Performance Analysis of IEEE 802.11e HCCA for V2I Communications in WAVE Networks

Minseok Kim and Jong-Moon Chung Communications & Networking Laboratory

School of Electrical & Electronic Engineering Yonsei University, Seoul, Republic of Korea

{msk84, jmc}@yonsei.ac.kr

Abstract—In this paper, a centralized polling-based medium access (MAC) scheme, namely, the IEEE 802.11e hybrid coordinator function (HCF) controlled channel access (HCCA), is considered as an alternative to the current MAC protocol used in IEEE 802.11p for Wireless Access in Vehicular Environment (WAVE). At first, the limitations of the current enhanced distributed channel access (EDCA) are examined, and then a simple analytical performance evaluation of HCCA is provided. The results demonstrate that the HCCA scheme can be an alternative option to EDCA and could serve as an efficient channel access mechanism for vehicular communications.

I. INTRODUCTION In recent years, intelligent transportation systems (ITSs)

have become a popular field for both commercial and academic research. The goals of ITS technologies are to support safety related applications, providing an efficient traffic management, as well as to deliver multimedia contents. Examples of such applications include cooperative collision warning, road condition warning, intelligent traffic congestion control, map downloading, electronic toll payment, and enhanced navigation to name a few.

In the perspective of communications and networking, vehicular ad hoc networks (VANETs) have emerged to consider the spontaneous and abrupt nature of vehicular environment. Due to the highly dynamic characteristics, ITS applications require high reliability while demanding relatively short access delay compared to the former mobile ad hoc networks (MANETs). Satisfying these requirements has been a main challenge in providing wireless access to vehicles. An exclusive spectrum at 5.9 GHz called dedicated short range communications (DSRC) was allocated by the U.S. Federal Communication Commission in 1999, in order to support vehicular communications. As shown in Fig. 1, DSRC spectrum is composed of seven 10 MHz channels (one control and six service channels), and each of them has its own usage [1]. In additions, the TGp of IEEE 802.11 and IEEE 1609 family has begun to define WAVE in 2004. The terminology WAVE indicates a protocol for communication setup used by IEEE 802.11 wireless LAN devices to operate in the DSRC

band. In other words, the purpose of WAVE is to provide vehicles a seamless and interoperable connectivity using widely deployed WLAN technologies. In WAVE, IEEE 802.11p defines amendments in PHY and MAC layers, while IEEE 1609 deals with the operations in higher layers.

The MAC layer of IEEE 802.11p introduces several changes and enhancements to the legacy IEEE 802.11 MAC. For instance, authentication and association procedures in communication group setup are removed to support dynamic vehicular nature and the stations are enabled to communicate without the aid of any basic service set (BSS) as in ad hoc networks. Furthermore, the channel access mechanism of IEEE 802.11p relies on the EDCA and HCCA of the IEEE 802.11e, while the mandatory scheme is the EDCA, and the HCCA operation is considered as an optional choice. The EDCA is generically a random access scheme based on carrier-sense multiple access with collision avoidance (CSMA/CA). Owing to its inherent random backoff characteristics, EDCA imposes some limitations when considering vehicle-to-infrastructure (V2I) communications. In contrast to the EDCA, HCCA is based on a polling mechanism controlled by the HCF. The HCF gathers the traffic requirements of the vehicles, and then schedules the duration and period of each vehicle’s access. By individually polling each vehicle, the HCF allocates appropriate transmission opportunities (TXOPs) to each vehicle. More details will be explained in the following sections.

The remainder of this paper is organized as follows. In section II, an overview of the IEEE 802.11e EDCA is provided and some of its limitations are described. Additionally, an introduction to HCCA is presented as an alternative. Then in section III, we present a simple mathematical analysis following the performance evaluation and a comparison between the EDCA and HCCA in section IV. Finally, section V concludes the paper.

Fig. 1. DSRC spectrum and channel allocation

This research was supported by the Information Technology Research Center (ITRC) program (NIPA-2010-C1090-1011-0006) supervised by the National IT Industry Promotion Agency (NIPA) of the Ministry of Knowledge Economy (MKE) of the Republic of Korea.

978-1-4244-7773-9/10/$26.00 ©2010 IEEE 328

II. OVERVIEW OF CHANNEL ACCESS IN WAVE

A. IEEE 802.11e EDCA As mentioned briefly in the previous section, EDCA

channel access is based on CSMA/CA, which is basically a random access scheme based on its random backoff mechanism. After a station senses the medium being idle for an arbitration inter-frame space (AIFS), it draws a random number out of its current contention window size and then actually accesses the channel when its backoff counter expires. A typical example of channel access mechanism of EDCA is presented in Fig. 2. Additionally, EDCA introduces four access categories (ACs) to support QoS requirements of different types of traffic. The ACs are AC_VO, AC_VI, AC_BE, and AC_BK which stand for voice, video, best effort, and background, respectively. By assigning different AIFS values and different backoff window sizes to different ACs, service differentiation can be achieved. The default values of these parameters are listed in TABLE I. Another important feature of EDCA is a TXOP. If a station obtains a right to access the medium, the duration of channel occupancy must not exceed the specified TXOP limit. Within a TXOP, a station can transmit multiple frames in a row. It is straight forward to understand that the TXOP is a powerful mean to manage the frame transmission delays [2].

