) is beyond a certain threshold, PLC occurs. If (SNRFar→Near-SNRAP→Near) is beyond a certain threshold, AC occurs.Figure 3
Examples of SNR relationship notations.
(a)
S
N
R
N
e
a
r
→
A
P
-
S
N
R
F
a
r
→
A
P
=
18 dB
(b)
S
N
R
F
a
r
→
N
e
a
r
-
S
N
R
A
P
→
N
e
a
r
=
-
5 dB


## 3. Experiment Setting

### 3.1. Experiment Testbed

We use Linux laptops equipped with an Atheros AR9380-based PCI-E card that supports 802.11 b/g/a/n to build the experiment testbed. Ath9k [15] is used for the device driver. Three laptops are used. One serves as the AP and the other two functions serve as user stations. Figure 4 shows the layout of the experiment testbed. The position of the AP is fixed, while two user stations are located in four possible positions. Position 1 is closest to AP and Position 4 is farthest from AP. For the notational convenience, we denote by “Positions i, j” the case thatNear node is at Position i andFar node is at Position j. By fixing the location ofFar node at Position 4, we experiment three configurations: “Positions 1, 4,” “Positions 2, 4,” “Positions 3, 4.” The SNR relationship of each case is shown in Figure 5 and Table 1.Table 1
SNR differences.
Near, Far node positions
Positions 1, 4
Positions 2, 4
Positions 3, 4
SNRNear→AP-SNRFar→AP
26 dB
18 dB
6 dB
SNRFar→Near-SNRAP→Near
−27 dB
−5 dB
14 dBFigure 4
Experiment Testbed Layout.Figure 5
SNR relationships for experiments.
(a)
Positions 1, 4
(b)
Positions 2, 4
(c)
Positions 3, 4Each laptop is equipped with an additional 802.11 interface card for the purpose of traffic sniffing. The sniffer interface catches all the transmissions and receptions at the PCI-E interface belonging to the corresponding laptop, and records the events in a log with timestamp. The resolution of the sniffer timestamp is one microsecond. Note that even when collision happens, the transmission of the collided packets can be detected by the sniffers associated with the sender stations (it is because PLC occurs at the sniffer interface of the sender station. Similar method has been used to catch collided packets as in [7]).All the sniffing traces collected at each laptop are merged together into a single traffic trace. We synchronize the timestamps of the sniffing traces from different nodes by utilizing the beacons transmitted by the AP. The main challenge is that the software timestamp is unreliable due to the fluctuation of software timestamping delay. As a result, the timestamps of different nodes are not precisely aligned. We get around this issue by increasing the MAC slot time. With the extended slot time, the time gap between data packets are also extended, so that it is possible to compensate the timestamp drift.We fix the contention window size to 1 by setting bothCWmin and CWmax to 1. As a result, only 0 or 1 slot is chosen for the random backoff value. This is solely to cause more collisions during the limited experiment duration. It does not affect the probability of PLC which is conditioned to the collision occurrence; that is, we only increase the chance of collision and the probability of PLC is unaffected. Iperf is used for traffic generation and the UDP packet size is set to 1536 bytes.All the experiments are conducted on the 5.180 GHz frequency (i.e., channel 36) to avoid interference from non--802.11 devices. We confirmed that ACK loss by noise error or other external interferences is negligible before starting the experiments. Auto rate adaptation is disabled and the transmission bit rate is fixed to a certain selected value in the experiments. For the 802.11a experiments, we use four transmission bit rates which are 54 Mbps, 48 Mbps, 24 Mbps, and 12 Mbps. For the 802.11n experiments, 12 transmission bit rates are used. The MCS indices used in the 802.11n experiments are summarized in Table2. Up to two spatial streams are used in the 802.11n experiments.Table 2
MCS index used in the 802.11n experiments.
MCS index
Number of spatial streams
Modulation & coding
Transmission bit rate (Mbps)
1
1
QPSK 1/2
13
2
1
QPSK 3/4
19.5
3
1
16-QAM 1/2
26
4
1
16-QAM 3/4
39
6
1
64-QAM 3/4
58.5
7
1
64-QAM 5/6
65
8
2
BPSK 1/2
13
9
2
QPSK 1/2
26
11
2
16-QAM 1/2
52
12
2
16-QAM 3/4
78
13
2
64-QAM 2/3
104
14
2
64-QAM 3/4
117


### 3.2. Detection of AC from Merged Traffic Trace

Table3 shows an example of the merged traffic trace, which is obtained from the 802.11a experiments of “Positions 3, 4” setting. The transmission bit rate ofNear node is set to 48 Mbps and that ofFar node is set to 24 Mbps. Such information as packet length, transmission bit rate, sequence number, and retry flag are extracted from the 802.11 MAC frame header. The packet number at the first column is assigned for the convenience of packet identification.Table 3
Example of merged traffic trace.
Packet number
Time (sec)
Sender
Receiver
Length (byte)
Sequence number
TX rate (Mbps)
Info
Retry flag
27986
62.227381
Near
AP
1536
437
48
Data
0
27987
62.227426
AP
Near
14
24
ACK
0
27988
62.232190
Near
AP
1536
438
48
Data
0
27989
62.232236
AP
Near
14
24
ACK
0
27990
62.232448
Far
AP
1536
3393
24
Data
0
27991
62.237000
Near
AP
1536
438
48
Data
1
27992
62.237045
AP
Near
14
24
ACK
0
27993
62.241809
Near
AP
1536
439
48
Data
0
27994
62.241854
AP
Near
14
24
ACK
0The transmission duration of a packet is computed by accounting PLCP preamble length, PHY header length, and MAC frame length. If the transmission duration of two packets overlap more than a half of any packet transmission, we infer that a collision occurs. In Table3, a collision occurs between Packet 27988 and Packet 27990 as their transmission durations overlap. Here, it can be observed that an ACK is generated by the AP for the Packet 27988, which indicates the occurrence of PLC between Packet 27988 and Packet 27990.Notice that the sequence number of Packet 27991 is the same as that of Packet 27988, which means that Packet 27991 is a retransmission. In other words, even if the AP sends an ACK toNear node for Packet 27988,Near node retransmits that packet. This happens because the ACK is corrupted due to the collision with the residual transmission of Packet 27990 which is send byFar node. We conclude that AC occurs in this case.The probability of PLC and the probability of AC are computed as follows:(1)The  probability  ofPLC⁡=the  number  of  PLC  occurrencesthe  number  of  data  frame  collisions,The  probability  ofAC⁡=the  number  of  AC  occurrencesthe  number  of  PLC  occurrences.


### 3.3. Validation of Experiment Setting

In this section, we examine the accuracy of our measurements. To this end, we compare the statistics extracted from the 802.11 device driver with the result obtained by analyzing the traffic trace. Specifically, we compare the number of nonretry data transmissions (i.e., the cases that the transmission does not suffer collision or channel error).We examine the accuracy for all the experiment settings used in the paper. For each type of link (i.e., 802.11a and 802.11n), three configurations of node positions are tested, that is, “Positions 1, 4,” “Positions 2, 4,” and “Positions 3, 4.” For each position configuration, various combinations of MCS settings are tested. The ACK frame is encoded by using 24 Mbps by default and is encoded in a lower MCS if the transmission bit rate of the data frame is lower than 24 Mbps.The comparison results are given in Tables4 and 5. The blank in the tables indicates that the corresponding MCS setting is infeasible due to too high channel loss rate and consequently is excluded from the experiments. Nearly 100% match is obtained in almost all cases, which confirms the accuracy of our experiment results.Table 4
Comparison of the merged traffic trace and system-provided statistics (802.11n).
MCS index
Positions 1, 4
Positions 2, 4
Positions 3, 4
Near
Far
Near
Far
Near
Far
Near
Far
802.11n (two spatial streams)
14
9
86.52%
99.87%
-
-
-
-
13
9
99.80%
99.88%
-
-
-
-
12
9
99.94%
99.90%
92.03%
99.76%
-
-
11
9
99.83%
99.83%
99.68%
99.78%
96.75%
92.97%
9
8
99.95%
99.81%
99.93%
99.76%
99.95%
99.13%
802.11n (one spatial stream)
7
3
99.64%
99.91%
-
-
-
-
6
3
99.89%
99.89%
99.83%
99.87%
-
-
4
2
99.98%
99.89%
99.96%
99.82%
99.94%
99.88%
3
1
99.91%
99.81%
99.94%
99.8%
99.92%
99.87%
3
3
99.95%
99.88%
99.96%
99.67%
99.87%
99.49%
1
3
99.92%
99.90%
99.93%
99.81%
99.91%
99.89%Table 5
Comparison of the merged traffic trace and system-provided statistics (802.11a).
Bit rate
Positions 1, 4
Positions 2, 4
Positions 3, 4
Near
Far
Near
Far
Near
Far
Near
Far
802.11a
54 Mbps
24 Mbps
99.83%
99.57%
99.66%
99.59%
-
-
48 Mbps
24 Mbps
99.84%
99.5%
99.72%
99.62%
99.41%
99.49%
24 Mbps
24 Mbps
99.84%
99.95%
99.88%
99.97%
99.73%
99.57%
12 Mbps
24 Mbps
99.63%
99.77%
99.9%
99.86%
99.34%
99.72%


