1. Performance Evaluation of
IEEE 802.11p for Vehicular
Communication Networks
A. Jafari, S. Al-Khayatt and A. Dogman
Faculty of Art, Computing, Engineering and Sciences,
Sheffield Hallam University, Sheffield, United Kingdom

2. Introduction
-Vehicles are definitely the most popular means of transportation
around the world
-Troubles and concerns have caused by increasing the number of
vehicles:
Growing the number of road accidents
Rising the cost in terms of victims and insured people
Increase in traffic congestion on the roads
Lack of parking space
Difficulty in predicting the speed of other vehicles and safety
distance
Wasting millions of hours and energy by vehicles every day

3. Introduction
-Current safety technology systems (e.g. airbag, seatbelts, ABS, EPS)
support drivers and passengers in critical condition to avoid or mitigate
accident; however, they cannot eradicate problems completely.
-Intelligent Transportation System (ITS) is one of the information and
communication technologies which enhances transportation
safety, reliability, security and productivity by integrating with
existing technologies.

4. Introduction
-Wireless data communication between vehicles is one of the
technologies which has improved the deployment of ITS
applications.
-This communication is divided into two types:
Vehicle to Vehicle (V2V): vehicles communicate directly with
neighbour vehicles
Vehicle to Infrastructure (V2I): two vehicles communicate indirectly by
third party medium (e.g. roadside equipment)
-Vehicles are equipped with short-range wireless communication
technology (approximately 100 to 300 meters)
-This is known as vehicular ad hoc network (VANET) technology.

5. Introduction
The major objectives of VANET:
Broadcast warning messages to neighbouring vehicles in case of
car accidents, obstacle, bad weather conditions , and emergency
braking on the road

6. Introduction
Obstacle on the road

7. Introduction
Emergency vehicle on the road

8. Introduction
Provide drivers with latest real-time traffic information
Help emergency vehicles to pass other vehicles quickly
Assist drivers to find accessible parking space
Supply automobile internet access
Receive online mechanic help when the car breaks down

9. Research Focus
-In 2004, IEEE 802.11 task group p developed an amendment to the
802.11 standard in order to enhance the 802.11 to support VANETs.
-This standard is known as 802.11p, it defines physical and medium
access control layers of VANETs.
-In addition, The IEEE 1609 working group defined IEEE 1609
protocol family which developed higher layer specification based on
802.11p.
-This protocol consists of four documents:
IEEE 1609.1: describes resource manager specification
IEEE 1609.2: defines the formats and processing of secure messages
IEEE 1609.3: covers network and transport layer services
IEEE 1609.4: specifies improvement to the IEEE 802.11p MAC to support
multichannel operation

10. Research Focus
-IEEE 1609 protocol family and 802.11p together are called WAVE
standard. . This system architecture is used for automotive wireless
communications .
-The contribution of this paper is to evaluate the IEEE 802.11p
standard.
-A study was based on the structure of the WAVE architecture for
VANETs.
-We, subsequently, set up one real scenario which assisted us in
analysing the performance metrics of the IEEE 802.11p. This
scenario was implemented and modelled using ns-2 network
simulator with VanetMobiSim traffic simulator .

11. Related Work
-One of the most important points in the vehicular network simulation
is that the nature of vehicular communication is based on the
movement. Therefore, it is necessary to implement a realistic
vehicular movement in the simulation.
-Several publications [1], [2], [3] have studied the performance of
802.11p. However, none of the previous studies have supported
realistic vehicular mobility simulation.
-In [4], the authors have presented a comprehensive evaluation and
review of the performance of 802.11p and WAVE protocols supporting
realistic vehicular mobility model. However, standards were
implemented in Qualnet network simulator.

