Enabling Coexistence of
Heterogeneous Wireless Systems:
Case for ZigBee and WiFi
Xinyu Zhang
xyzhang@eecs.umich.edu
Kang G. Shin
kgshin@eecs.umich.edu
The University of Michigan
Coexistence between ZigBee and WiFi
Spatial coexistence:
ZigBee
(monitoring & control)
WiFi (Internet access)
Frequency-domain coexistence (spectrum sharing):
20MHz
Current scheme for managing coexistence
Built-in MAC protocols:
CSMA/CA  Listen before you talk
Versions used by both ZigBee and WiFi
Is the built-in CSMA/CA effective?
Some small scale measurement studies:
Severe collision occurs under moderate to high WiFi traffic
Evidence from the real-world:
In a 90-node ZigBee building energy monitoring network.
50+% ZigBee nodes suffer connection loss during WiFi peak hours
[C-J. M. Liang, et al., “Surviving Wi-Fi Interference in Low Power
ZigBee Networks,” SenSys 2010, November 2010]
Why CSMA fails
Heterogeneity challenges coexistence:
Scheduling mode: ZigBee allows TDMA mode
Problem: direct collision (no carrier sensing)
Transmit power: WiFi:  15dBm; ZigBee: < 0 dBm
Problem: asymmetric interference
WiFi
transmission
range
Asymmetric
interference
region
ZigBee
transmission
range
Why CSMA fails
Time resolution:
e.g., WiFi: 9 us; ZigBee: 320us
Problem: preemption:
Communication barrier:
WiFi: OFDM; ZigBee: DSSS
Problem: lack of ability to negotiate
New solution: Cooperative Busy Tone (CBT)
Principles of CBT:
Make ZigBee visible to WiFi, without interfering with
ZigBee
Allow ZigBee to coexist and contend with WiFi in
frequency, spatial, and temporal domains
Preserve carrier-sensing-based spectrum etiquette
CBT Overview
switching time
WiFi
client
ZigBee TX
signaler
WiFi
AP
DATA
ACK
ZigBee
signaler
ZigBee
TX
A separate node
(ZigBee signaler) emits a
busy-tone to make WiFi
aware of ZigBee
transmission
WiFi TX
CCA, DATA ACK
backoff
Busy tone harbingers
the data packet and
continues throughout the
DATA-ACK transmission
to prevent WiFi
preemption
Challenges
How can the busy-tone be prevented from interfering
with the ZigBee data packet?
When should the signaler begin and end sending the
busy-tone?
Signaler “frequency flip”
Avoids signaler interfering with ZigBee data packet:
Busy tone
Transmitter sends data packet on some channel
Signaler sends busy-tone on an adjacent channel
Return to the original channel after sending the busy-tone
Busy-tone scheduler objectives
Schedule the signaler’s busy-tone so as to:
reduce WiFi preemption of ZigBee transmissions
minimize the potential influence on WiFi performance
be able to protect both the TDMA and CSMA modes of ZigBee
Busy-tone scheduler: TDMA mode
CCA attempts
frequency flip
Harbinger time
Key parameter: harbinger time H s  KmCz  J z
H s too large: busy-tone wastes channel time
H s too small: no idle slot can be sensed, busy-tone aborted
Analytical framework: relate H s to network performance
Busy-tone scheduler: CSMA mode
backoff
CCA switching
frequency flip
Key parameter: busy-tone duration Tb
Tb too large: busy-tone wastes channel time
Tb too small: data/ACK may not be protected
Enlarge Tb by extending busy-tone time by Kb extra slots
Analytical framework: relate Tb to network performance
Performance analysis and parameter optimization
Network model:
Topology: co-located ZigBee and WiFi networks,
Sz  Wt (ZigBee signaler within range of WiFi transmitter)
Traffic: Poisson, arrival rate
z
and
w , respectively
Parameters:
Traffic intensity
z
and
w
Topology: Zt  Wt or Zt  Wt
(ZigBee transmitter within range of WiFi transmitter, or not)
Transmit power
z
and
w
Using legacy ZigBee or CBT
Performance analysis and parameter optimization
Performance metrics:
Normalized throughput:
z
and
w
Approach:
Assume ZigBee does not affect WiFi traffic (low power and
low duty cycle)
Analyze collision probability under each parameter setting
Analyze throughput based on collision probability:
Focus primarily on temporal collision probability
Incorporate spatial collision probability (includes
node locations and capture effect)
ZigBee TDMA mode with WiFi
Collision probability of legacy ZigBee:
Tag an arbitrary packet from Zt , and calculate the
collision probability with randomly arrived Wt packets
(assuming ZigBee does not affect WiFi traffic)
Collision probability of CBT:
Relate CCA failure rate to harbinger time H s
(derived in Proposition 1 in paper)
Relate collision probability to the CCA failure rate:
Derive collision probability as a function of
w , z , H s ,
etc.
