Interference aware channel switching

1. IEEE Proceedings of 4th International Conference on Intelligent Human Computer Interaction, Kharagpur, India, December 27-29, 2012
Interference-Aware Channel Switching for Use in
WBAN with Human-Sensor Interface
Judhistir Mahapatro∗, Sudip Misra†, Senior Member, IEEE, Manjunatha M‡, Member, IEEE, Nabiul Islam§
∗ ‡ School of Medical Science and Technology
† § School of Information Technology
Indian Institute of Technology, Kharagpur
West Bengal, India - 721302
Email: {∗jmahapatro, †smisra, §nabiuli}@sit.iitkgp.ernet.in, ‡mmaha2@smst.iitkgp.ernet.in
Abstract—A Wireless Body Area Network (WBAN) consists of
different medical sensors connected to an on-body coordinator
through a wireless medium. The sensors are placed over a human
body for continuous monitoring of physiological parameters. The
information sensed by the nodes are transmitted to the on-body
coordinator. Upon receiving these information from the sensor
nodes, the coordinator transmits the same to the medical server
for post data analysis.
Any radio frequency based wireless device suffers from inter-
ference due to the existence of other wireless devices operating in
the same licence-free frequency band. In this paper, we address
the problem of interference when multiple WBANs come in
the proximity of one another. In such a scenario, the WBAN
senses the existence of other interfering WBANs, based on the
Signal-to-Interference Ratio (SIR). We propose an interference-
aware channel switching algorithm (InterACS) for WBANs, so
that there is seamless communication with their sensors without
interference among them. We simulated the proposed solution
using the NS-3 network simulator and observed that there is
improvement in reducing the number of interferences by using
the proposed solution scheme.
Index Terms—WBAN, Interference, TDMA, Human Computer
Interaction, Human-Sensor Interface
I. INTRODUCTION
An important application domain of sensor networks is
medicine and health care. A WBAN is a special purpose
sensor network where different medical sensors are attached
on clothing or on a human body. With the help of this emerging
technology, the real-time physiological information of human
bodies can be obtained. Because of its user-friendly and cost-
effective solution for continuous monitoring, vital signs of
patients, especially those who suffer from diseases such as
Alzheimers, Parkinsons, cardiovascular diseases (CVDs) can
be monitored. WBANs are also deployed in elderly persons
for monitoring their daily activities.
The various implanted and worn-on sensors are attached in-
body or on-body respectively. The monitored parameters by
the nodes are aggregated, and are sent to a remotely placed
medical server for post data analysis [1]. The architecture of
such a low-power network is showin in Fig. 1.
Interference is a characteristic phenomenon observed in
wireless networks when cuncurrent transmissions from radio
devices occur over the shared medium. There are two typical
cases of interference that may occur: (1) Cuncurrent transmis-
sions from the nodes of two different collocated networks, for
example, superimpose the transmitted signals of two different
nodes of two different WBANs, as shown in Fig. 2, and
(2) Cuncurrent transmissions from the nodes of the same
network, for example, superimpose the transmitted signals of
two different nodes of the same WBAN. The second case of
interference is easily handled by employing Time Division
Multiple Access (TDMA) based schedules within the WBAN.
It is markedly challenging to handle the first case of inter-
ference because WBANs use the 2.4 GHZ licence-free band
(eg., ISM) for their operation. Several other wireless devices
based on Wi-Fi, Bluetooth, and other Body Area Networks
(BANs) share the same frequency band, thereby causing huge
interference possibilities. The effect of this interference is
very serious for patients equipped with BANs, because the
devices monitor their critical conditions involving instruments
for measuring ECG, EEG, and EMG. The seriousness is such
that the misinterpretation of signals due to interference can led
to the death of patient [2]. This motivated us to investigate the
problem of interference in the presence of multiple WBANs.
Let us consider an example of two aged persons carrying
BANs, with the devices measuring their critical physiological
parameters. Let us consider that they are living in the same
house or an old-age home and are talking to each other for long
duration of time while sitting together. In this case, both BANs
send false information to the medical server. The situation
becomes even worse if the BANs carry life saving actuators
such as glucose actuators, which pump the correct dose to the
diabetics if the glucose level goes beyond or below the normal.
