Throughput analysis of IEEE 802.15.4 network under IEEE 802.11 network interference

Int. J. Electron. Commun. (AEÜ) 67 (2013) 686–689

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Throughput analysis of IEEE 802.15.4 network under IEEE 802.11 network interference Soo Young Shin ∗ School of Electronic Engineering in Kumoh National Institute of Technology, Gumi, Gyeongbuk 730-701, Republic of Korea

a r t i c l e

i n f o

Article history: Received 7 October 2011 Accepted 21 February 2013 Keywords: Throughput IEEE 802.15.4 IEEE 802.11 Collision Interference

a b s t r a c t This paper evaluates throughput of IEEE 802.15.4 network under the interference of a saturated IEEE 802.11 network using an analytic method. Packet losses due to both collisions among IEEE 802.15.4 and mutual interference between IEEE 802.15.4 and 802.11 are considered for throughput analysis. To include the interference from IEEE 802.11, we modified the state transition probabilities of IEEE 802.15.4 twostate Markov process model. Simulation results closely match the theoretical expressions confirming the effectiveness of the proposed model. © 2013 Elsevier GmbH. All rights reserved.

1. Introduction IEEE 802.15.4 is one of the widely used protocols based on CSMA/CA for wireless sensor network [1]. Typical wireless sensor network consists of a number of sensors spread across a geographical area. In CSMA/CA, collisions among IEEE 802.15.4 nodes greatly affects throughput of IEEE 802.15.4 network. In addition, IEEE 802.15.4 uses 2.4 GHz unlicensed industrial scientific and medical (ISM) band which is heavily used by IEEE 802.11 and it might experience from IEEE 802.11 network which also affects throughput of IEEE 802.15.4 network. Therefore, for the throughput analysis of IEEE 802.15.4 under interference of IEEE 802.11, not only collisions among IEEE 802.15.4 nodes but also IEEE 802.11 interference impact must be considered simultaneously. In this paper, throughput of IEEE 802.15.4 network under IEEE 802.11 network interference is analyzed. The analytic results are validated by using simulations. 2. Throughput analysis Slotted CSMA/CA mechanism of beacon enabled IEEE 802.15.4 works as follows. Three variables are maintained at each device for a channel access: NB, CW and BE. NB is the number of times that CSMA/CA backoffs while attempting the current transmission, and is reset to 0 for each new data transmission. CW is the

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contention window length, which is reset to 2 either for a new data transmission or when the channel is found to be busy. BE is the backoff exponent, related to the backoff periods a device should wait before attempting carrier sensing. When a device needs to transmit, it delays for a random number of backoff periods (up to 2BE − 1 periods) and then determines if the channel is clear. If the channel is busy, the MAC increases both NB and BE by one, and resets CW to 2. If NB is less than or equal to macMaxCSMABackoffs, the CSMA/CA delays for a random time again, otherwise it terminates with a failure. If the channel is assessed to be idle, it must ensure that the contention window is expired before starting transmission. For this, the MAC sublayer first decrements CW by one. If CW is not equal to 0, it must go to another channel sensing step. Otherwise, it starts transmission on the boundary of the next slot period [1]. In [2], Markov process model was used for modeling beacon enabled IEEE 802.15.4 CSMA/CA mechanism. To include packet loss effect by the interference of IEEE 802.11 network, Markov process model of saturated IEEE 802.15.4 network in [2] is modified shown as bold arrows in Fig. 1. Unlike the transitions from the state (− 1, L − 1) only described whether the transmitted packet experiences collision with the probability of pC (failure) or not with the probability of (1 − pC ) (successful) in [2], transitions of modified Markov model explain both the collision and the packet loss. Note that L is the packet transmission and ACK reception duration measured in slots. Therefore, the packet transmissions are successful with the probability of (1 − pC )(1 − pE ), i.e., no collisions among IEEE 802.15.4 nodes and no interference from IEEE 802.11, or failure with the

