Feb. 2017
15-17-0130-00-lpwa
Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)
Submission Title: [The Potentials of IEEE 802.15.4 CSMA/CA to operate in Dense Metering Networks with Hidden Nodes]
Date Submitted: [22 February, 2017]
Source: [Tallal Elshabrawy1, Ezzeldin Shereen1, Mohamed Ashour1, and Joerg Robert2] Company [1The German
University in Cairo, 2Friedrich-Alexander University Erlangen-Nuernberg]
Address1 [German University in Cairo - GUC, New Cairo City - Main Entrance of Al Tagamoa Al Khames, Egypt]
Address2 [Wolfsmantel 33, 91058 Erlangen, Germany]
Voice:[+202-27595525], FAX1: [+202 27581041], E-Mail:[[email protected]]
Abstract: [In this document, a simple analytical model to evaluate the report success probability as well as meters’
battery lifetime within IEEE 802.15.4-based metering networks is introduced. The model is utilized for proper
configuration of the IEEE 802.15.4 network given a target report success probability performance. It is shown that the
expected battery lifetime of meters could be optimized by controlling the percentage of hidden nodes combined with proper
setting of the maximum number of allowable backoff attempts by each meter.]
Purpose:
[Presentation within IEEE802.15 Interest Group LPWA]
Notice:
This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not
binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and
content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein.
Release:
The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be
made publicly available by P802.15.
Submission
Slide 1
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
The Potentials of IEEE 802.15.4
CSMA/CA to operate in Dense Metering
Networks with Hidden Nodes
Tallal Elshabrawy1, Ezzeldin Shereen1, Mohamed
Ashour1, and Joerg Robert2
1The German University in Cairo,
2Friedrich-Alexander University Erlangen-Nuernberg
Submission
Slide 2
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Motivation
• Dense Metering Networks
– Thousands of Meters
– Periodic Reports
– Inevitable Hidden Nodes
• Dimensioning and Parameter Configuration of
802.15.4 CSMA/CA-based Metering Networks
– Target Report Success Probability
– Maximize Battery Lifetime
Submission
Slide 3
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Metering Network Model
• Dense Meters Population
• Periodic Reporting
• CAP CSMA/CA
• Star Configuration between
Meters and Basestation
• Each Meter Mt has q% of
Hidden Nodes
• Collisions at Base station
