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Int. J. Sensor Networks, Vol. x, No. x, xxxx 1
Performance evaluation of IEEE 802.15.6-based
WBANs under co-channel interference
Muhammad Mahtab Alam* and Elyes Ben Hamida
Qatar Mobility Innovations Center,
Qatar Science and Technology Park,
Doha, Qatar
Email: mahtaba@qmic.com
Email: elyesb@qmic.com
*Corresponding author
Abstract: In this paper, interference mitigation and coexistence strategies proposed in IEEE 802.15.6
standard are investigated within the context of co-channel interference. A comparative evaluation
of the reference scenario (which does not use any coexistence scheme), two non-collaborative (i.e.,
time shared, random channel) and one implicitly collaborative (i.e., CSMA/CA) based coexistence
schemes is presented for five co-located bodies. Extensive set of physical, medium access control
(MAC) parameters are invoked to realise a comprehensive study with enhanced IEEE 802.15.6
proposed channel models. It is concluded that there is trade-off between coexistence schemes. For
example, time shared and random channel provides much better packet reception ratio (PRR) and
energy efficiency, though they suffer in meeting the delay constraints of the IEEE 802.15.6 standard.
Whereas, CSMA/CA based implicit collaborative approach is able to achieve the delay requirements
however, it does not perform well both in terms of PRR and energy consumption.
Keywords: WBAN; wireless body area networks; BBN; body-to-body networks; interference
mitigation; coexistence; performance evaluation; IEEE 802.15.6 standard.
Reference to this paper should be made as follows: Alam, M.M. and Hamida, E.B. (xxxx)
‘Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference’,
Int. J. Sensor Networks, Vol. x, No. x, pp.xxx–xxx.
Biographical notes: Muhammad Mahtab Alam (PhD) is a Research Scientist in Qatar Mobility
Innovations Center, Qatar. His research interests are in the fields of self-organised and self-adaptive
wireless sensor and body area networks, energy-efficient communication protocols and algorithms,
signal processing and radio-link and mobility modelling.
Elyes Ben Hamida (PhD) is currently a IoT Product Manager and R&D Expert at the Qatar Mobility
Innovations Center (QMIC) in Doha, and has more than 10 years of R&D experience in the
fields of wireless networking, telecommunications and security. He has been involved in several
international and industrial R&D projects. He is an inventor of six patents and published more than
60 publications.
1 Introduction
Wireless body area networks (WBAN) is a self organised
network at the human body scale. It consists of heterogeneous
smart devices which are low-power, miniaturised, hardware-
constrained with limited processing and storage capabilities.
These devices can be sensors (to sense, transmit and receive
data), actuators (to react according to the perceived data) or
coordinators (to act as a gateway for the external network).
There are number of WBANs applications such as healthcare,
sports and fitness, rescue and emergency management,
augmented reality and many more (Alam and Hamida, 2014b),
and to meet their requirements, Institute of Electrical and
Electronics Engineers (IEEE) has introduced a new standard
for WBAN (i.e., IEEE 802.15.6 (2012)). While effectively
realising emerging applications, WBAN communication has
to extend from on-body to body-to-body networks (BBN)
(Hamida et al., 2014).
However, one of the fundamental problem while multiple
bodies interact and being close to each other is that the sensors
connected on one body interfere with the sensors connected
on the other bodies and therefore, can interrupt the intra
and inter body communications. In this regard, most of the
existing literature is based on adjacent channel interference
(i.e., interference from other standards), whereas interference
mitigation and coexistence schemes for BBN is limited. The
focus in this paper is to ensure effective communication
within and between multiple co-located bodies by applying
suitable coexistence strategies and to evaluate and compare
their performance under realistic environment.
Performance evaluation of IEEE 802.15.6 standard is one
of the important topics in the WBANs. Often the evaluation
Copyright © 20xx Inderscience Enterprises Ltd.