S.Y. Shin / Int. J. Electron. Commun. (AEÜ) 67 (2013) 686–689

p C +(1- pC) p E - 1,L- 1

failure

687

1 1

success

…

(1- p C)(1 - p E) 1/ W0

1/ W0 - 1,0 1

0,- 1

0,1

1

…

1−α 0,- 2

0,2

0,W0- 2

0,W0- 1

α 1/ W1

…

1/ W1

…

β

…

1− β

…

…

Fig. 1. Modified Markov chain model of IEEE 802.15.4 under IEEE 802.11 interference.

probability of pC + (1 − pC )pE , i.e., either collision or corruption by interference, where pE represents the packet loss probability by the interference of IEEE 802.11 network. In this paper, IEEE 802.15.4 nodes are assumed to be hidden from IEEE 802.11 nodes, and vice versa. If both standards are set to use the carrier sensing (CS) method such as preamble detection to determine the channel state, it can be assumed without loss of generality.1 We assume a network of a fixed number N of IEEE 802.15.4 end devices, and each device always has a packet available for transmission. b(i, j) represents the steady-state probabilities of the Markov chain as the same in [3], where i and j mean the backoff stage and the backoff counter, respectively. The stationary probability  that the device attempts its carrier channel assessment (CCA) for the first time within a slot is obtained. After the delay counter is decremented to zero, the values −1 and −2 correspond to the first CCA (CCA1) and second CCA (CCA2), respectively. Let ˛ be the probability of assessing channel busy during CCA1, and let ˇ be the probability of assessing it busy during CCA2, given that it was idle in CCA1. Next, when entering the transmission state, L slots should be counted. The backoff window Wi is initially W0 = 2aMinBE and doubled until Wi = Wmax = 2aMaxBE where i represents the transmission stage and (aMaxBE − aMinBE) ≤ i ≤ NB. From the modified Markov model and transition probabilities, three equations were obtained using the similar way in [2]. The probability that a node starts to transmit is expressed as





 =  (1 − ˛) 1 − ˇ ,

(1)

NB

where  = b . i=0 i,0 The probability ˇ that there is a transmission in the medium when the considered device does its second sense during CCA2, given that it was idle in CCA1 is expressed as



ˇ=



1−



1 N



1 + (1/1 − (1 − ) )



1 − (1 − )

N



=

2 (1 − 2p)



(1 − 2p) (Wmin + 1) + pW min 1 − (2p)m

,

(3)

which is a function of the conditional collision probability p = 1 − (1 − )(n−1) . Wmin is the minimum contention window size specified for the backoff operation in IEEE 802.11 and m is the maximum power used to set up the maximum contention window size (i.e., Wmax = 2m Wmin ). Let Ptr be the probability that there is at least one transmission in the considered 802.11 time slot, Ptr = 1 − (1 − )n . PS (n) and PC (n) are the probabilities that a packet transmission is successful or a collision, respectively: PS (n) =

n(1 − )n−1 , Ptr



PC (n) =

1 − (1 − )n − n(1 − )n−1 Ptr



(4) .

Fig. 2 shows an example of packet transmissions for multiple IEEE 802.11 nodes. At each time-slot boundary, all IEEE 802.11 nodes transmit data packets with probability . ta is denoted as the average access time from the viewpoint of channel, which is the time elapsed from the moment of the end of tDIFS or the ACK timeout to the moment when the new IEEE 802.11b data packet is transmitted. The average access time can be expressed as ta (n) = tslot (1 − )n /{1 − (1 − )n }, where tslot is the slot time of IEEE 802.11b, 20 ␮s. Then, the average inter frame time of the IEEE 802.11b packet, TW , can be expressed as TW (n) = PS (n) (LW + TA + ta (n)) + PC (n) (LW + TACKTimeOut + ta (n)) , (5)

.