12. Related Work
- In terms of modelling accuracy, a new model of IEEE 802.11 MAC
and PHY, which support IEEE 802.11P, is designed and implemented
in ns-2 network simulator version 2.34 [5]. This version of ns-2
network simulator is used in this paper.
- The main novelty of this paper is to implement the key parameters
of 802.11p standard in ns-2, and prepare the realistic vehicular
mobility model by VanetMobiSim

13. WAVE Architecture
WAVE Architecture

14. WAVE Architecture
A- Physical and MAC Layers
-The physical and MAC layers of WAVE are based on IEEE 802.11p
standard.
-The physical layer of IEEE 802.11p consists of seven channels in
5.9GHz band which uses 10MHZ bandwidth for each channel.
-The physical layer of 802.11p uses OFDM technology in order to
increase data transmission rate and overcome signal fading in wireless
communication.
-The management functions are connected to the physical and MAC
layers called physical layer management entity (PLME) and MAC layer
management entity (MLME), respectively.
-The IEEE 802.11p uses CSMA/CA to reduce collisions and provide fair
access to the channel.

15. WAVE Architecture
B- Multichannel Operation
-IEEE 1609.4 is one of the standards of the IEEE 1609 protocol
family, which manages channel coordination and supports MAC
service data unit delivery.
- This standard describes seven different channels with different
features and usages (six service channels and one control
channel). In addition, these channels use different frequencies and
transmit powers.
-Each station continuously alternates between the control channel
and one of the service channels.
-The control channel is used for system control and safety data
transmission.

16. WAVE Architecture
B- Multichannel Operation
- The IEEE 802.11p MAC layer is based on multichannel operation
of WAVE architecture and 802.11e EDCA.
-EDCA mechanism defines four different access categories (AC) for
each channel, and each of them has an independent queue.
- The EDCA mechanism provides prioritization by assigning different
contention parameters to each access category.
-AC3 has the highest priority to access medium, whereas AC0 has the
lowest priority.
-Each frame is categorized into different access categories, depending
on the importance of the message.

17. WAVE Architecture
B- Multichannel Operation
During data transmission, there are two contention procedures to
access the medium:
Internal contention procedure which occurs inside each channel
between their access categories by using the contention parameters
(AIFS and CW).
The contention procedure between channels to access the medium
supported by different timer settings based on the internal contention
procedure.

18. WAVE
Architecture
B- Multichannel
Operation
The contention
procedure inside each
channel and
the channel coordination

19. WAVE Architecture
C - Network and Transport Layers
-The IEEE 1609.3 defines the operation of services at network and
transport layers. Moreover, it provides wireless connectivity between
vehicles, and vehicles to roadside devices.
-The functions of the WAVE network services can be separated into
two sets:
Data-plane services: They transmit network traffics and support
IPV6 and WAVE short-message- Protocol (WSMP) protocols.
Management-plane services: Their functions are to configure and
maintain system, for instance: IPV6 configuration, channel usage
monitoring, and application registration. This service is known as
WAVE management entity (WME).

20. WAVE Architecture
D - Resource Manager
IEEE 1609.1 standard defines a WAVE application known as resource
manager (RM) which allows communication between applications
runs on Roadside units (RSU) and On-board units (OBU).
E - Security Services
- The IEEE 1609.2 standard defines security services for the WAVE
architecture and the applications which run through this architecture.
- This standard defines the format and the processing of secure
messages.

21. Simulation
Simulation in VANET consists of two components:
 Traffic simulation : generates a trace file which provides realistic
vehicles movement. This trace file is fed into the network simulator
which defines the realistic position of each vehicle during the network
simulation
Network simulation: The network simulator then implements the
VANET protocols and produces a trace file which prepares complete
information about the events taking place in the scenario. Information
is then analysed to evaluate the performance metrics of the IEEE
802.11p in VANET.

22. Simulation
- VanetMobiSim is selected as a traffic simulator for this paper. This
simulator supports Intelligent DriverModel with Intersection
Management (IDMIM) which generates realistic vehicular mobility
model .
-Vehicular safety communications based on IEEE 802.11p consist of
safety broadcast messages between neighbouring vehicles.
Consequently, the overall IEEE 802.11p performance is related to
broadcast messages reception performance.
-PBC agent is a broadcast message generator implemented in ns-2
version 2.34. We used this agent in order to define the broadcast
message generation behaviour in our simulation.