## 3.1. Experiment Testbed

We use Linux laptops equipped with an Atheros AR9380-based PCI-E card that supports 802.11 b/g/a/n to build the experiment testbed. Ath9k [15] is used for the device driver. Three laptops are used. One serves as the AP and the other two functions serve as user stations. Figure 4 shows the layout of the experiment testbed. The position of the AP is fixed, while two user stations are located in four possible positions. Position 1 is closest to AP and Position 4 is farthest from AP. For the notational convenience, we denote by “Positions i, j” the case thatNear node is at Position i andFar node is at Position j. By fixing the location ofFar node at Position 4, we experiment three configurations: “Positions 1, 4,” “Positions 2, 4,” “Positions 3, 4.” The SNR relationship of each case is shown in Figure 5 and Table 1.Table 1
SNR differences.
Near, Far node positions
Positions 1, 4
Positions 2, 4
Positions 3, 4
SNRNear→AP-SNRFar→AP
26 dB
18 dB
6 dB
SNRFar→Near-SNRAP→Near
−27 dB
−5 dB
14 dBFigure 4
Experiment Testbed Layout.Figure 5
SNR relationships for experiments.
(a)
Positions 1, 4
(b)
Positions 2, 4
(c)
Positions 3, 4Each laptop is equipped with an additional 802.11 interface card for the purpose of traffic sniffing. The sniffer interface catches all the transmissions and receptions at the PCI-E interface belonging to the corresponding laptop, and records the events in a log with timestamp. The resolution of the sniffer timestamp is one microsecond. Note that even when collision happens, the transmission of the collided packets can be detected by the sniffers associated with the sender stations (it is because PLC occurs at the sniffer interface of the sender station. Similar method has been used to catch collided packets as in [7]).All the sniffing traces collected at each laptop are merged together into a single traffic trace. We synchronize the timestamps of the sniffing traces from different nodes by utilizing the beacons transmitted by the AP. The main challenge is that the software timestamp is unreliable due to the fluctuation of software timestamping delay. As a result, the timestamps of different nodes are not precisely aligned. We get around this issue by increasing the MAC slot time. With the extended slot time, the time gap between data packets are also extended, so that it is possible to compensate the timestamp drift.We fix the contention window size to 1 by setting bothCWmin and CWmax to 1. As a result, only 0 or 1 slot is chosen for the random backoff value. This is solely to cause more collisions during the limited experiment duration. It does not affect the probability of PLC which is conditioned to the collision occurrence; that is, we only increase the chance of collision and the probability of PLC is unaffected. Iperf is used for traffic generation and the UDP packet size is set to 1536 bytes.All the experiments are conducted on the 5.180 GHz frequency (i.e., channel 36) to avoid interference from non--802.11 devices. We confirmed that ACK loss by noise error or other external interferences is negligible before starting the experiments. Auto rate adaptation is disabled and the transmission bit rate is fixed to a certain selected value in the experiments. For the 802.11a experiments, we use four transmission bit rates which are 54 Mbps, 48 Mbps, 24 Mbps, and 12 Mbps. For the 802.11n experiments, 12 transmission bit rates are used. The MCS indices used in the 802.11n experiments are summarized in Table2. Up to two spatial streams are used in the 802.11n experiments.Table 2
MCS index used in the 802.11n experiments.
MCS index
Number of spatial streams
Modulation & coding
Transmission bit rate (Mbps)
1
1
QPSK 1/2
13
2
1
QPSK 3/4
19.5
3
1
16-QAM 1/2
26
4
1
16-QAM 3/4
39
6
1
64-QAM 3/4
58.5
7
1
64-QAM 5/6
65
8
2
BPSK 1/2
13
9
2
QPSK 1/2
26
11
2
16-QAM 1/2
52
12
2
16-QAM 3/4
78
13
2
64-QAM 2/3
104
14
2
64-QAM 3/4
117


## 3.2. Detection of AC from Merged Traffic Trace

Table3 shows an example of the merged traffic trace, which is obtained from the 802.11a experiments of “Positions 3, 4” setting. The transmission bit rate ofNear node is set to 48 Mbps and that ofFar node is set to 24 Mbps. Such information as packet length, transmission bit rate, sequence number, and retry flag are extracted from the 802.11 MAC frame header. The packet number at the first column is assigned for the convenience of packet identification.Table 3
Example of merged traffic trace.
Packet number
Time (sec)
Sender
Receiver
Length (byte)
Sequence number
TX rate (Mbps)
Info
Retry flag
27986
62.227381
Near
AP
1536
437
48
Data
0
27987
62.227426
AP
Near
14
24
ACK
0
27988
62.232190
Near
AP
1536
438
48
Data
0
27989
62.232236
AP
Near
14
24
ACK
0
27990
62.232448
Far
AP
1536
3393
24
Data
0
27991
62.237000
Near
AP
1536
438
48
Data
1
27992
62.237045
AP
Near
14
24
ACK
0
27993
62.241809
Near
AP
1536
439
48
Data
0
27994
62.241854
AP
Near
14
24
ACK
0The transmission duration of a packet is computed by accounting PLCP preamble length, PHY header length, and MAC frame length. If the transmission duration of two packets overlap more than a half of any packet transmission, we infer that a collision occurs. In Table3, a collision occurs between Packet 27988 and Packet 27990 as their transmission durations overlap. Here, it can be observed that an ACK is generated by the AP for the Packet 27988, which indicates the occurrence of PLC between Packet 27988 and Packet 27990.Notice that the sequence number of Packet 27991 is the same as that of Packet 27988, which means that Packet 27991 is a retransmission. In other words, even if the AP sends an ACK toNear node for Packet 27988,Near node retransmits that packet. This happens because the ACK is corrupted due to the collision with the residual transmission of Packet 27990 which is send byFar node. We conclude that AC occurs in this case.The probability of PLC and the probability of AC are computed as follows:(1)The  probability  ofPLC⁡=the  number  of  PLC  occurrencesthe  number  of  data  frame  collisions,The  probability  ofAC⁡=the  number  of  AC  occurrencesthe  number  of  PLC  occurrences.