2M.M. Alam and E.B Hamida
of the novel algorithms and protocols is achieved under very
ideal environment and therefore the accuracy of such solutions
becomes questionable. There are number of important aspects
that needs to be taken into account for a realistic performance
evaluation. These includes, accurate channel models, mobility
and radio-link models, exact physical (PHY) configurations
and corresponding BER, Eb/No, PER of the modulation
schemes, further the comparison of the MAC protocols and
coexistence schemes are very critical.
There are number of challenges and limitation for accurate
performance evaluation of IEEE 802.15.6 standard. Recently,
Cavallari et al. (2014), Rahman et al. (2015), Wong et al.
(2012) and Lee et al. (2013) claimed to be the IEEE 802.15.6
compliant radio transceivers however, they are limited due
to several reasons. First, the utilisation of low frequency
bands (sub-giga spectrum) which does not often satisfy most
of the applications data rates requirement. Second, only
transmitter is available without fully IEEE 802.15.6 standard
compliant. Finally works such as Cavallari et al. (2014) shows
interesting experimental results using platform implementing
the IEEE 802.15.6 CSMA/CA protocol. However, to best of
our knowledge, IEEE 802.15.6 compliance radio transceivers
are still to come. Another possible solution is to realise
mathematical proofs and develop analytical models, however,
WBAN and BBN networks are very complex mainly due
to large set of parameters and variables. For example, at
the physical (PHY) and medium access control (MAC)
layers there are number of possible combinations and
along with space-time varying radio-link and channel,
accurate mobility and associated interference models for
different applications, the analytical analysis becomes highly
complicated. Therefore, very specific and small scale analysis
are feasible which are not complete and extensive. So,
simulations can be a viable alternate provided an extensive
set of parameters and all the important factors (as explained
above) being taken into account.
In this realm, we have developed the IEEE 802.15.6
compliant open-source simulator which is going to add (as
an option) to the existing OMNet++ based Castalia simulator.
Castalia is limited only to the WBAN channel models and
currently it support only the draft version of the IEEE 802.15.6
standard with only basic MAC model (i.e., baseline MAC)
(Lu et al., 2013) and not fully compliant to PHY and MAC
models proposed in IEEE 802.15.6 standard.
To bridge the gap and limitations of existing studies, this
paper provides an important addition towards an accurate and
complete performance evaluation of IEEE 802.15.6 standard.
In our previous study we evaluated the performance of intra-
BAN communication using IEEE 802.15.6 standard (Alam
and Hamida, 2014a). The focus in this paper is to ensure
effective communication within and between multiple bodies
by applying suitable coexistence strategies under varying set
of PHY and MAC configurations. The contributions of this
paper are as follows:
First: To enhance the accuracy of the evaluation of the
IEEE 802.15.6 standard MAC layer, at first, we have
proposed accurate biomechanical mobility (i.e., for on-body)
and group mobility (i.e., for body-to-body communication),
which are based on real-time motion captured system.
The biomechanical model not only helps to provide
dynamic mobility patterns which are required to mimic
diverse applications (such as rescue and critical, emergency
management, remote health monitoring of the workforce as
well as mobile health etc.), but also it provides accurate space
and time variations of the various sensors connected on the
body. Thus, these accurate variations help to enhance the
existing IEEE 802.15.6 proposed channel models which are
based on static distances and therefore are not realistic to
various dynamic applications. Realistic biomechanical intra
and inter BAN mobility model along with accurate radio link
estimation, realistic pathloss and enhanced channel models
are proposed. Specific intra and inter BAN channel models
are utilised which take into account the spatial and temporal
dependencies of the WBAN channel.
Second: The scheduled access and CSMA/CA MAC protocols
are implemented which provide the foundation for coexistence
strategies to be compared. We implemented modified, simpler
and more efficient versions of the coexistence schemes in
comparison to IEEE 802.15.6 standard. Two non-collaborative
(i.e., time shared,channel hopping) and one implicit
collaborative (i.e., carrier sense multiple access/collision
avoidance (CSMA/CA)) schemes are compared. Time shared
mechanism is implemented as a simplified version of the
beacon shifting coexistence scheme (proposed in the standard)
since it does not requires to maintain complex beacon shifting
sequence. For the case of channel hopping technique a random
channel selection method is adapted. Further, a modified
and simpler IEEE 802.15.6 compliant CSMA/CA based
implicit collaborative coexistence strategy is implemented and
evaluated.