(2)

Eqs. (1)–(3) represent a nonlinear system in the three unknowns , ˛ and ˇ, which can be solved using numerical techniques. On the other hand, the packet loss probability of IEEE 802.15.4 by the interference of IEEE 802.11b, pE , was already obtained in [4] as follows. IEEE 802.11b is assumed to be in a saturated condition. For a saturated IEEE 802.11b, this paper relies on the work of Bianchi [3], where IEEE 802.11b with a fixed number of nodes, denoted as

1

n, is assumed. Then, the probability  that a node transmits in a randomly chosen 802.11 time slot is

It is known that most 802.11b WLAN devices use only the CS method [5].

where n is the number of IEEE 802.11b nodes and TA = tSIFS + TACK,W + tDIFS . LW is the duration of IEEE 802.11b packet, 1303 ␮s for 1500 bytes. tSIFS , tLIFS , TACK,W , and TACKTimeOut are 10, 50,

Fig. 2. Packet transmission example for multiple IEEE 802.11b sources.

688

S.Y. Shin / Int. J. Electron. Commun. (AEÜ) 67 (2013) 686–689

304, and 334 ␮s, respectively. Denote NW as the number of IEEE 802.11b packets that collide with a 102 bytes long IEEE 802.15.4 packet, with the collision time for each IEEE 802.11b packet

 PE (n) =

TW (n)

OW =0

 1−

NW 





PS (n) 1 − pb0

li (OW )/b

i=1

+

n 



PC (k) 1 − pW b

li (OW )/b



dOW . TW (n)

k

k=2

expressed within {li } (i = 1, . . ., NW ). According to the time offset between IEEE 802.15.4 and a IEEE 802.11b, (i.e., OW ), the collision time for multiple IEEE 802.11b nodes can be obtained as

W TC,n =

signal and the noise powers, and the IEEE 802.11b interferer power, respectively. Q() is a Q-function. The processing gain of IEEE 802.15.4, i.e. PG, is 9 dB, and   0.85.

Denoting pW as the BER for k IEEE 802.11b nodes colliding at the b k

same time, the packet error rate can be obtained as Eq. (8) where b is a bit duration of IEEE 802.15.4 [4].

⎧ {LZ − (2TW (n) − OW )} + 2{LW }, for 0 ≤ OW ≤ TW (n) − LW and NW = 3, ⎪ ⎪ ⎪ ⎪ ⎨ {LZ − (2TW (n) + OW )} + 2{LW } + {TW (n) − LW } for TW (n) − LW < OW , OW ≤ LZ − 2TW (n), and NW = 4, ⎪ 2{LW } + {OW − (TW (n) − LW )}, ⎪ ⎪ ⎪ ⎩ NW

for LZ − TW (n) − LW < OW , OW ≤ TW (n), and NW = 3.

is the total collision time. l (OW ) = i=1 i (OW ) The bandwidth of IEEE 802.11b is 22 MHz, which is much larger than that of IEEE 802.15.4 (i.e., 2 MHz). Therefore, the signal of the interferer (i.e., IEEE 802.11b), can be modeled as a band-limited barrage noise or a band-limited additive white Guassian noise (AWGN) to the signal of IEEE 802.15.4. IEEE 802.15.4 employs offset quadrature phase-shift-keying (OQPSK) modulation with half-sine pulse shaping. Then, the SINR and BER of IEEE 802.15.4, interfered by multiple IEEE 802.11b nodes, can be determined by

SINRW,k = 10log10 =Q pW b



k

Pc PNo + kPIW

(6)

for LZ − 2TW (n) < OW , OW ≤ LZ − TW (n) − LW , and NW = 3,

{LZ − (TW (n) + OW )} + {LW } + {OW − (TW (n) − LW )},

W TC,n



+ PG, (7)



(8)

2SINRW,k ,

Now, using Eqs. (1)–(3) and pE , the throughput of IEEE 802.15.4 network, S, can be obtained as S=



LN(1 − )

N−1



 

(1 − ˛) 1 − ˇ A

· (1 − pE ) ,

(9)

where the first term represents the throughput of saturated IEEE 802.15.4 network and the second term the probability of successful packet transmission under the interference of IEEE 802.11. Here, A is the PHY data rate of IEEE 802.15.4, 250 kbps. 3. Numerical evaluation

where k denotes the number of IEEE 802.11b nodes that collide simultaneously, and Pc , PNo , and PIW denote the IEEE 802.15.4