ZigBee TDMA mode with WiFi (cont’d)
Network performance:
Model transmission attempt of Zt as a renewal reward process
ZigBee throughput = mean reward rate =
Prob.[no collision]
 data packet size
Average amount of data sent within an attempt
Mean service time of a data packet
Includes retransmission, ACK, and switching time
WiFi throughput approximated using simpler model (in paper):
Depends on whether or not Zt  Wt
ZigBee CSMA mode with WiFi
Performance of legacy ZigBee:
Derive mean service time, based on a Markov chain model
BSi : i-th backoff &
CCA stage
Ptx:
Pd :
Pa :
Transmission probability (after CCA)
Data packet collision probability
ACK packet collision probability
These depend on
WiFi traffic intensity
ZigBee CSMA mode with WiFi (cont’d)
Performance of CBT:
Similar Markov chain model
Also depends on key parameter: busy tone duration Tb
If Tb = data packet duration + max backoff&CCA duration,
then collision probability

0
Otherwise, the collision probability is bounded:
Bound depends on Tb (derived in Proposition 2 in paper)
Spatial collision probability I e
Probability that a packet cannot be decoded, given
that temporal collision already occurs
(Account for capture effect)
Approximate I e in
a random topology:
Details in the paper
Simulation and testbed evaluation
Simulation:
Based on ns-2 ZigBee model
Modeled CBT (TDMA and CSMA mode) in ns-2
Testbed experiments:
Legacy ZigBee: Based on openzb in TinyOS, running on
MICAz motes
CBT (TDMA mode): implementation of signaler in GNURadio,
running on USRP2 software radio
Synchronize USRP signaler to ZigBee coordinator using short
notification messages
Temporal collision probability
Markers = simulation results; lines = analytical results
Analysis matches simulation
CBT significantly reduces the collision rate for both
data and ACK packets
Spatial-temporal collision probability
Probability that ZigBee cannot decode collided packet
(accounting for capture effect and random node locations)
dt
Zt  Wt Zt  Wt
Out of interference range
Normalized throughput: TDMA mode
Sweet spot
CBT gives about 2  ZigBee throughput improvement under
moderate to high WiFi traffic
Negligible degradation of WiFi throughput, compared with
legacy ZigBee
CBT may have lower throughput than legacy ZigBee under
light WiFi traffic (a sweet spot exists)
Impact of harbinger time in TDMA mode
Larger K m
larger H s
more overhead, but
higher ZigBee throughput under high WiFi interference
Under low duty-cycle ZigBee traffic (below 0.05), WiFi
throughput is virtually unaffected by harbinger time
Experimental testbed configuration
Node locations:
Nodes A and B are WiFi
All other nodes are ZigBee (MICAz motes)
Only TDMA mode implemented
CBT signaler implemented in GNURadio on USRP2 software radio
Testbed results: Collision probability (TDMA mode)
For randomly selected links:
CBT reduces collision rate by 60+% for most links
Testbed results: Impact on WiFi (TDMA mode)
WiFi packet delay:
CBT and legacy ZigBee have similar effects on WiFi
performance
WiFi performance essentially unaffected when ZigBee
traffic load < 2%
Conclusion
Traditional CSMA fails in heterogeneous networks:
Due to disparate MAC/PHY properties
CBT resolves collision between ZigBee and WiFi:
Busy-tone scheduler: ensure busy-tones protect data packets
Frequency flip: preventing signaler/transmitter interference
Stochastic models for performance analysis and optimization
Simulation as well as measured testbed performance
Possible future work:
Extension to other heterogeneous networks, such as
WiFi/Bluetooth (802.15.3), WiFi/WiMax (802.11y), and
whitespace networks
Appendix
Normalized throughput
CSMA mode
Impact of busy-tone duration in CSMA mode
CSMA mode