## 3.3. Validation of Experiment Setting

In this section, we examine the accuracy of our measurements. To this end, we compare the statistics extracted from the 802.11 device driver with the result obtained by analyzing the traffic trace. Specifically, we compare the number of nonretry data transmissions (i.e., the cases that the transmission does not suffer collision or channel error).We examine the accuracy for all the experiment settings used in the paper. For each type of link (i.e., 802.11a and 802.11n), three configurations of node positions are tested, that is, “Positions 1, 4,” “Positions 2, 4,” and “Positions 3, 4.” For each position configuration, various combinations of MCS settings are tested. The ACK frame is encoded by using 24 Mbps by default and is encoded in a lower MCS if the transmission bit rate of the data frame is lower than 24 Mbps.The comparison results are given in Tables4 and 5. The blank in the tables indicates that the corresponding MCS setting is infeasible due to too high channel loss rate and consequently is excluded from the experiments. Nearly 100% match is obtained in almost all cases, which confirms the accuracy of our experiment results.Table 4
Comparison of the merged traffic trace and system-provided statistics (802.11n).
MCS index
Positions 1, 4
Positions 2, 4
Positions 3, 4
Near
Far
Near
Far
Near
Far
Near
Far
802.11n (two spatial streams)
14
9
86.52%
99.87%
-
-
-
-
13
9
99.80%
99.88%
-
-
-
-
12
9
99.94%
99.90%
92.03%
99.76%
-
-
11
9
99.83%
99.83%
99.68%
99.78%
96.75%
92.97%
9
8
99.95%
99.81%
99.93%
99.76%
99.95%
99.13%
802.11n (one spatial stream)
7
3
99.64%
99.91%
-
-
-
-
6
3
99.89%
99.89%
99.83%
99.87%
-
-
4
2
99.98%
99.89%
99.96%
99.82%
99.94%
99.88%
3
1
99.91%
99.81%
99.94%
99.8%
99.92%
99.87%
3
3
99.95%
99.88%
99.96%
99.67%
99.87%
99.49%
1
3
99.92%
99.90%
99.93%
99.81%
99.91%
99.89%Table 5
Comparison of the merged traffic trace and system-provided statistics (802.11a).
Bit rate
Positions 1, 4
Positions 2, 4
Positions 3, 4
Near
Far
Near
Far
Near
Far
Near
Far
802.11a
54 Mbps
24 Mbps
99.83%
99.57%
99.66%
99.59%
-
-
48 Mbps
24 Mbps
99.84%
99.5%
99.72%
99.62%
99.41%
99.49%
24 Mbps
24 Mbps
99.84%
99.95%
99.88%
99.97%
99.73%
99.57%
12 Mbps
24 Mbps
99.63%
99.77%
99.9%
99.86%
99.34%
99.72%


## 4. 802.11a Experiment Results

We conduct experiments under the settings listed in Table5. The probability of PLC and the probability of AC obtained from the experiments are plotted in Figures 6 and 7. Each setting is experimented three times and the average value obtained from the experiments is plotted in the results.Figure 6
The probability of PLC in 802.11a experiments.Figure 7
The probability of AC in 802.11a experiments.


### 4.1. The Probability of PLC

In the case of “Positions 1, 4,” the probability of PLC is nearly 100% regardless of the MCS setting used. It means that PLC almost always occurs when the transmissions ofNear node andFar node collide. It is because the SNR difference betweenFar node andNear node to the AP is high; that is, (SNRNear→AP-SNRFar→AP) is high.By contrast, in the case of “Positions 3, 4,” the probability of PLC in the first two settings in Figure6 is zero. PLC occurs only whenNear node uses low-order MCS, that is, the last two settings. It is because the SNR difference betweenFar node andNear node to the AP is relatively small (i.e., (SNRNear→AP-SNRFar→AP) is low) and the transmission ofNear node can survive only when more reliable MCS (i.e., low-order MCS) is used.In the case of “Positions 2, 4,” the MCS ofNear node is the key factor as in the case of “Positions 3, 4.” As more reliable MCS is used forNear node, the probability of PLC increases and the last two settings produce 100% PLC. As the transmission bit rate ofNear node decreases, the probability of PLC increases.Note that the MCS ofFar node does not affect the probability of PLC. Only the relative location ofFar node affects the probability of PLC.


### 4.2. The Probability of AC

Figure7 shows the probability of AC obtained in the 802.11a experiments. First of all, regardless of the node positions, AC never occurs in the last two MCS settings (i.e., the transmission bit rates of “24, 24 Mbps” and “12, 24 Mbps” forNear node andFar node, resp.). It is because the transmission duration ofNear node is equal or longer than that ofFar node, which means that the ACK transmission from the AP toNear node never overlaps with the transmission ofFar node. Recall that the packet size is set to be equal for bothNear node andFar node.Now let us consider only the first two MCS settings (i.e., the transmission bit rates of “54, 24 Mbps” and “48, 24 Mbps”). In the case of “Positions 3, 4,” the probability of AC is zero since the probability of PLC is zero for this case. Recall that AC may occur only after PLC occurs.In the case of “Positions 1, 4,” the probability of AC is about 15%. Since the transmission duration ofFar node is at least twice longer than that ofNear node, the ACK transmission always overlaps with the transmission ofFar node. In this case, however, the signal strength of ACK is strong enough to overpower the signal strength ofFar node in most cases, that is, SNRAP→Near>SNRFar→Near. As a result, the chance of AC is relatively low.IfSNRAP→Near<SNRFar→Near, the probability of AC will be much higher. Indeed, we observe the probability of AC being 100% in the case of “Positions 2, 4.”


## 4.1. The Probability of PLC

In the case of “Positions 1, 4,” the probability of PLC is nearly 100% regardless of the MCS setting used. It means that PLC almost always occurs when the transmissions ofNear node andFar node collide. It is because the SNR difference betweenFar node andNear node to the AP is high; that is, (SNRNear→AP-SNRFar→AP) is high.By contrast, in the case of “Positions 3, 4,” the probability of PLC in the first two settings in Figure6 is zero. PLC occurs only whenNear node uses low-order MCS, that is, the last two settings. It is because the SNR difference betweenFar node andNear node to the AP is relatively small (i.e., (SNRNear→AP-SNRFar→AP) is low) and the transmission ofNear node can survive only when more reliable MCS (i.e., low-order MCS) is used.In the case of “Positions 2, 4,” the MCS ofNear node is the key factor as in the case of “Positions 3, 4.” As more reliable MCS is used forNear node, the probability of PLC increases and the last two settings produce 100% PLC. As the transmission bit rate ofNear node decreases, the probability of PLC increases.Note that the MCS ofFar node does not affect the probability of PLC. Only the relative location ofFar node affects the probability of PLC.


## 4.2. The Probability of AC

Figure7 shows the probability of AC obtained in the 802.11a experiments. First of all, regardless of the node positions, AC never occurs in the last two MCS settings (i.e., the transmission bit rates of “24, 24 Mbps” and “12, 24 Mbps” forNear node andFar node, resp.). It is because the transmission duration ofNear node is equal or longer than that ofFar node, which means that the ACK transmission from the AP toNear node never overlaps with the transmission ofFar node. Recall that the packet size is set to be equal for bothNear node andFar node.Now let us consider only the first two MCS settings (i.e., the transmission bit rates of “54, 24 Mbps” and “48, 24 Mbps”). In the case of “Positions 3, 4,” the probability of AC is zero since the probability of PLC is zero for this case. Recall that AC may occur only after PLC occurs.In the case of “Positions 1, 4,” the probability of AC is about 15%. Since the transmission duration ofFar node is at least twice longer than that ofNear node, the ACK transmission always overlaps with the transmission ofFar node. In this case, however, the signal strength of ACK is strong enough to overpower the signal strength ofFar node in most cases, that is, SNRAP→Near>SNRFar→Near. As a result, the chance of AC is relatively low.IfSNRAP→Near<SNRFar→Near, the probability of AC will be much higher. Indeed, we observe the probability of AC being 100% in the case of “Positions 2, 4.”


## 5. 802.11n Experiment Results

### 5.1. The Probability of PLC

With respect to the probability of PLC, the 802.11n experiments produce very similar results to the 802.11a experiments. The results are plotted in Figure8. Firstly, when (SNRNear→AP-SNRFar→AP) is high in such cases as “Positions 1, 4,” the probability of PLC is nearly 100% regardless of the MCS setting used. When (SNRNear→AP-SNRFar→AP) is low, PLC rarely occurs unlessNear node uses very reliable MCS (i.e., low-order MCS) such as MCS 1 for single stream, and MCS 9 for two streams. Secondly, PLC occurs more often when more reliable MCS (i.e., low-order MCS) is used forNear node, the same as in the 802.11a experiments.Figure 8
The probability of PLC in 802.11n experiments.
(a)
2 spatial streams
(b)
1 spatial stream


### 5.2. The Probability of AC

Similar to the 802.11a experiments, AC rarely occurs in the case of “Positions 1, 4” and “Positions 3, 4.” Therefore, we only show the results of the “Positions 2, 4” experiment in Figure9. In this setting, SNRFar→Near is high enough to cause AC as compared to SNRAP→Near.Figure 9
The probability of AC in 802.11n experiments: Positions 2, 4.
(a)
2 spatial streams
(b)
1 spatial streamThe probability of AC in the 802.11n experiments is different from that of the 802.11a experiments in two aspects. Firstly, whenNear node uses a higher-order MCS thanFar node, the probability of AC is nearly 100% in the 802.11a experiments (see “Positions 2, 4” case in Figure 7). By contrast, the probability of AC is below 40% in the 802.11n experiments. Secondly, whenNear node uses a lower or equal order MCS thanFar node, the probability of AC is zero in the 802.11a experiments. In the 802.11n experiments, however, the probability of AC is 10~30%.These differences are caused by the frame aggregation of 802.11n. Unlike 802.11a, multiple frames are aggregated into a single frame in 802.11n as depicted in Figure10. As a result, the transmission duration ofNear node andFar node is not necessarily determined by the MCS used. Even if one node uses higher-order MCS than another node, the transmission duration may be longer if more frames are aggregated. Consequently, the transmission ofFar node may not overlap with the ACK frame forNear node, even ifNear node uses higher-order MCS thanFar node. On the flip side of the coin, the transmission ofFar node may overlap with the ACK frame forNear node, even ifNear node uses lower order MCS thanFar node.Figure 10
Frame aggregation and transmission duration.In Sections5.3 and 5.4, we assess the impact of frame aggregation on AC in detail.