B. Limitations of EDCA Due to its inherent characteristic of random access, EDCA

could have unpredictable delays. Moreover, unnecessary backoff procedure results in a waste of time and bandwidth. As the vehicular applications demand very short access latency, this may influence the overall performance, especially for time-critical safety applications. In additions, fairness between the users is out of scope and cannot be guaranteed in EDCA [3]. Finally, although EDCA introduces four ACs to support QoS requirements of different types of traffic, it can only provide minimum level of QoS.

C. IEEE 802.11e HCCA HCCA is an alternative and optional channel access

method in IEEE 802.11e and is a modified version of the point coordinator function (PCF) in the legacy IEEE 802.11. In HCCA [4], the HCF gathers a right to access the medium using PIFS which is shorter than the AIFSs of the stations. In this situation, the HCF obtains a complete authority over the channel, and polls each station based on their requests, starting a contention-free period (CFP). A station must be polled and assigned a HCCA TXOP by the controller before it transmits a frame. The main difference between HCCA and the legacy PCF is that the stations can be polled not only in the CFP, but also in the contention period (CP).

The service interval (SI) and the duration of allocated HCCA TXOP is scheduled by the HCF using the TSPEC information from the stations that requested a polled access. TSPEC describes the characteristics of the traffic, such as mean data rate, allowable delay bound, nominal MSDU size, etc. HCF aggregates the requirements and schedules the duration and periodicity of contention-free access. An efficient algorithm for a scheduler is an important issue in HCCA design, and more details can be found in [4-6].

Fig. 3 shows a typical example of HCCA channel access procedure. A contention-free, controlled access period (CAP) is repeated in every SI durations. Time-critical and real-time services can be well-supported using this method. By reflecting requirements of each traffic streams, HCCA can support differentiated services and guarantee QoS in many cases.

III. NUMERICAL ANALYSIS In this section, we develop an analytical performance

model for the IEEE 802.11e HCCA. For simplicity, we concentrate only on the CFP, and assume that the vehicles generate only one packet per each assigned TXOPs. This assumption can easily be generalized into multiple packets situations. The analysis presented below is similar to the one presented in [7], where the authors use the probability generating function (PGF) to compute the expected values. Suppose that there are N on-board units (OBUs) who requested contention-free access, so that there are N OBUs in the HCF’s polling list. The sequence of HCCA channel access can be represented as the one shown in Fig. 4.

Let PV be the steady-state probability that a particular OBU’s buffer is currently empty, and there are totally k OBUs trying to transmit frames to the roadside unit (RSU). Then, the distribution of k would be the binomial distribution as follows.

kNV

kVK PP

kN

kKPkP −−⎟⎟⎠

⎞⎜⎜⎝

⎛=== )1(}{)( (1)

The corresponding PGF of Eq. (1) would be,

{ }NVVK ZPPZG ⋅−+= )1()( (2)

TABLE I. DEFAULT EDCA PARAMETERS OF IEEE 802.11P

AC_VO AC_VI AC_BE AC_Bk AIFS [μs] 58 58 71 123 CWmin 3 7 15 15 CWmax 7 15 1023 1023 TXOPlimit [ms] 1.504 3.008 0 0

Fig. 2. Channel access mechanism in IEEE 802.11e EDCA

Fig. 3. Channel access mechanism in IEEE 802.11e HCCA

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When a polled OBU has no packets to transmit, the allocated TXOP expires after remaining idle for a PIFS [4]. Since we have assumed that among N OBUs, only k OBUs have frames to send, there would be N-x TXOP pre-expiration after PIFS (as in polled TXOPi in the Fig. 6). If we let l=N-k, then the distribution of N-k and the corresponding PGF is as follows.

kV

kNVL PP

kNN

lLPlP −−⎟⎟⎠

⎞⎜⎜⎝

⎛−

=== )1(}{)( (3)

{ }NVVL ZPPZG ⋅+−= )1()( (4)

Considering the sequence of flow illustrated in Fig. 4, the total length of the contention-free period in HCCA would just be the sum of all frame transmission times and the interframe spaces that are involved in the period and can be represented as in Eq. (5).