Third: As the reliability and quality-of-service are considered
as key requirements for most of the WBAN applications,
therefore, the performance of the IEEE 802.15.6 MAC
protocols and coexistence strategies are evaluated for narrow
band transmission in terms of packet error rate, packet delivery
ratio (PDR), packet latency and energy consumption under
varying number of BANs, data payloads, different frequency
bands, modulation schemes, data rates, transmission powers.
The rest of the paper is organised as follows. After the
introduction, related works is presented in Section 2 follows
by the overview of IEEE 802.15.6 standard in Section 3. We
present our proposed system models in Section 4, whereas
the performance evaluation of the coexistence schemes are
presented in Section 5. The paper ends with a conclusion and
the future works.
2 State-of-the-art
Generally the interference mitigation is classified into
collaborative and non-collaborative coexistence techniques.
In collaborative methods multiple nodes interact with each
other to manage coexistence, whereas, in non-collaborative
multiple nodes manage coexistence without any interaction.
The initial research studies on WBAN interference had major
Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference 3
emphasis on the adjacent channel interference mainly due
IEEE 802.11, IEEE 802.15.4 standards. It is clear from the
previous research works such as Martelli and Verdone (2012),
Thaier et al. (2014) and Jie and Smith (2013), that there
is a dominant interference from other networks in WBAN.
These approaches of interference analysis are only enough
for intra-BAN communication. However, with an advent of
body-to-body communications, inter-BAN interference (i.e.,
co-channel interference caused by multiple co-located bodies
operating with the same standard) and its mitigation is an
emerging problem.
Merely a few studies targeted this issue, for example,
Davenport et al. (2009) focused the study on the measurements
of the coupling between 10 bodies in a room at (2400-to-
2500) MHz. An average pathloss of –67.9 dB and standard
deviation of 5 dB was observed. These bodies were separated
by 1-to-5 m in hospital environment. Mucchi and Carpini
(2014) propose an interference model based on real
measurements carried out in the emergency ward of a modern
city hospital. The measurements are used to derive the main
parameters (first and second order statistics) of the probability
density function of the aggregate interference, finally the best
fitting distributions is derived for each frequency and location.
For dense co-existing WBANs, Wang and Cai (2011)
proposed geometrical probability distribution model. The
model approximate the total inter-cell interference through
gamma distribution which is validated by the simulation
results. Although the measurements conducted and the
interference models proposed in Davenport et al. (2009) and
Mucchi and Carpini (2014) are interesting to characterise
the co-channel interference. However, these studies are
limited due to, static-case (i.e., without any mobility
considerations), neither any coexistence method is evaluated
and the considered performance metric is only limited to PDR,
whereas the impact on the energy efficiency and delay are not
addressed.
Three co-located WBANs were configured to operate
at different transmission power levels, with chirp and duty
cycling sampling receivers in Dotlic (2011). The results
showed that under high traffic density the chirp receiver is
more immune to interference than the sampling receiver where
the PDR was observed around 99%for up to 10 co-located
bodies. Further, Hernandez and Mucchi (2014) present the
coexistence of the medical BANs based on the IEEE 802.15.6
standard using ultra wide band (UWB) physical layer. The
above mentioned studies are targeted to operate at UWB
spectrum, whereas, the impact of interference in narrow band
is much more stronger and evident (Chiani and Giorgetti,
2009), and therefore, proper coexistence techniques and their
evaluation for the narrow band spectrum is important.