### 5.3. The Degree of Frame Aggregation in Real Applications

In the 802.11n standard, the maximum transmission duration of an AMPDU (Aggregated MAC PDU) is declared to 10 milliseconds, though it is an implementation dependent value (i.e., 4 milliseconds in Ath9k device driver). In practice, however, most AMPDU frames have far shorted transmission durations. It is because the 802.11n interface does not forward the received frames to the upper layer until there is no hole in the “Block Acknowledgement (BA).” If there is any error in the MPDUs of the AMPDU, the lost MPDU must be retransmitted. As a result, MPDU frame aggregation is not fully utilized even if the sender has enough PDUs to transmit.To analyze the degree of frame aggregation that is achieved in the real world, we experimentally measure the transmission duration of AMPDU frames of three types of applications:Real time interactive game,File download, andLive streaming.Real time interactive game is a TCP-based online web game that constantly sends the player’s input to the server and receives the current status of the game from the server.File downloadis a TCP-based application that downloads a large file from a server.Live streaming is a UDP-based application that downloads a live video stream from a server. Experiments are conducted in a room and the user node is located 3 meters away from the AP.The measurement results are plotted in Figure11. It can be observed that most AMPDUs are far shorter than 4 milliseconds, while the degree of frame aggregation is highly dependent on the application used.File download produces much longer transmission durations thanReal time interactive game andLive streaming. We also measure the degree of frame aggregation in an uncontrolled environment, that is, in a public cafe. The measurement result is plotted in Figure 11, marked byPublic place.Figure 11
Distribution of transmission durations of AMPDU data frames from real traffic.


### 5.4. The Impact of Frame Aggregation on AC

We investigate the impact of frame aggregation on AC by intentionally limiting the degree of frame aggregation. To this end, the maximum transmission duration of an AMPDU is reduced to less than the default value of 4 milliseconds. Three configurations are tested: (i) “Near: 1 ms, Far: 4 ms” in which the maximum transmission duration ofNear node is reduced to 1 millisecond, (ii) “Near: 4 ms, Far: 1 ms” in which the maximum transmission duration ofFar node is reduced to 1 millisecond, and (iii) “Random (1~4 ms)” in which the maximum transmission duration is randomly chosen from 1 to 4 milliseconds for bothNear node andFar node.The results of “Positions 2, 4” experiment are plotted in Figure12. As expected, in general, the “Near: 1 ms, Far: 4 ms” experiments result in higher AC probability than the “Near: 4 ms, Far: 1 ms” experiments. It is because the chance that the transmission ofFar node lasts after the completion of the transmission ofNear node is higher in the former case than in the latter case, which leads to the collision between ACK and theFar node transmission. However, since the actual frame length may be shorter than 4 milliseconds even if the maximum transmission duration is set to 4 milliseconds, AC does occur in “Near: 4 ms, Far: 1 ms” experiments.Figure 12
AC probability when the maximum AMPDU transmission duration is varied (“Positions 2, 4” setting is used).
(a)
2 spatial streams
(b)
1 spatial streamLet us examine the transmission duration of each case in more detail. Figure13(a) shows the distribution of transmission duration ofFar node in the “Near: 1 ms, Far: 4 ms” experiment. It can be observed that a large portion of frames have the transmission duration of near 4 ms, while in most of the remaining cases the transmission duration is below 1 ms. The size of the portion of transmission duration near 4 ms is dependent on the MCS used byFar node. WhenFar node uses low-order MCS such as MCS 1 or MCS 8, the portion of 4 ms frames is about 90%, while it is only about 75% in case of MCS 3.Figure 13
Distribution of transmission durations of AMPDU frames (“Positions 2, 4” setting is used).
(a)
Far node in “Near: 1 ms, Far: 4 ms” experiment
(b)
Near node in “Near: 4 ms, Far: 1 ms” experimentThe portion of transmission duration below 1 ms is virtually zero in case of MCS 1 or MCS 8. The reason is as follows. As low-order MCS is used, the chance of transmission error decreases, and consequently the chance of creating short frames for retransmission decreases. As a result, the AC probability is nearly 100% whenFar node uses low-order MCS such as MCS 1 or MCS 8 in the “Near: 1 ms, Far: 4 ms” experiments (see Figure 12). Recall that MCS 8 is slower (i.e., more reliable) than MCS 3 as shown in Table 2.The interplay between MCS and transmission duration is observed also in the “Near: 4 ms, Far: 1 ms” experiment. Figure13(b) shows the distribution of transmission duration ofNear node in the “Near: 4 ms, Far: 1 ms” experiment. It can be observed that a large portion of transmissions byNear node has far shorter duration than 4 ms. Actually, a significant portion of transmissions have smaller than 1 ms duration when high-order MCS such as MCS 12 or MCS 6 is used forNear node. It is because the transmissions with high-order MCS tend to experience more errors and as a result short frames for retransmission are more frequently generated. For this reason, in Figure 12, we observed relatively high AC probability whenNear node uses high-order MCS even in the “Near: 4 ms, Far: 1 ms” experiment.


### 5.5. Multiple Far Nodes

Due to the difficulty of scaling up the testbed, we rely on simulation to examine the case that multipleFar nodesexist. To this end, we use a simulator which is custom-made for our purpose instead of public simulators (e.g., ns-2), since PLC is not properly simulated in those simulators [7]. In our simulator, we implement the PLC occurrences by applying the probability of PLC that is experimentally obtained in our testbed. That is, for given locations ofNear node andFar node and given MCS setting used, PLC is triggered at the probability measured in the experiment. For example, in case of “Positions 2, 4,” the PLC probability is set to 43.2% for “MCS 6, 3 setting.” The 802.11 MAC protocol is implemented by using typical parameters; for example, CWmin and CWmax are 15 and 1023, respectively. We verified the correctness of our simulator by comparing the collision probability and the throughput obtained from our simulator with the results of the analytical model presented in [16].We simulate up to 10 user nodes. One node (i.e.,Near node) is placed at Position 2 and the remaining nodes (i.e.,Far node) are placed at Position 4. When there is only oneFar node, it becomes the same as the “Positions 2, 4” experiment. The same MCS setting as in the “Positions 2, 4” experiment is used. The degree of MPDU frame aggregation is randomly chosen from the traffic trace ofPublic place shown in Figure 11.The experiment result indicates that the chance of AC in the “Positions 2, 4” setting is nearly 100% if theFar node transmission is long enough to collide the ACK frame forNear node. Based on this observation, we trigger AC occurrence if a collision occurs betweenFar node transmission and ACK frame in the simulation. The transmission error caused by noise is ignored in the simulation.Figure14 shows the probability of AC as the number ofFar nodesis increased from 1 to 9. In case of oneFar node, the probability of AC is around 41~42%, which is consistent with the results of “Positions 2, 4” experiment (see the case of “Random” in Figure 12). We conduct 100 times of simulation for each setting.Figure 14
AC probability for different number ofFar nodes (simulation result).As the number ofFar nodes increases, the probability of AC also increases. It is because as the number ofFar nodes increases, the number ofFar nodes involved in each collision increases as well. We plot the average number of nodes involved in a collision (includingFar node) in Figure 15. As the number ofFar nodes involved in a collision increases, the chance of havingFar node with long transmission duration increases.Figure 15
Average number of nodes involved in a collision (simulation result).