Fig. 3 shows an example of coexisting IEEE 802.15.4 and IEEE 802.11 networks, which is used for the performance evaluation. In this paper, both IEEE 802.15.4 and 802.11 networks are assumed to be in saturated condition. IEEE 802.15.4 end devices are assumed to transmit data packets to IEEE 802.15.4 coordinator, which replies with ACK packets and IEEE 802.11 terminals are assumed to transmit packets to random destination. For analytic simplicity, IEEE 802.15.4 end devices and IEEE 802.11 nodes are located on concentric circles with radii of dZ and dW from IEEE 802.15.4 coordinator, respectively. 180 anal (No interference) anal (WLAN 1 node) anal (WLAN 5 nodes) anal (WLAN 10 nodes) anal (WLAN 20 nodes) anal (WLAN 30 nodes) sim (No interference) sim (WLAN 1 node) sim (WLAN 5 nodes) sim (WLAN 10 nodes) sim (WLAN 20 nodes) sim (WLAN 30 nodes)

160

Table 1 IEEE 802.15.4 parameters. Parameter

Definition

Value

LH

Header and trailer length of data packet Data length of data packet Turn-around time Length of ACK packet Maximum wait duration for ACK packet Unit slot time Minimum backoff exponent Maximum backoff exponent Maximum number of backoff trials

27 bytes

Ld tTA LACK tackwait U aMinBE aMaxBE NB

102 bytes 192 ␮s ≤ tTA ≤ 512 ␮s 11 bytes 864 ␮s 320 ␮s 3 or 5 5 5

Throughput of 802.15.4 [kbps]

140

Fig. 3. Coexistence example: IEEE 802.15.4 and IEEE 802.11 (TX power setting 802.11: 30 mW, 802.15.4: 1 mW).

120 100 80 60 40 20 0

5

10

15

20

25

30

35

40

# of 802.15.4 nodes

Fig. 4. Throughput of IEEE 802.15.4 network vs. number of IEEE 802.15.4 nodes (aMinBE = 3) with different number of IEEE 802.11 nodes when dW = 6 m.

S.Y. Shin / Int. J. Electron. Commun. (AEÜ) 67 (2013) 686–689

802.15.4 end devices. Also, as the number of IEEE 802.11 nodes increases, throughput of IEEE 802.15.4 decreases because of larger interference of IEEE 802.11. Fig. 6 illustrates throughput of IEEE 802.15.4 network with 15 (shown as normal) and 25 (shown as bold) end devices while varying the number of IEEE 802.11 nodes and dW . dW =∞ means there is no interference from IEEE 802.11. The number of IEEE 802.11 nodes varied from 1 to 30. As the dW decreases and the number of IEEE 802.11 nodes increases, throughput of IEEE 802.15.4 decreases abruptly because of low signal-to-interference plus noise ratio. However, if the dW is at 10 m, the throughput decrease is almost negligible (less than 3% in simulation) compared to that of non-interference case even when the number of IEEE 802.11 nodes is 30. Note that the throughput of IEEE 802.15.4 decreased when the number of IEEE 802.15.4 end devices increased from 15 to 25.

180

Throughput of 802.15.4 [kbps]

160

anal (No interference) anal (WLAN 1 node) anal (WLAN 5 nodes) anal (WLAN 10 nodes) anal (WLAN 20 nodes) anal (WLAN 30 nodes) sim (No interference) sim (WLAN 1 node) sim (WLAN 5 nodes) sim (WLAN 10 nodes) sim (WLAN 20 nodes) sim (WLAN 30 nodes)

140 120 100 80 60 40 20 0

5

10

15

20

25

30

35

689

40

4. Conclusions

# of 802.15.4 nodes Fig. 5. Throughput of IEEE 802.15.4 network vs. number of IEEE 802.15.4 nodes (aMinBE = 5) with different number of IEEE 802.11 nodes when dW = 6 m. 110