Submission
Slide 4
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Model Parameters for Success Report Probability
Parameter Description
𝑁𝑀
Number of Meters in Network
Percentage of total meters that are hidden with respect
𝑞
to an IEEE 802.15.4 device of interest
IEEE 802.15.4 Packet Length for Metered Data in
𝐿𝑀
terms of Number of Timeslots
𝜆𝑅
Aggregate Meters Report Arrival Rate
𝜆𝑐𝑐𝑎
Aggregate CCA Attempts Arrival Rate
Probability of an IEEE 802.15.4 device successfully
𝑃𝑐𝑐𝑎
passing CCA (i.e., attempting transmission)
𝑃𝑆
Probability of a successful IEEE 802.15.4 transmission
𝑚𝑎𝑥
Maximum Number of Allowable Backoffs
𝑁𝐵
𝐵𝐸𝑚𝑖𝑛
Minimum Backoff Exponent
𝐵𝐸𝑚𝑎𝑥
Maximum Backoff Exponent
𝑃𝑅𝑆
Success Report Probability
Submission
Slide 5
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Report Success Probability Analytical
Model
Poisson-Based Model
Aggregate CCA Attempts Rate
𝜆𝑐𝑐𝑎 = 𝜆𝑅
1 − 1 − 𝑃𝑆
𝑚𝑎𝑥
𝑁𝐵
+1
𝑃𝑆
Probability of Collision Free Transmission
𝑠
𝑑
𝑃𝐶𝐴 × 𝑃𝐶𝐴
𝑃𝑆 =
1 + 𝐿𝑀 + 1 1 − 𝑒 − 1−𝑞 𝜆𝑐𝑐𝑎 𝑇𝑆
Successful Report Probability (i.e., less
𝑚𝑎𝑥
than 𝑁𝐵
CCA attempts)
𝜆𝑐𝑐𝑎 𝑃𝑆
𝑃𝑅𝑆 =
𝜆𝑅
Submission
Slide 6
Collision Avoidance Probability w.r.t to
Visible Nodes
𝑠
𝑃𝐶𝐴 = 𝑒 −
1−𝑞 𝜆𝑐𝑐𝑎 𝑇𝑆
Collision Avoidance Probability w.r.t to
Hidden Nodes
𝑑
𝑃𝐶𝐴 = 𝑒 −𝑞𝜆𝑐𝑐𝑎 𝑃𝑐𝑐𝑎 𝑇𝑆 ×
𝐿𝑀 −1
× 𝑒 −𝑞𝜆𝑐𝑐𝑎 𝑇𝑆 ×𝐿𝑀
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Model Parameters for Battery Lifetime
Parameter Description
Drained Current when an IEEE 802.15.4 device is in
𝐼𝑅𝑋
Receive mode
Drained Current when an IEEE 802.15.4 device is in
𝐼𝑇𝑋
Transmit mode
Drained Current when an IEEE 802.15.4 device is in
𝐼𝐼𝐷
Idle mode
Effective Average Drained Current by an IEEE
𝐼𝑒𝑓𝑓
802.15.4 Device.
𝑇𝑅𝑋
Percentage of Time Spent in Receive mode
𝑇𝑇𝑋
Percentage of Time Spent in Transmit mode
𝑇𝐼𝐷
Percentage of Time Spent in Idle mode
𝐵𝐿
Expected Meter Battery Lifetime
𝐶𝐵
Meter Battery Capacity
Submission
Slide 7
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Battery Lifetime Analysis
• IEEE 802.15.4 Device States:
– Transmit
• 𝑇𝑇𝑋 =
𝜆𝑐𝑐𝑎
(𝑃𝑐𝑐𝑎 𝐿𝑀 𝑇𝑆 )
𝑁𝑀
– Receive
• CCA Checks
• ACK Reception
• 𝑇𝑅𝑋 =
𝜆𝑐𝑐𝑎
𝑁𝑀
Probability of Passing First CCA
0.4𝑇𝑆 1 + 𝑃𝑐𝑐𝑎1 + 𝑃𝑐𝑐𝑎 𝑇𝑎𝑐𝑘−𝑅𝑋
𝑃𝑐𝑐𝑎1 = 1 − 1 − 𝑒 −
1−𝑞 𝜆𝑐𝑐𝑎 𝑇𝑆
𝐿𝑀 𝑃𝑐𝑐𝑎
– Idle/Sleep
• 𝑇𝐼𝐷 = 1 − 𝑇𝑅𝑋 − 𝑇𝑇𝑋
– 𝐼𝑒𝑓𝑓 = 𝐼𝑅𝑋 𝑇𝑅𝑋 + 𝐼𝑇𝑋 𝑇𝑅𝑋 + 𝐼𝐼𝐷 𝑇𝐼𝐷
• 𝐵𝐿 =
Submission
𝐶𝐵
𝐼𝑒𝑓𝑓
Slide 8
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
OMNET++ Simulation Model
Note: external interference
disabled
𝟏𝟎𝟎 × 𝟏𝟎𝟎 𝒎𝟐