∑∑∑−

===

+++++++++=kN

jifsifs

k

ickifsiifs

N

iifsHCCA ESPASDSPSBT

111

)()( (5)

In (5), the terms B, ACK, P, E, and Di represent the transmission time of a beacon frame, acknowledgement frame, CF_POLL frame, CF_END frame, and the transmitted data frame of OBU i, respectively. Representing xi=Di+2Sifs+ ACK, the PGF of (5) can be expressed as

][][][)( )(11 ifsifs

kN

jifs

k

ii SPNESB

Px

HCCA ZEZEZEZT ++++⋅∑

⋅∑

=

−

== . (6)

The first and second term on the right side of (6) can be expressed as follows using (2) and (4), and from the fact that xi’s are independent and identically distributed with PGF X(Z).

NVV

xxxx

ZXPPZEZE k

k

ii

)}()1({)()( .....211 −+==∑ +++= (7)

NPVV

PPPP

ifskifsifsifs

kN

iifs

ZPPZEZE })1{()()( .....211 +−==

∑ +++

−

= (8)

As a consequence, the PGF of THCCA in (6) becomes as (9).

)}({})1{(

)}()1({)(ifsifsifs SPNESBNP

VV

NVVHCCA

ZZPP

ZXPPZT++++⋅+−⋅

−+= (9)

Then the average length of the contention-free period can be obtained by deriving the first moment of the PGF of (9). By

taking first derivative and setting Z to unity, and assuming that all of the data frames have identical length D, we obtain (10).

{ }ckifsV

ifsVifsifsHCCA

ASDPNPPSPNESBT

+⋅+⋅−+

⋅+++++=

2)1()(

(10)

The average length of CFP for HCCA with RTS/CTS mechanism can easily be obtained by extending (10) and can be represented as in (11).

{ }ckifsV

ifsVifsifsCTSRTS

ASDCRPNPPSPNESBT

+⋅+++⋅−+

⋅+++++=

4)1()(/ (11)

In Eq. (11), R and C represents the transmission time of RTS and CTS frames, respectively. Finally if we define the normalized system throughput or channel utilization efficiency as the ratio of the average time used for data frame transmission over the total average length of the contention-free period, it can be represented as (12).

HCCA

VHCCA T

DPNU ⋅−⋅= )1( (12)

IV. PERFORMANCE EVALUATION In this section we provide a performance evaluation using

the analytical model introduced in the previous section. The system parameters used in obtaining the numerical results are shown in TABLE II. To compare the performance of HCCA with the mandatory random access scheme, we adopted the results of Bianchi’s work in [9]. Fig. 5 shows the comparison of normalized saturation throughput. For PCF, we assumed that there is about a 20% delayed start of CFP across the TBTT [4], so the total length of CFP is reduced by that amount. It is clear that the polling-based HCCA have greater efficiency in terms of saturation throughput. As can be seen from the figure, the maximum achievable saturation throughput of HCCA converges to 0.9, while the random access scheme decreases as the number of stations increase. Higher channel utilization efficiency is an advantage of the controlled access scheme, but there is a trade-off that the controlled scheme requires more overhead due to the polling and management procedure. In addition, Fig. 6 shows the normalized throughput in terms of different packet payload sizes. The performance of HCCA with the RTS/CTS mechanism is lower than the basic access mode of HCCA, but

Fig. 4. Typical channel access procedure in HCCA

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when the packet size is greater than 1000 bits, the throughput of both cases converges to 1. Since the HCCA is basically a controlled access, it is clear that the probability of collision is very low (almost zero) within the same BSS. However, because the WAVE allows ad-hoc communication mode outside the context of any BSS, the RTS/CTS mechanism can be effective when considering minimization of collision probability from the OBUs outside of the current BSS, or between the OBUs of different BSSs.

In Fig. 6, the channel utilization efficiency of PCF, HCCA, and HCCA with the RTS/CTS mechanism is shown for fully saturated, moderately saturated, and non-saturated conditions, respectively. Fully saturated condition means that the transmission buffers of each vehicle are heavily queued, and there is always a frame to be sent at any time. Furthermore, Fig. 6 also shows the average length of the contention-free period required to support the number of OBUs represented in the horizontal axis. It can be seen from Fig. 6, in saturation condition, relatively high utilization can be achieved by using HCCA (converges to 0.9 as the number of OBUs increase). However, when the network traffic load is low, in terms of utilization performance, HCCA is not so effective. In these circumstances, the polling-based mechanism might be inefficient compared to the random access scheme. This is because the control and polling overhead becomes a burden to the overall system performance, and the need for controlled access is not so high. On the other hand, random access works fine since less control signals are sent over the channel.