23. Simulation
-The scenario is a highway of 1500 metres long with three lanes in
one direction and nine vehicles moving in these three lanes.
-The maximum speeds of the lanes are around 80, 100 and 130 km/h
respectively. The speed limit for each lane is 60 km/h.
- The distance between each lane is 4 metres.
- In the scenario, an ambulance is in the emergency situation
travelling in the same direction as other vehicles at the speed of 150
km/h. The ambulance is located behind other cars which are 100
metres apart.
- The ambulance transmits one periodic broadcast message with a
payload of 250 bytes in every 0.2 seconds.

24. Simulation
- In order to evaluate the effect of different message sizes on the
performance metrics, we implemented another two scenarios in which
the ambulance transmits period broadcast messages with the payload
of 500, 1000 bytes respectively.
-Each network simulations run twenty times with the same mobility
trace to obtain an average and get a notion of statistical
significance.
- simulation run-time 65 seconds.

25. Results
170
160
150
140
130
120
Distance (m)
110
100
90
80
70
60
50
40
30
20
10
0
0 6 12 18 24 30 36 42 48 54 60
Vehicle 2
Simulation Time (s)
Vehicle 4
Vehicle 10
Distance between the ambulance and other vehicles during movement

26. Results
Packet loss (%)
Packet loss between vehicle 1 and 2
Packet loss between vehicle 1 and 4
Simulation Time (s)
Packet loss between vehicle 1 and 10
Packet loss between the ambulance and other vehicles during movement

27. Results
-There is no packet loss between the ambulance and vehicle 4 after
58 seconds of the simulation time, and the distance between the
ambulance and vehicle 4 is less than 138 metres after 58 seconds.
-Packet loss is dropped to 0% after 38 seconds of simulation, at the
same time the distance between ambulance and vehicle 10 is less
than 138 metres after 38 seconds.
-It provides similar results for vehicle 10 and 4. Accordingly, the
vehicles can receive the broadcast message when their distance
from the ambulance is less than 138 metres.

28. Results
6.4
5.9
5.4
4.9
Throughput (kbps)
4.4
3.9
3.4
2.9
2.4
1.9
1.4
0.9
0.4
-0.1
0 10 20 30 40 50 60
Simualtion Time (s)
Throughput of vehicle 2,4, and 10 (message size 250 bytes)

29. Results
-Throughput of vehicles 4 and 10 fluctuate between 1.8 and 2.2 Kbps,
when the distances between the vehicles and the ambulance are less
than 138 metres.
- All of the vehicles have nearly similar throughput when the
distances between vehicles and ambulance are less than 138 metres.
- The most important point is that each vehicle has different speed,
as a result the throughput and packet loss are not affected by the
varying speed.

30. Results
0.4665
0.46645
170
0.4664 160
150
End-to-End Delay (ms)
140
0.46635 130
120
Distance (m)
0.4663 110
100
0.46625 90
80
0.4662 70
60
0.46615 50
40
0.4661 30
20
10
0.46605 0
0.466 0 6 12 18 24 30 36 42 48 54 60
0 5 10 15 20 25 30 35 40 45 50 55 60 65 Vehicle 2
Simulation Time (s)
End-to-End Delay between vehicle 1 and 2
Simulation Time (s) Vehicle 4
End-to-End Delay between vehicle 1 and 4
Vehicle 10
End-to-End Delay Between vehicle 1 and 10
End-to-End delay between the Distance between the ambulance and
ambulance and other vehicles other vehicles during movement
(message size 250 bytes)

31. Results
-A comparison between two figures shows that as long as the
distance between vehicle and the ambulance is below 138 metres, the
results of both figures look similar.
-As the distance between sender and receiver increases, End-to-
End delay increases accordingly.
-It is observed that End-to-End delay is significantly influenced by the
distance between sender and receiver of the message.
- As mentioned earlier, vehicles have different speed;
consequently, various vehicle speeds do not have any impact on
End-to-End delay.