Communication Range Vs Percentage of Hidden Nodes
1
0.9
Percentage of hidden Nodes q
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
Submission
Slide 9
20
40
60
80
Communication Range (m)
100
120
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Analytical Model Verification
Submission
Report Success Probability P
RS
RS
Report Success Probability P
0.8
0.6
0.4
Analytical Model
BEmin = 3, BEmax = 3
0.2
BEmin = 3, BEmax = 8
BEmin = 8, BEmax = 8
0
1000
1200
1400
1600
1800
Number of 802.15.4 enabled Meters NM
0.8
0.6
0.4
Analytical Model
BEmin = 3, BEmax = 3
0.2
BEmin=3, BEmax = 8
BEmin = 8, BEmax = 8
0
1000
2000
q = 0.5
Analytical Model
BEmin = 3, BEmax = 3
BEmin = 3, BEmax = 8
BEmin = 8, BEmax = 8
0.6
0.4
0.2
1200
1400
1600
1800
Number of 802.15.4 enabled Meters NM
Slide 10
2000
RS
1
0.8
0
1000
1200
1400
1600
1800
2000
Number of 802.15.4 enabled Meters NM
q = 0.75
1
Report Success Probability P
• Performance
strongly impact
by hidden nodes
percentage
q = 0.25
1
RS
• It is better to
increase 𝐵𝐸𝑚𝑖𝑛
and 𝐵𝐸𝑚ax
Report Success Probability P
• The analysis is
an upper bound
q=0
1
0.8
Analytical Model
BEmin = 3, BEmax = 3
BEmin = 3, BEmax = 8
0.6
BEmin = 8, BEmax = 8
0.4
0.2
0
1000
1200
1400
1600
1800
2000
Number of 802.15.4 enabled Meters NM
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Mapping Hidden Nodes to Tx Power
TI CC2630 Datasheet
𝑑𝑀𝑎𝑥 =
10
𝑃𝑇𝑥 −𝑅𝑥 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦−105
10
Variable
𝐼𝑇𝑋
20
× 5032
15
Value
6.1 𝑚𝐴 0 𝑑𝐵𝑚 𝑇𝑥 𝑃𝑜𝑤𝑒𝑟
9.1 𝑚𝐴 5 𝑑𝐵𝑚 𝑇𝑥 𝑃𝑜𝑤𝑒𝑟
Rx Sensitivity
5.9 𝑚𝐴
1 𝜇𝐴
−100 𝑑𝐵𝑚
𝐶𝐵
225 𝑚𝐴ℎ (𝐶𝑅2032 𝐶𝑜𝑖𝑛 𝐵𝑎𝑡𝑡𝑒𝑟𝑦)
𝐼𝑅𝑋
𝐼𝐼𝐷
Submission
Pathloss Exp n = 3.5
Pathloss Exp n = 2.7
17.5
Transmission Power PTx (dBm)
𝑛
𝑑𝑀𝑎𝑥 to Percentage of Hidden Nodes from
OMNET++ Model in Urban Environment
12.5
10
7.5
5
2.5
0
-2.5
-5
Slide 11
-7.5
-10
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Percentage of Hidden Nodes q
0.8
0.9
Tallal Elshabrawy, German University in Cairo
1
Feb. 2017
15-17-0130-00-lpwa
Contour Plot for 𝑃𝑅𝑆 Performance versus 𝑞
(𝑚𝑎𝑥)
and 𝑁𝐵
given 𝑁𝑀 = 1000 and 𝐿𝑀 = 6
10
1
0.
0.9
5
5
0.1
0.
25
0.
3
35
0.
5
0.6
0.7
0.75
0.8
0.85
5
2
0.
6
0.4 45 5
0.
0. 55
6
0.
0.
0.9
4
0. .45 5
0
0.
4
5
0.9
9
0.
0.
55
0.
85
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Percentage of Hidden Nodes (q)
Slide 12
0.
65
0.7
2
0.75
0.8
Maximum Number of Backoffs (N(Max)
)
B
5
0.0
5
0.1
5
0.2
3
0. 35
0.
7
3
Submission
0.2
0.95
0.75
85
00..8
8
0.4 .45 .5
0
0
5
0.5 0.6
5
0.6
0.7
0.9
9
0.8
0.