## 5.1. The Probability of PLC

With respect to the probability of PLC, the 802.11n experiments produce very similar results to the 802.11a experiments. The results are plotted in Figure8. Firstly, when (SNRNear→AP-SNRFar→AP) is high in such cases as “Positions 1, 4,” the probability of PLC is nearly 100% regardless of the MCS setting used. When (SNRNear→AP-SNRFar→AP) is low, PLC rarely occurs unlessNear node uses very reliable MCS (i.e., low-order MCS) such as MCS 1 for single stream, and MCS 9 for two streams. Secondly, PLC occurs more often when more reliable MCS (i.e., low-order MCS) is used forNear node, the same as in the 802.11a experiments.Figure 8
The probability of PLC in 802.11n experiments.
(a)
2 spatial streams
(b)
1 spatial stream


## 5.2. The Probability of AC

Similar to the 802.11a experiments, AC rarely occurs in the case of “Positions 1, 4” and “Positions 3, 4.” Therefore, we only show the results of the “Positions 2, 4” experiment in Figure9. In this setting, SNRFar→Near is high enough to cause AC as compared to SNRAP→Near.Figure 9
The probability of AC in 802.11n experiments: Positions 2, 4.
(a)
2 spatial streams
(b)
1 spatial streamThe probability of AC in the 802.11n experiments is different from that of the 802.11a experiments in two aspects. Firstly, whenNear node uses a higher-order MCS thanFar node, the probability of AC is nearly 100% in the 802.11a experiments (see “Positions 2, 4” case in Figure 7). By contrast, the probability of AC is below 40% in the 802.11n experiments. Secondly, whenNear node uses a lower or equal order MCS thanFar node, the probability of AC is zero in the 802.11a experiments. In the 802.11n experiments, however, the probability of AC is 10~30%.These differences are caused by the frame aggregation of 802.11n. Unlike 802.11a, multiple frames are aggregated into a single frame in 802.11n as depicted in Figure10. As a result, the transmission duration ofNear node andFar node is not necessarily determined by the MCS used. Even if one node uses higher-order MCS than another node, the transmission duration may be longer if more frames are aggregated. Consequently, the transmission ofFar node may not overlap with the ACK frame forNear node, even ifNear node uses higher-order MCS thanFar node. On the flip side of the coin, the transmission ofFar node may overlap with the ACK frame forNear node, even ifNear node uses lower order MCS thanFar node.Figure 10
Frame aggregation and transmission duration.In Sections5.3 and 5.4, we assess the impact of frame aggregation on AC in detail.


## 5.3. The Degree of Frame Aggregation in Real Applications

In the 802.11n standard, the maximum transmission duration of an AMPDU (Aggregated MAC PDU) is declared to 10 milliseconds, though it is an implementation dependent value (i.e., 4 milliseconds in Ath9k device driver). In practice, however, most AMPDU frames have far shorted transmission durations. It is because the 802.11n interface does not forward the received frames to the upper layer until there is no hole in the “Block Acknowledgement (BA).” If there is any error in the MPDUs of the AMPDU, the lost MPDU must be retransmitted. As a result, MPDU frame aggregation is not fully utilized even if the sender has enough PDUs to transmit.To analyze the degree of frame aggregation that is achieved in the real world, we experimentally measure the transmission duration of AMPDU frames of three types of applications:Real time interactive game,File download, andLive streaming.Real time interactive game is a TCP-based online web game that constantly sends the player’s input to the server and receives the current status of the game from the server.File downloadis a TCP-based application that downloads a large file from a server.Live streaming is a UDP-based application that downloads a live video stream from a server. Experiments are conducted in a room and the user node is located 3 meters away from the AP.The measurement results are plotted in Figure11. It can be observed that most AMPDUs are far shorter than 4 milliseconds, while the degree of frame aggregation is highly dependent on the application used.File download produces much longer transmission durations thanReal time interactive game andLive streaming. We also measure the degree of frame aggregation in an uncontrolled environment, that is, in a public cafe. The measurement result is plotted in Figure 11, marked byPublic place.Figure 11
Distribution of transmission durations of AMPDU data frames from real traffic.


## 5.4. The Impact of Frame Aggregation on AC

We investigate the impact of frame aggregation on AC by intentionally limiting the degree of frame aggregation. To this end, the maximum transmission duration of an AMPDU is reduced to less than the default value of 4 milliseconds. Three configurations are tested: (i) “Near: 1 ms, Far: 4 ms” in which the maximum transmission duration ofNear node is reduced to 1 millisecond, (ii) “Near: 4 ms, Far: 1 ms” in which the maximum transmission duration ofFar node is reduced to 1 millisecond, and (iii) “Random (1~4 ms)” in which the maximum transmission duration is randomly chosen from 1 to 4 milliseconds for bothNear node andFar node.The results of “Positions 2, 4” experiment are plotted in Figure12. As expected, in general, the “Near: 1 ms, Far: 4 ms” experiments result in higher AC probability than the “Near: 4 ms, Far: 1 ms” experiments. It is because the chance that the transmission ofFar node lasts after the completion of the transmission ofNear node is higher in the former case than in the latter case, which leads to the collision between ACK and theFar node transmission. However, since the actual frame length may be shorter than 4 milliseconds even if the maximum transmission duration is set to 4 milliseconds, AC does occur in “Near: 4 ms, Far: 1 ms” experiments.Figure 12
AC probability when the maximum AMPDU transmission duration is varied (“Positions 2, 4” setting is used).
(a)
2 spatial streams
(b)
1 spatial streamLet us examine the transmission duration of each case in more detail. Figure13(a) shows the distribution of transmission duration ofFar node in the “Near: 1 ms, Far: 4 ms” experiment. It can be observed that a large portion of frames have the transmission duration of near 4 ms, while in most of the remaining cases the transmission duration is below 1 ms. The size of the portion of transmission duration near 4 ms is dependent on the MCS used byFar node. WhenFar node uses low-order MCS such as MCS 1 or MCS 8, the portion of 4 ms frames is about 90%, while it is only about 75% in case of MCS 3.Figure 13
Distribution of transmission durations of AMPDU frames (“Positions 2, 4” setting is used).
(a)
Far node in “Near: 1 ms, Far: 4 ms” experiment
(b)
Near node in “Near: 4 ms, Far: 1 ms” experimentThe portion of transmission duration below 1 ms is virtually zero in case of MCS 1 or MCS 8. The reason is as follows. As low-order MCS is used, the chance of transmission error decreases, and consequently the chance of creating short frames for retransmission decreases. As a result, the AC probability is nearly 100% whenFar node uses low-order MCS such as MCS 1 or MCS 8 in the “Near: 1 ms, Far: 4 ms” experiments (see Figure 12). Recall that MCS 8 is slower (i.e., more reliable) than MCS 3 as shown in Table 2.The interplay between MCS and transmission duration is observed also in the “Near: 4 ms, Far: 1 ms” experiment. Figure13(b) shows the distribution of transmission duration ofNear node in the “Near: 4 ms, Far: 1 ms” experiment. It can be observed that a large portion of transmissions byNear node has far shorter duration than 4 ms. Actually, a significant portion of transmissions have smaller than 1 ms duration when high-order MCS such as MCS 12 or MCS 6 is used forNear node. It is because the transmissions with high-order MCS tend to experience more errors and as a result short frames for retransmission are more frequently generated. For this reason, in Figure 12, we observed relatively high AC probability whenNear node uses high-order MCS even in the “Near: 4 ms, Far: 1 ms” experiment.