32. Results
180
1.8 160
Average Throughput (kbps)
Average Distance (m)
140
1.5
120
1.2 100
0.9 80
60
0.6
40
0.3 20
0
0
2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10
Vehicle Numbers Vehicle Numbers
Average throughput of Average distance between the
vehicles 100
ambulance and other vehicles
(message size 250 bytes) 90 (message size 250 bytes)
80
Package Loss (%)
70
60
Average
50
40
30
20
10
0
2 3 4 5 6 7 8 9 10
Vehicle Numbers
Average packet loss between the ambulance
and other vehicles (message size of 250 bytes)

33. Results
-The probability of message reception for vehicles 4, 7 and 10 is
less than other vehicles and they have the highest average packet
loss, since their average distance is more than other vehicles and at
the beginning of simulation their distance from the ambulance is
more than 138 metres.
- However other vehicles, which their distances do not exceed 138
metres from the ambulance during simulation time, have equal and
highest rate of average throughout without any packet loss.
-This is another reason indicating that throughput and packet loss
are not influenced by different vehicle speed.

34. Results
1.6
10
Average End-toEnd Delay (ms)
Average Throughput (kbps)
9 1.4
8 1.2
7
1
6
5 0.8
4 0.6
3
2 0.4
1 0.2
0
0
0 1 2 3 4 5 6 7 8 9 10
0 1 2 3 4 5 6 7 8 9 10
Message size 250 bytes
Vehicle Numbers Message size 250 bytes
Vehicle Numbers
Message size 500 bytes
Message size 500 bytes
Message size 1000 bytes
Message size 1000 bytes
Average throughput of vehicles with different Average End-to-End delay between the
message sizes ambulance and other vehicles with different
message size
- According to these figures the average throughput and End-to-End delay
are increased by increasing the message size, but the increment of
throughput of vehicles 4, 7, and 10 is not as high as other vehicles.

35. Conclusion
- Based on our findings, we have observed that the performance
metrics (throughput, End-to-End delay, and packet loss) are not
affected by varying vehicle speed.
-Analysis of throughput for the all vehicles showed that the
probability of successful message reception was same for all the
vehicles when the distance between sender and receiver of the
message was less than 138 metres.
- In addition, End-to-end delay metric was directly related to the
distance between the vehicle transmitting the broadcast messages
and its neighbouring vehicles.
-Results of scenarios with different message sizes demonstrated that
the average throughput and End-to-End delay metrics were
increased by increasing message sizes.

36. References
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standard,” in Proc. IEEE Vehicular Technology Conf., Baltimore, MD, US, Oct.
2007, pp. 2199-2203.
[2] T. Murray, M. Cojocari, H. Fu, “Measuring the performance of IEEE 802.11p using
ns-2 simulator for vehicular networks,” in: Proc. IEEE EIT, 2008, pp. 98–503.
[3] K. Bilstrup, E. Uhlemann, E. G. Ström and U. Bilstrup, “Evaluation of the IEEE
802.11p MAC method for vehicle-to-vehicle communication,” Proc. IEEE Int.
Symposium on Wireless Vehicular Communications, Calgary, Canada, Sept. 2008.
[4] S. Grafling, P. Mahonen, and J. Riihijarvi, “Performance evaluation of IEEE 1609
WAVE and IEEE 802.11p for vehicular communications,” in Proceedings of the 2nd
International Conference on Ubiquitous and Future Networks (ICUFN ’10), June
2010, pp. 344 –348.
[5] Q. Chen, F. Schmidt-Eisenlohr, D. Jiang, M. Torrent-Moreno, L. Delgrossi, and H.
Hartenstein, “Overhaul of IEEE 802.11 modeling and simulation in ns-2,” in Proc. 10th
ACM Symp. MSWiM, Chania, Greece, Oct. 2007, pp. 159–168.