6
0.9
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Contour Plot for 𝐵𝐿 Performance versus 𝑞 and
𝑚𝑎𝑥
𝑁𝐵
given 𝑁𝑀 = 1000 and 𝐿𝑀 = 6, 𝑇𝑅 = 6𝑠 and
Urban Environment Pathloss 𝒏 = 𝟐. 𝟕
60
30
45
35
50
6
40
5
0.9
5
55
P(T)
RS
30
45
4
63 .5
63 .5
66
0.1
40
55
60
5
0.9
3
35
50
60
(Max)
Maximum Number of Backoffs (NB
)
40
7
2
Submission
0.95
𝐵𝐿𝑚𝑎𝑥 ≈ 63.5 months.
35
55
=3
8
60
𝑚𝑎𝑥
𝑁𝐵
60
9
𝑞 = 0.15
 𝑃𝑇𝑥 = 2.5 𝑑𝐵𝑚
30
50
Mild Urban Env.
45
10
66
0.2
Slide 13
63 .5
55
60
0.3
0.4
0.5
0.6
0.7
Percentage of Hidden Nodes (q)
0.8
50
0.9
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Contour Plot for 𝐵𝐿 Performance versus 𝑞 and
𝑚𝑎𝑥
𝑁𝐵
given 𝑁𝑀 = 1000 and 𝐿𝑀 = 6, 𝑇𝑅 = 6𝑠 and
Urban Environment Pathloss 𝒏 = 𝟑. 𝟓
10
Severe Urban Env.
𝐵𝐿𝑚𝑎𝑥 ≈ 22 months.
20
22
P(T)
RS
6
24
22
22
26
0.9
5
20
5
24
28
26
4
3
24
5
0.9
30
28
30
26
28
2
Submission
20
20
0.1
30
=5
7
22
𝑚𝑎𝑥
𝑁𝐵
8
20
(might not be affordable)
0.95
𝑞 = 0.3
 𝑃𝑇𝑥 = 15 𝑑𝐵𝑚
(Max)
Maximum Number of Backoffs (NB
)
9
0.2
Slide 14
0.3
0.4
0.5
0.6
0.7
Percentage of Hidden Nodes (q)
0.8
0.9
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Contour Plot for 𝐵𝐿 Performance versus 𝑞 and
𝑚𝑎𝑥
𝑁𝐵
given 𝑁𝑀 = 1000 and 𝐿𝑀 = 6, 𝑻𝑹 = 𝟖𝒔
and Urban Environment Pathloss 𝒏 = 𝟑. 𝟓
40
8
30
7
35
45
40
35
5
Submission
45
P(T)
RS
50
55
4
5
0.9
0.1
0.2
Slide 15
55
45
40
35
30
0.95
2
60
50
3
𝐵𝐿𝑚𝑎𝑥 ≈ 50 months.
0.95
40
6
30
(Max)
Maximum Number of Backoffs (NB
)
=4
9
30 35 40
0.95
𝑚𝑎𝑥
𝑁𝐵
35
𝑞 = 0.74
 𝑃𝑇𝑥 = 4 𝑑𝐵𝑚
30
Relaxing Reporting
Rate
10
0.3
0.4
0.5
0.6
0.7
Percentage of Hidden Nodes (q)
0.8
.5
63 6
6 .5
68
0.9
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Conclusions & Further Proposals
• Report Success Probability is improved by setting the backoff
exponents to the maximum value
• Report Probability Performance is affected by Hidden Nodes
Percentage and Maximum Number of Backoffs
• Controlling Hidden Nodes by Transmit Power can signifcantly
improve performance
• Further Proposals
– Controlling Hidden Nodes by Enhancing Sensing Algorithms
– Controlling Hidden Nodes by Base station Time Scheduling of
Multiple PAN IDs
Submission
Slide 16
Tallal Elshabrawy, German University in Cairo
Feb. 2017
15-17-0130-00-lpwa
Thank You
Discussion?
Submission
Slide 17
Tallal Elshabrawy, German University in Cairo