## 5.5. Multiple Far Nodes

Due to the difficulty of scaling up the testbed, we rely on simulation to examine the case that multipleFar nodesexist. To this end, we use a simulator which is custom-made for our purpose instead of public simulators (e.g., ns-2), since PLC is not properly simulated in those simulators [7]. In our simulator, we implement the PLC occurrences by applying the probability of PLC that is experimentally obtained in our testbed. That is, for given locations ofNear node andFar node and given MCS setting used, PLC is triggered at the probability measured in the experiment. For example, in case of “Positions 2, 4,” the PLC probability is set to 43.2% for “MCS 6, 3 setting.” The 802.11 MAC protocol is implemented by using typical parameters; for example, CWmin and CWmax are 15 and 1023, respectively. We verified the correctness of our simulator by comparing the collision probability and the throughput obtained from our simulator with the results of the analytical model presented in [16].We simulate up to 10 user nodes. One node (i.e.,Near node) is placed at Position 2 and the remaining nodes (i.e.,Far node) are placed at Position 4. When there is only oneFar node, it becomes the same as the “Positions 2, 4” experiment. The same MCS setting as in the “Positions 2, 4” experiment is used. The degree of MPDU frame aggregation is randomly chosen from the traffic trace ofPublic place shown in Figure 11.The experiment result indicates that the chance of AC in the “Positions 2, 4” setting is nearly 100% if theFar node transmission is long enough to collide the ACK frame forNear node. Based on this observation, we trigger AC occurrence if a collision occurs betweenFar node transmission and ACK frame in the simulation. The transmission error caused by noise is ignored in the simulation.Figure14 shows the probability of AC as the number ofFar nodesis increased from 1 to 9. In case of oneFar node, the probability of AC is around 41~42%, which is consistent with the results of “Positions 2, 4” experiment (see the case of “Random” in Figure 12). We conduct 100 times of simulation for each setting.Figure 14
AC probability for different number ofFar nodes (simulation result).As the number ofFar nodes increases, the probability of AC also increases. It is because as the number ofFar nodes increases, the number ofFar nodes involved in each collision increases as well. We plot the average number of nodes involved in a collision (includingFar node) in Figure 15. As the number ofFar nodes involved in a collision increases, the chance of havingFar node with long transmission duration increases.Figure 15
Average number of nodes involved in a collision (simulation result).


## 6. AC Avoidance Scheme

### 6.1. Throughput Decrease

In preceding sections, we show that AC occurs with high probability under certain conditions. The immediate consequence of AC is the nullification of PLC so thatNear node with better channel condition has to perform retransmission which is not necessary if AC does not occur. Note that PLC has a side effect of increasing the user throughput. In [10], a scheme is proposed to deliberately cause PLC to mitigate the impact of packet collisions (i.e., decrease of the total system throughput). From the view point of the user throughput, AC leads to “throughput decrease.”We assess how AC affects the throughput ofNear node by comparing the results of AC-enabled simulation and AC-disabled simulation. In the real experiments, you cannot disable the occurrences of AC and therefore we rely on simulation for this analysis. In Figure 16, the simulation results are plotted as the number ofFar nodes is varied. All the simulations are conducted in the “Positions 2, 4” setting. That is,Near node is placed at Position 2 and all theFar nodes are placed at Position 4. “Throughput decrease” is computed by (“Throughput of AC-disabled simulation”-“Throughput of AC-enabled simulation”)/“Throughput ofAC-enabled simulation.”Figure 16
Throughput decrease of Near node due to AC.
(a)
802.11a
(b)
802.11nThe results of the 802.11a simulation are plotted in Figure16(a). In the 802.11a simulation, frame aggregation is not used and all the data packets are 1536 bytes long for bothNear node andFar node. Since the probability of PLC and the probability of AC in the “Positions 2, 4” setting are fairly high (See Figures 6 and 7), substantial throughput decrease is observed.The results of the 802.11n simulation are plotted in Figure16(b). In the 802.11n simulation, frame aggregation is used and the degree of MPDU frame aggregation is randomly chosen from the traffic trace ofPublic place. As compared to the results of the 802.11a simulation, the throughput decrease is smaller because of overall lower AC probability in the 802.11n networks. Notice that the throughput decrease of the case of “MCS 6, 3” is smaller than other cases. It is because the PLC probability of this case is particularly low (i.e., 43.2% as shown in Figure 8(b)).


### 6.2. AC Avoidance

We present a scheme to avoid (or reduce) AC occurrences. The key idea is to avoid the collision between theFar node transmission and the ACK transmission forNear node. To this end, there are two possible options: (i) extending theNear node transmission and (ii) shortening theFar node transmission. Suppose that all nodes have about the same amount of data to transmit. If we shorten the transmission duration ofFar node, the system efficiency will be greatly reduced asFar node uses short frames with low-order MCS. Therefore, the first option makes more sense and we take this approach.In the proposed scheme,Near node estimatesMinimum transmission duration which is long enough to avoid AC. To compute this value,Near node firstly identifies theFar nodes that can potentially create AC. Recall that AC occurs only if (SNRFar→Near and SNRAP→Near) is bigger than a certain threshold. By sniffing the ongoing transmissions,Near node obtains SNRFar→Near and SNRAP→Near. The threshold is obtained experimentally.Far nodes that meet this condition are included in the candidate set.Secondly,Near node checks if aFar node in the candidate set will produce PLC with theNear node. PLC occurs when (SNRNear→AP-SNRFar→AP) is beyond a certain threshold. Otherwise, theFar node is excluded from the candidate set. This threshold is obtained experimentally, and there exist many previous works on measuring the PLC threshold. By assuming that the downlink channel and the uplink channel are symmetric, these values are indirectly estimated by using SNRFar→Near and SNRAP→Near.Finally,Near node computes the expected transmission duration of theFar nodes in the candidate set. The history of past transmissions byFar nodes within a certain time window is used. We consider two ways, which are “Moving average” and “Moving maximum.” The former takes the average value in the time window, and the latter takes the maximum value in the time window. TheMinimum transmission duration ofNear node is decided so that the ACK transmission does not overlap with the expectedFar node transmission.Once a node computes itsMinimum transmission duration, it tries to make the data frame size larger than is value. It is done by adjusting MCS in 802.11a and by adjusting the degree of frame aggregation in 802.11n. The proposed AC avoidance scheme is described in Algorithm 1.Algorithm 1:AC avoidance algorithm.
n
n
e
a
r: The node executing AC avoidance algorithm
N
a
c: The set of the far nodes which can cause AC to nnear
N
a
l
l: The set of the nodes in the same WiFi cell as nnear
(1) nnear monitors the channel to obtain the RSSIs and transmission durations of all the nodes in Nall
(2) for each node i∈Nall do
(3) If (SNRi→nnear-SNRAP→nnear)> AC threshold then
(4)Nac←Nac∪i
(5)end if
(6) end for
(7) ifNac≠⌀ then
(8)for each node j∈Nac do
(9)if (SNRnnear→AP-SNRj→AP)< PLC threshold then
(10)Nac←Nac-j
(11)end if
(12)end for
(13) end if
(14) Minimum transmission duration← Moving avg. or moving max. of transmission durations of Nac
(15) Create data frame so that it is larger thanMinimum transmission duration


### 6.3. Throughput Analysis of AC Avoidance

The effectiveness of our AC avoidance scheme is evaluated via simulation using the same setting as in Section6.1. The result of 802.11a simulation (the case of “54 Mbps, 24 Mbps MCS setting”) is presented in Figures 17 and 18. “Moving average” and “Moving maximum” produce identical results. It is because the packet size is fixed to 1536 byte for all nodes in this simulation. After applying the AC avoidance scheme, AC virtually disappears, and the throughput ofNear node substantially increases.Figure 17
AC probability ofNear node for the case of 54 Mbps, 24 Mbps (802.11a).Figure 18
Throughput ofNear node in the case of 54 Mbps, 24 Mbps (802.11a).One noteworthy observation is that when the number ofFar nodes is one, the AC avoidance scheme rather decreases the throughput ofNear node. It is because the penalty (i.e., throughput decrease) by downshifting the MCS for AC avoidance is bigger than the penalty caused by AC.The result of 802.11n simulation (the case of “MCS 6, 3 setting”) is presented in Figures19 and 20. “Moving average” and “Moving maximum” produce different results because the degree of frame aggregation varies in the 802.11n simulation. As expected, “Moving maximum” eliminates the chance of AC while “Moving average” suffers occasional occurrences of AC. Unlike the 802.11a simulation, when the AC avoidance scheme is applied,Near node throughput is much higher than when it is disabled when the number ofFar nodes is small. It is because the overheads for transmissions (i.e., SIFS, ACK reception, and PHY header) are reduced thanks to the high degree of frame aggregation triggered by the AC avoidance scheme so that the length of the aggregated frame is larger thanMinimum transmission duration.Figure 19
AC probability ofNear node for the case of MCS 6, 3 (802.11n).Figure 20
Throughput ofNear node in the case of MCS 6, 3 (802.11n).