V. CONCLUSION In this paper, we conducted an analytical model of the

polling-based controlled channel access scheme called the IEEE 802.11e HCCA. The results demonstrates that the polling-based mechanism results in higher utilization efficiency than the mandatory random backoff based mechanism at the expense of more overhead due to the scheduling and polling. Overall, the HCCA can be an

attractive alternative channel access method for time-critical and dynamic vehicular applications under heavy data traffic load conditions.

REFERENCES [1] J. Zhu and S. Roy, “MAC for Dedicated Short Range Communications

in Intelligent Transport System,” IEEE Commun. Mag., vol. 41, no. 12, 2003

[2] S. Mangold, S. Choi, G. R. Hiertz, O. Klein, and B. Walke, “Analysis of IEEE 802.11E for QoS Supprot in Wireless LANs,” IEEE Wireless Commun. Mag., vol. 10, no. 6, pp. 40-50. Dec. 2003.

[3] D. Pong, and T. Moors, “Fairness and Capacity Trade-off in IEEE 802.11 WLANs,” Proc. IEEE LCN’ 04, pp. 310-317, Tampa, Florida, Nov. 2004.

[4] A. Grillo, M. Macedo, and M. Nunes, “A Scheduling Algorithm for QoS Support in IEEE 802.11e Networks,” IEEE Wireless Commun., Mag., vol. 10, no. 3, pp. 36-43, June 2003.

[5] P. Ansel, Q. Ni, and T. Turletti, “FHCF: A simple and efficient scheduling scheme for IEEE 802.11e wireless LAN,” ACM/Kluwer J. Mobile Networks Applications (MONET), Special Issue Modeling Opt., vol. 11, no. 3, pp. 391-403, June 2006.

[6] Y. Higuchi, A. Foronda, C. Ohta, M. Yoshimoto, and Y. Okada, “Dealy Guarantee and Servie Interval Optimization for HCCA in IEEE 80211e WLANs,” IEEE WCNC, 2007.

[7] S. V. Krishnamurthy, A. S. Acampora, and M. Zorzi, “Polling-based Media Access Protocols for Use with Smart Adaptive Array Antennas,” IEEE/ACM Trans. on Networking, vol. 9, no. 2, April 2001.

[8] G. Bianchi, “Performance Analysis of the IEEE 802.11 DCF,” IEEE J. Select. Areas Commun., vol. 18, pp 535-547, Mar. 2000.

[9] D. Bertsekas and R. Gallager, Data Networks, 2nd Ed. New Jersey: Prentice Hall, 1992.

TABLE II. SYSTEM PARAMETERS

Data 8000 bits MAC Header 224 bits PHY Header 22 bits ACK 112+PHY header CF_Poll/END 160+PHY header Propagation Delay 1 us Slot Time 13 us SIFS 32 us Channel bit rate 3 Mbits/s

0 2 4 6 8 10 12 14 16 18 200.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Number of OBUs

No

rmal

ized

Sat

ura

tion

Th

rou

gh

pu

t

HCCABianchi W=32, m=3Bianchi W=128, m=3

100

101

102

103

104

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Packet Size [bits]

No

rmai

lized

Th

rou

gh

pu

t

PCFHCCAHCCA+RTS/CTS

(a) (b)

Fig. 5. (a) Normalized saturation throughput comparison between HCCA and Bianchi’s DCF model, (b) Normalized throughput of PCF, HCCA, and HCCA with RTS/CTS mechanism in terms of packet payload size.

0 2 4 6 8 10 12 14 16 18 200.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Number of OBUs

Util

izat

ion

Eff

icie

ncy

PCFHCCAHCCA+RTS/CTS

0 2 4 6 8 10 12 14 16 18 200

1

2

3

4

5

6

7

8x 10

4

Number of OBUs

Ave

rag

e C

FP

Len

gth

[ μs]

PCFHCCAHCCA+RTS/CTS

(a) (b)

0 2 4 6 8 10 12 14 16 18 200.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Number of OBUs

Util

izat

ion

Eff

icie

ncy

PCFHCCAHCCA+RTS/CTS

0 2 4 6 8 10 12 14 16 18 200

1

2

3

4

5

6

7

8x 10

4

Number of OBUs

Ave

rag

e C

FP

Len

gth

[ μs]

PCFHCCAHCCA+RTS/CTS

(c) (d)

0 2 4 6 8 10 12 14 16 18 200.25

0.3

0.35

0.4

0.45

0.5

0.55

Number of OBUs

Util

izat

ion

Eff

icie

ncy

PCFHCCAHCCA+RTS/CTS

0 2 4 6 8 10 12 14 16 18 200

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2x 10

4

Number of OBUs

Ave

rag

e C

FP

Len

gth

[ μs]

PCFHCCAHCCA+RTS/CTS

(e) (f)

Fig. 6. Utilization efficiency and average length of CFP for (a)-(b) fully saturated, (c)-(d) moderately saturated, and (e)-(f) non-saturated conditions, respectively.

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