In this paper, we specifically explore the problem of network
interference between WBANs with human-sensor interface.
This happens when two or more BANs come in the proximity
of one another and stay for longer time. Among different
types of interference such as co-channel interference, and
adjacent channel interference, the network interference is
predominant [3].
In [4], the interfering signals from various links of the WSN
are scheduled at different times. The typical hardware solution
is to use dual radios, one for IEEE 802.15.4, and the other
for IEEE 802.11, which are used to mitigate interference [5].
The MIMO technology has been proven useful in mitigating
interference in cellular networks [6]. The constraint of low
power consumption makes it inefficient to adapt power control
978-1-4673-4369-5/12/$31.00 c 2012 IEEE

2. strategy, which is used in cellular networks [7].
In our previous paper [8], we proposed a solution where
two or more BANs cooperate between themselves and agree
to a common schedule, rather than send data independently.
If they agree to a common schedule, there might be a case
that devices attached to a BAN wait for relatively longer time
than those that have large traffic or they are in large numbers
attached to other BANs. In this case, the schedules interleave
among themselves so that the average latency per node is
minimized. This approach has only overhead that the messages
are exchanged between the coordinators to create a common
schedule.
Due to interference/collision, the nodes attempt to retransmit
the loss packet, and for which a node can consume extra
amount of energy. In addition to, the propagation of wireless
signals in body area communications experiences fading due
to diffraction, reflection, energy absorption, and shadowing by
body and clothes [9]. Therefore, overall, we need a solution
that should be a light weight in terms of resource utilization.
Mainly two classes of MAC protocols are considered
for such medical applications of sensor networks. They are
TDMA-based and contention-based. In a WBAN, it has been
observed that slot-based MAC protocols are suitable for
improved operation and performance, since such protocols
require no additional overhead and data load is uniform
across the nodes. In the literature, most of implementations
of WBAN use the IEEE 802.15.4 or its variant for low power
consumption [10] [11] [12]. It considers a star topology and
each sensor node sends traffic to a coordinator(controller)
in their own slot time. The coordinator of WBAN has to
schedule the transmission of its physiological sensors. The
sensors buffer their generated traffic until they get the time
slot they have been assigned to transmit to the coordinator.
Fig. 1: Architecture
The rest of the paper is organized as follows. Section II
discuses the proposed interference framework for the WBANs.
In Section III, we discuss the interference aware channel
switching algorithm for WBANs. In Section IV, we present
the simulation results, and we conclude the paper in Section V.
II. PROPOSED FRAMEWORK FOR INTERFERENCE
As shown in Fig. 3, the proposed interference framework
consists of a set of network nodes, device state models, and
the interfaces interconnecting them. State models represent
different states of a node at different time. These states include
Transmit (Tx), Receive (Rx), and Idle. The other components
such as propagation model and propagation delay represent the
amount of power loss due to the environment obstacles and the
amount of delay caused for the tranmission over the wireless
medium. The interactions between an WbanInterferenceHelper
and WbanPhyStateHelper are: (1) WbanInterferenceHelper
model records the duration of a node it receives, and (2) Wban-
PhyStateHelper notifies when a node transmit/Receive/Idle.
Fig. 2: Interference between two WBANs
Let us suppose multiple WBANs come in the proximity
of one another. This leads to more than one patient carrying
WBANs coming in the proximity of one another. In such a
scenario, required number of channels for WBANs may not
be sufficient, and, therefore, this could lead to the interference
between them.
III. INTERACS: THE INTERFERENCE-AWARE CHANNEL
SWITCHING ALGORITHM
Interference occurs due to external nodes concurrently trans-
mitting within the transmission range of a sender, while its data
transmission is underway. Eventually this degrades the Signal-
to-Interference Ratio (SIR) of the sender [13]. We assume that
the coordinators are not constrained in the context of resources
as compared to their physiological sensor nodes. Therefore, the
coordinator node periodically monitors the level of SIR and
when it finds the SIR of the device below a threshold value,

3. Fig. 3: Framework for Interference
it switches to a different channel. The selection of channel
by the coordinator is based on the level of SIR. The value of
SIR is divided into three different categories such as LOW,
MODERATE, and HIGH. If the SIR value at the coordinator
is LOW, MODERATE, and HIGH, it switches to next 2-
hop channel, next 3-hop channel, and next 4-hop channel
respectively. The proposed algorithm is presented below.