### 6.4. Fairness Analysis of AC Avoidance

As demonstrated in the previous section, our AC avoidance scheme increases the throughput ofNear node by reducing AC. On the other hand, however, AC avoidance may affect fairness betweenNear node andFar nodes. To examine this aspect, we compare the fairness among nodes before and after applying our AC avoidance scheme. The result is plotted in Figure 21.Figure 21
Time fairness in the case of MCS 6, 3 (802.11n).Jain’s Fairness Index is used as a fairness metric and we measure the fairness of transmission opportunity (i.e., time used for successful transmission) instead of resultant throughput, because throughput is determined by the MCS being used and consequently it is harder to interpret. We call our comparison metric as “time fairness.” Figure21 reveals that the fairness is substantially worsen as the number ofFar nodes increases after our AC avoidance scheme is applied, where fairness is relatively well maintained if AC avoidance is not applied. It is because PLC leads to transmission success forNear node, which does not increase its contention window size. Meanwhile PLC leads to transmission failure forFar nodes, which increases its contention window size.In short, AC negates the effect of PLC while AC avoidance tries to sustain the effect of PLC. There are existing studies that exploit PLC to enhance the network performance such as [10, 17]. While AC avoidance scheme can introduce unfairness, it is beneficial to be applied to those schemes. For the situations where fairness needs to be maintained, we extend our AC avoidance scheme to mitigate unfairness as follows.To reduce unfairness, the contention window size ofNear node is increased when the AC avoidance scheme is applied. We call this extension by “fairness compensation.” The effect of this extension is clearly shown in Figure 21. In the simulation, contention window is increased by the following equation:(2)CW=min⁡CW×Minimum  transmission  durationInitial  transmission  duration,CW×nNac+1.CW is the contention window size currently set at Near node.Initial transmission duration is the transmission duration ofNear node before applying the extension.Minimum transmission duration is the estimated transmission duration which is long enough to avoid AC. Nac is the set of the nodes which can cause AC toNear node, and n(Nac) is the number of these nodes. Different equations may be applied to make tradeoff between fairness and throughput. Figure 22 compares the aggregated throughput (i.e., the sum of the throughput of all nodes).Figure 22
Aggregated Throughput in the case of MCS 6, 3 (802.11n).Note that this is different from not using AC avoidance at all. It is because if AC avoidance is disabled, AC occurs and the successful transmission byNear node is wasted. With the fairness extension, AC is avoided and the successful transmission byNear node is saved, and unnecessary decrease of bit rate atNear node is prevented. Unnecessary decrease of bit rate due to collision is a well-known issue as studied in [18].


### 6.5. Discussion on Auto Rate Adaptation

In our experiments reported in preceding sections, we disable the auto rate adaptation and set the transmission bit rate to a fixed value. When AC occurs, theNear node’s ACK is lost, which theNear node will consider a transmission failure. If auto rate adaptation is enabled, the transmission bit rate of theNear node will be lowered for the subsequent retransmission, which will extend the transmission duration ofNear node. As a result of this action, the transmission duration ofNear node may become longer than that ofFar nodes, which breaks one of the necessary conditions for AC occurrence.To examine the influence of auto rate adaptation on AC, we conduct the same experiments that are reported in Figure9 by enabling auto rate adaptation for bothNear node andFar node. The result of this experiment is summarized in Table 6. When auto rate adaptation is enabled, the probability of AC decreases to some degree, but we still observe substantial AC occurrences.Table 6
The probability of AC when auto rate adaptation is used.
MCS index
Probability of AC
Near
Far
802.11n (two spatial streams)
12
9
43.31%
11
9
19.93%
9
8
35.25%
802.11n (one spatial stream)
6
3
29.31%
4
2
20.58%
3
1
36.67%
3
3
14.36%
1
3
8.23%
802.11n (auto)
Auto
Auto
9.52%There are a number of reasons why AC still occurs even when auto rate adaptation is enabled. First of all, the frame aggregation mechanism of 802.11n can result in a longer transmission of aNear node even if the transmission bit rate of theNear node is equal to (or even lower than) that of theFar node. We have already explained the reason in detail. Secondly, after the bit rate of aNear node is lowered as a result of AC, the retransmission of theNear node will still experience AC if the bit rate is not low enough and the frame length of theNear node is still shorter than that of the far user. Only if the bit rate reduction is sufficient to prevent AC, the probability of AC will drop. However, as a result of successful transmission, theNear node will increase its bit rate again and therefore AC may occur again at the subsequent transmissions.


## 6.1. Throughput Decrease

In preceding sections, we show that AC occurs with high probability under certain conditions. The immediate consequence of AC is the nullification of PLC so thatNear node with better channel condition has to perform retransmission which is not necessary if AC does not occur. Note that PLC has a side effect of increasing the user throughput. In [10], a scheme is proposed to deliberately cause PLC to mitigate the impact of packet collisions (i.e., decrease of the total system throughput). From the view point of the user throughput, AC leads to “throughput decrease.”We assess how AC affects the throughput ofNear node by comparing the results of AC-enabled simulation and AC-disabled simulation. In the real experiments, you cannot disable the occurrences of AC and therefore we rely on simulation for this analysis. In Figure 16, the simulation results are plotted as the number ofFar nodes is varied. All the simulations are conducted in the “Positions 2, 4” setting. That is,Near node is placed at Position 2 and all theFar nodes are placed at Position 4. “Throughput decrease” is computed by (“Throughput of AC-disabled simulation”-“Throughput of AC-enabled simulation”)/“Throughput ofAC-enabled simulation.”Figure 16
Throughput decrease of Near node due to AC.
(a)
802.11a
(b)
802.11nThe results of the 802.11a simulation are plotted in Figure16(a). In the 802.11a simulation, frame aggregation is not used and all the data packets are 1536 bytes long for bothNear node andFar node. Since the probability of PLC and the probability of AC in the “Positions 2, 4” setting are fairly high (See Figures 6 and 7), substantial throughput decrease is observed.The results of the 802.11n simulation are plotted in Figure16(b). In the 802.11n simulation, frame aggregation is used and the degree of MPDU frame aggregation is randomly chosen from the traffic trace ofPublic place. As compared to the results of the 802.11a simulation, the throughput decrease is smaller because of overall lower AC probability in the 802.11n networks. Notice that the throughput decrease of the case of “MCS 6, 3” is smaller than other cases. It is because the PLC probability of this case is particularly low (i.e., 43.2% as shown in Figure 8(b)).


## 6.2. AC Avoidance

We present a scheme to avoid (or reduce) AC occurrences. The key idea is to avoid the collision between theFar node transmission and the ACK transmission forNear node. To this end, there are two possible options: (i) extending theNear node transmission and (ii) shortening theFar node transmission. Suppose that all nodes have about the same amount of data to transmit. If we shorten the transmission duration ofFar node, the system efficiency will be greatly reduced asFar node uses short frames with low-order MCS. Therefore, the first option makes more sense and we take this approach.In the proposed scheme,Near node estimatesMinimum transmission duration which is long enough to avoid AC. To compute this value,Near node firstly identifies theFar nodes that can potentially create AC. Recall that AC occurs only if (SNRFar→Near and SNRAP→Near) is bigger than a certain threshold. By sniffing the ongoing transmissions,Near node obtains SNRFar→Near and SNRAP→Near. The threshold is obtained experimentally.Far nodes that meet this condition are included in the candidate set.Secondly,Near node checks if aFar node in the candidate set will produce PLC with theNear node. PLC occurs when (SNRNear→AP-SNRFar→AP) is beyond a certain threshold. Otherwise, theFar node is excluded from the candidate set. This threshold is obtained experimentally, and there exist many previous works on measuring the PLC threshold. By assuming that the downlink channel and the uplink channel are symmetric, these values are indirectly estimated by using SNRFar→Near and SNRAP→Near.Finally,Near node computes the expected transmission duration of theFar nodes in the candidate set. The history of past transmissions byFar nodes within a certain time window is used. We consider two ways, which are “Moving average” and “Moving maximum.” The former takes the average value in the time window, and the latter takes the maximum value in the time window. TheMinimum transmission duration ofNear node is decided so that the ACK transmission does not overlap with the expectedFar node transmission.Once a node computes itsMinimum transmission duration, it tries to make the data frame size larger than is value. It is done by adjusting MCS in 802.11a and by adjusting the degree of frame aggregation in 802.11n. The proposed AC avoidance scheme is described in Algorithm 1.Algorithm 1:AC avoidance algorithm.
n
n
e
a
r: The node executing AC avoidance algorithm
N
a
c: The set of the far nodes which can cause AC to nnear
N
a
l
l: The set of the nodes in the same WiFi cell as nnear
(1) nnear monitors the channel to obtain the RSSIs and transmission durations of all the nodes in Nall
(2) for each node i∈Nall do
(3) If (SNRi→nnear-SNRAP→nnear)> AC threshold then
(4)Nac←Nac∪i
(5)end if
(6) end for
(7) ifNac≠⌀ then
(8)for each node j∈Nac do
(9)if (SNRnnear→AP-SNRj→AP)< PLC threshold then
(10)Nac←Nac-j
(11)end if
(12)end for
(13) end if
(14) Minimum transmission duration← Moving avg. or moving max. of transmission durations of Nac
(15) Create data frame so that it is larger thanMinimum transmission duration