Throughput of 802.15.4 [kbps]

100

90

anal (d

= 10m)

anal (d

= 9m)

anal (d

= 8m)

anal (d

= 7m)

anal (d

= 6m)

sim (d

80

sim (d

= 9m)

sim (d

= 8m)

sim (d

= 7m)

sim (d

= 6m)

This paper has analyzed the throughput of IEEE 802.15.4 network under the interference of a saturated IEEE 802.11 network considering the packet losses by collisions among IEEE 802.15.4 nodes and interference from IEEE 802.11 network. Simulation results closely match the theoretical expressions confirming the effectiveness of the proposed model. The result of this paper can suggest the coexistence criteria and can be useful to design and implement a network using IEEE 802.15.4 and IEEE 802.11 at 2.4 GHz band. Acknowledgments

70

This research was financially supported by the Ministry of Education, Science Technology (MEST) and National Research Foundation of Korea (NRF) through the Human Resource Training Project for Regional Innovation (2012-03-A-01-015-12-010100).

60

50

References 40

30

5

10

15

20

25

30

# of interfering 802.11 nodes Fig. 6. Throughput of IEEE 802.15.4 network vs. number of IEEE 802.11 nodes with varying dW for 15 (normal) and 25 (bold) end devices of IEEE 802.15.4.

To evaluate the performance, we developed an OPNET simulation model for coexistence among IEEE 802.15.4 and IEEE 802.11 network as illustrated in Fig. 3. The indoor propagation model had a line-of-sight distance of 8 m, and the path loss exponent was 3.3. The other parameters are listed in Table 1. Therefore, L is [{LH + Ld + LACK }/A + tTA ]/U  =15 slots. The payload sizes of IEEE 802.11 was 1500 bytes long and CCK modulation at a rate of 11 Mbps was used for IEEE 802.11. Figs. 4 and 5 show the throughput of IEEE 802.15.4 network with varying the number of IEEE 802.15.4 nodes with aMinBE = 3 and 5 respectively. The number of IEEE 802.15.4 end devices varied from 1 to 40 and the number of IEEE 802.11 nodes varied from 0, 1, 5, 10, 20 and 30. Here, we set dZ = 1 m and dW = 6 m. As expected, when the number of IEEE 802.15.4 end devices increases, throughput of IEEE 802.15.4 decreases because of collisions among IEEE

[1] IEEE 802.15.4 workgroup, IEEE Std.802.15.4: IEEE standard for wireless medium access control (MAC) and physical layer (PHY) specifications for low-rate wireless personal area networks (LR-WPANs), 2006. [2] Pollin S, Ergen S, Bougard B, Perre LV, Moerman I, Bahai A, et al. Performance analysis of slotted carrier sense IEEE 802.15.4 medium access layer. IEEE Trans Wireless Commun 2008;7:3359–71. [3] Bianchi G. Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J Sel Areas Commun 2000;18:535–47. [4] Shin SY, Park HS, Kwon WH. Packet error rate analysis of IEEE 802.15.4 under saturated IEEE 802.11b network interference. IEICE Trans Commun 2007;10:2961–3. [5] Choi S, Prado JD. 802.11g CP: a solution for IEEE 802.11g and 802.11b interworking. Proc IEEE VTC’03 Spring 2003;1:690–4. Soo Young Shin was born in 1975. He received his B.S., M.S., and Ph. D degrees in Electrical Engineering and Computer Science from Seoul National University, Korea in 1999, 2001, and 2006, respectively. He was a visiting scholar in FUNLab at University of Washington, US, from July 2006 to June 2007. After 3 years working in WiMAX design lab. of Samsung Electronics, he is now assistant professor in School of Electronics in Kumoh National Institute of Technology since September 2010. His research interests include wireless LAN, WPAN, WBAN, wireless mesh network, sensor networks, coexistence among wireless networks, industrial and military network, cognitive radio networks, and next generation mobile wireless broadband networks.