Algorithm: InterACS
1: Inputs: An array of WBANs and their SIRs, SIR
thresholds(δT )
2: Output: Switch to a different channel; otherwise, no
switch
3: Procedure:
4: done ← false
5: Each WBAN Coordinator measures its SIR
6: if (SIR < δT ) then
7: while (not done) do
8: Wait for random time
9: Broadcast the channel information
10: Wt ← WaitforAcknowledgement
11: if (Wt > Tt(Time out)) then
12: Repeat the loop three times
13: else
14: done ← true
15: end if
16: end while
17: else
18: No Switch
Fig. 4: Average data rate versus Interference count with four
WBANs
19: end if
20: if (done) then
21: if (SIR is High) then
22: Switch to next 2-hop channel
23: else
24: if (SIR is Moderate) then
25: Switch to next 3-hop channel
26: else
27: if (SIR is Low) then
28: Switch to next 4-hop channel
29: end if
30: end if
31: end if
32: end if
33:
IV. PERFORMANCE EVALUATION
In this Section, we report the results of simulation exper-
iments conducted using NS-3 [14] to investigate the perfor-
mance of the proposed scheme for mitigating network inter-
ference arising due to the co-existence of different WBANs.
A. Simulation Settings
We considered a simulation area of 50 m × 50 m. We use
the Random-Waypoint mobility model to move the WBANs
within the above mentioned area. The propagation time used
is the speed of light multiplied by the distance between the
nodes, and therefore, it is (3.3 × d) nano-seconds, where ‘d’
is distance between the coordinator and the nodes, and d ≤ 10
(in meters). We executed the simulations for 100 seconds with

4. Fig. 5: Average data rate versus Interference count for Uni-
form, where W1=4, W2=6, W3=8, and W4=10. W1 to W4
present the number of WBANs
different set of parameters such as the number of WBANs and
data rate.
B. Performance metrics
We used the following two perfomance metrics to evaluate
the performance of the proposed solution.
• Average data rate : It is average data rate with
which the sensor nodes transmit data packets through
their physical interface.
• Interference count : It is defined as the total number
of times interference occur at a particular coordinator of
a WBAN.
C. Results and Disscusion
In our simulation experiments, the random network topol-
ogy of WBANs was generated by the position allocator tool
of the NS-3 simulator. It was observed that an increase in
the average data rate of WBANs results in an increase of the
interference count. This is shown in the plot in Fig. 4. Our pro-
posed algorithm (InterACS) was compared with a uniformly
channel switching approach (Uniform) where the channels are
selected randomly. Another observation is that when we vary
the number of WBANs with respect to the average data rate
and observe the improvement in reduction of the interference
count, therefore, our proposed algorithm shows better perfor-
mance when the number of WBANs increases. In other words,
we can say that when the number of WBANs increase, the
available number of channels required also increase. Similarly,
the average data rate versus interference count by varying the
WBANs using Uniform has been shown in Fig. 5. The average
Fig. 6: Average data rate versus Interference count for Inter-
ACS, where W1=4, W2=6, W3=8, and W4=10. W1 to W4
represent the number of WBANs
data rate versus interference count while varying the WBANs
using InterACS has been shown in Fig. 6.
V. CONCLUSIONS AND FUTURE WORK
In this work, we investigated the effect of network inter-
ference between multiple WBANs with their human-sensor
interface and then proposed a scheme for avoiding interference
caused from other collocated WBANs. We observed that the
proposed scheme reduces its total interference count when
different human body with carrying WBAN come in the
proximity of one another. In the future, we would like to
investigate the interference effects in scenarios where the
density of WBANs is more. In such a scenario, we would
like to investigate that how well our proposed algorithm will
perform.
ACKNOWLEDGEMENT
This work was supported by a grant from the council of
scientific and Industrial Research (CSIR), India (Grant Ref.
No. 22/477/09-EMR-II).
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