## 6.3. Throughput Analysis of AC Avoidance

The effectiveness of our AC avoidance scheme is evaluated via simulation using the same setting as in Section6.1. The result of 802.11a simulation (the case of “54 Mbps, 24 Mbps MCS setting”) is presented in Figures 17 and 18. “Moving average” and “Moving maximum” produce identical results. It is because the packet size is fixed to 1536 byte for all nodes in this simulation. After applying the AC avoidance scheme, AC virtually disappears, and the throughput ofNear node substantially increases.Figure 17
AC probability ofNear node for the case of 54 Mbps, 24 Mbps (802.11a).Figure 18
Throughput ofNear node in the case of 54 Mbps, 24 Mbps (802.11a).One noteworthy observation is that when the number ofFar nodes is one, the AC avoidance scheme rather decreases the throughput ofNear node. It is because the penalty (i.e., throughput decrease) by downshifting the MCS for AC avoidance is bigger than the penalty caused by AC.The result of 802.11n simulation (the case of “MCS 6, 3 setting”) is presented in Figures19 and 20. “Moving average” and “Moving maximum” produce different results because the degree of frame aggregation varies in the 802.11n simulation. As expected, “Moving maximum” eliminates the chance of AC while “Moving average” suffers occasional occurrences of AC. Unlike the 802.11a simulation, when the AC avoidance scheme is applied,Near node throughput is much higher than when it is disabled when the number ofFar nodes is small. It is because the overheads for transmissions (i.e., SIFS, ACK reception, and PHY header) are reduced thanks to the high degree of frame aggregation triggered by the AC avoidance scheme so that the length of the aggregated frame is larger thanMinimum transmission duration.Figure 19
AC probability ofNear node for the case of MCS 6, 3 (802.11n).Figure 20
Throughput ofNear node in the case of MCS 6, 3 (802.11n).


## 6.4. Fairness Analysis of AC Avoidance

As demonstrated in the previous section, our AC avoidance scheme increases the throughput ofNear node by reducing AC. On the other hand, however, AC avoidance may affect fairness betweenNear node andFar nodes. To examine this aspect, we compare the fairness among nodes before and after applying our AC avoidance scheme. The result is plotted in Figure 21.Figure 21
Time fairness in the case of MCS 6, 3 (802.11n).Jain’s Fairness Index is used as a fairness metric and we measure the fairness of transmission opportunity (i.e., time used for successful transmission) instead of resultant throughput, because throughput is determined by the MCS being used and consequently it is harder to interpret. We call our comparison metric as “time fairness.” Figure21 reveals that the fairness is substantially worsen as the number ofFar nodes increases after our AC avoidance scheme is applied, where fairness is relatively well maintained if AC avoidance is not applied. It is because PLC leads to transmission success forNear node, which does not increase its contention window size. Meanwhile PLC leads to transmission failure forFar nodes, which increases its contention window size.In short, AC negates the effect of PLC while AC avoidance tries to sustain the effect of PLC. There are existing studies that exploit PLC to enhance the network performance such as [10, 17]. While AC avoidance scheme can introduce unfairness, it is beneficial to be applied to those schemes. For the situations where fairness needs to be maintained, we extend our AC avoidance scheme to mitigate unfairness as follows.To reduce unfairness, the contention window size ofNear node is increased when the AC avoidance scheme is applied. We call this extension by “fairness compensation.” The effect of this extension is clearly shown in Figure 21. In the simulation, contention window is increased by the following equation:(2)CW=min⁡CW×Minimum  transmission  durationInitial  transmission  duration,CW×nNac+1.CW is the contention window size currently set at Near node.Initial transmission duration is the transmission duration ofNear node before applying the extension.Minimum transmission duration is the estimated transmission duration which is long enough to avoid AC. Nac is the set of the nodes which can cause AC toNear node, and n(Nac) is the number of these nodes. Different equations may be applied to make tradeoff between fairness and throughput. Figure 22 compares the aggregated throughput (i.e., the sum of the throughput of all nodes).Figure 22
Aggregated Throughput in the case of MCS 6, 3 (802.11n).Note that this is different from not using AC avoidance at all. It is because if AC avoidance is disabled, AC occurs and the successful transmission byNear node is wasted. With the fairness extension, AC is avoided and the successful transmission byNear node is saved, and unnecessary decrease of bit rate atNear node is prevented. Unnecessary decrease of bit rate due to collision is a well-known issue as studied in [18].


## 6.5. Discussion on Auto Rate Adaptation

In our experiments reported in preceding sections, we disable the auto rate adaptation and set the transmission bit rate to a fixed value. When AC occurs, theNear node’s ACK is lost, which theNear node will consider a transmission failure. If auto rate adaptation is enabled, the transmission bit rate of theNear node will be lowered for the subsequent retransmission, which will extend the transmission duration ofNear node. As a result of this action, the transmission duration ofNear node may become longer than that ofFar nodes, which breaks one of the necessary conditions for AC occurrence.To examine the influence of auto rate adaptation on AC, we conduct the same experiments that are reported in Figure9 by enabling auto rate adaptation for bothNear node andFar node. The result of this experiment is summarized in Table 6. When auto rate adaptation is enabled, the probability of AC decreases to some degree, but we still observe substantial AC occurrences.Table 6
The probability of AC when auto rate adaptation is used.
MCS index
Probability of AC
Near
Far
802.11n (two spatial streams)
12
9
43.31%
11
9
19.93%
9
8
35.25%
802.11n (one spatial stream)
6
3
29.31%
4
2
20.58%
3
1
36.67%
3
3
14.36%
1
3
8.23%
802.11n (auto)
Auto
Auto
9.52%There are a number of reasons why AC still occurs even when auto rate adaptation is enabled. First of all, the frame aggregation mechanism of 802.11n can result in a longer transmission of aNear node even if the transmission bit rate of theNear node is equal to (or even lower than) that of theFar node. We have already explained the reason in detail. Secondly, after the bit rate of aNear node is lowered as a result of AC, the retransmission of theNear node will still experience AC if the bit rate is not low enough and the frame length of theNear node is still shorter than that of the far user. Only if the bit rate reduction is sufficient to prevent AC, the probability of AC will drop. However, as a result of successful transmission, theNear node will increase its bit rate again and therefore AC may occur again at the subsequent transmissions.


## 7. Conclusion

In this paper, we investigate a phenomenon that we call “ACK Corruption,” by which an ACK frame is corrupted due to the collision with unfinished transmission of other data frames. Our study reveals that AC can occur in all IEEE 802.11 variants. It is shown that AC occurrence is dependent upon the relative signal strength between the stations and the MCS setting used. AC directly affects (i.e., degrades) the throughput of each station and the total system throughput. In certain circumstance, the probability of AC occurrences is very high. We proposed a practical solution to avoid the AC occurrences.



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*Source: 3096710-2018-02-15.xml*