More recently in Alasti et al. (2014), the authors addressed
the issue of co-channel interference between co-located
multiple BANs. Two uncoordinated approaches are presented,
first, a semi-random strategy is used to re-allocate the slots in
TDMA mode. Whereas, in the second approach, a minimum
interference slot assignment algorithm is selected instead of
randomly assigning the slot. These proposed approaches are
good starting point for co-channel interference evaluation,
however, they are limited due to number of un-realistic
assumptions such as ideal radio-links, mobility and channel
variations, further none of the coexistence schemes proposed
in the IEEE 802.15.6 standard are considered.
In this context, Movassaghi et al. (2013) presented the
challenges of deploying multiple WBANs in close vicinity
to each other and the interference avoidance and reduction
techniques are proposed. Further, the initial results of QoS
based preemptive priority scheduler (which is used to address
the issue of inter-BAN interference) is presented in Jamthe
et al. (2014). The variable traffic priority patterns are used to
control the traffic flow. However, the actual algorithm is only
verified by using two WBAN with very limited interference
impact and again none of the co-existence strategies are
recommended or evaluated.
With reference to WBAN interference mitigation,
IEEE 802.15.6 standard has proposed several methods
for coexistence. These include, beacon shifting,channel
hopping as dynamic coexistence whereas, active superframe
interleaving is a static scheme (IEEE 802.15.6, 2012). In
this paper, our emphasis is on dynamic coexistence strategies
due to our application and corresponding mobility context
(Hamida et al., 2014; Alam and Hamida, 2014a, 2014b). For
the coexistence using beacon shifting, the coordinator of each
BAN can adapt a different beacon shifting pseudo random
sequence to avoid the interference. Channel hopping technique
is valid only for narrow-band (NB) in which a coordinator
choose a polynomial based channel hopping sequence to avoid
interference on the same channel. More details on the channel
separation and exact calculation of channel hop can be found
in Section 3.1.2.
Table 1 summarise the main features and limitations of the
existing studies. It is evident that the IEEE 802.15.6 standard
proposed coexistence strategies for the narrow band are not
evaluated in any related or previous works. In addition, most of
the studies on inter-BAN interference lack dynamic mobility.
Therefore, to the best of our knowledge, the performance of the
IEEE 802.15.6 coexistence methods in particular with inter-
BANs context is yet to be evaluated. Further, all the above
methods discussed are based on non-collaborative approaches
and rely on pre-defined strategies. Hence, in this paper we
will also analyse the impact of implicit collaborative technique
using IEEE 802.15.6 compliant CSMA/CA method. This can
be considered as an option in which nodes do not explicitly
share any specific information to each other though the
interference can be minimised through only proper channel
sensing before transmission.
3 Overview of IEEE 802.15.6 standard
The IEEE 802.15.6 Standard was formally released in May
2012, specifically targeted for WBAN. A comprehensive
comparative study among various standards typically used for
WBAN can be found in Alam and Hamida (2014b). The IEEE
802.15.6 standard has proposed three different alternatives for
the PHY layer based on the specific applications and their
requirements, including human body communications (HBC),
narrowband (NB) PHY and ultra wideband (UWB) PHY as
shown in Figure 1. Below relevant and key features of the
4M.M. Alam and E.B Hamida
Table 1 Pros and cons of the existing state-of-the-art works related to the performance evaluation of the coexistence strategies for the BBN
using IEEE 802.15.6 standard
Co-channel
(Body-to- IEEE 802.15.6
body)Channel coexistence Mobility Operating Performance Evaluation
Ref. interference models evaluated? pattern bands metrics method
Martelli and Verdone (2012) No IEEE 802.15.6 No NA Narrow SINR, PLR, Numerical
band delay, energy
Jie and Smith (2013) Yes NA No NA Narrow SINR, PLR, Numerical +
band delay Matlab
Simulations
Davenport et al. (2009) Yes NA No Static Narrow PLR Measurements +
band NS2 Simulator
Wang and Cai (2011) Yes NA No NA NA SINR Numerical
Dotlic (2011) Yes IEEE 802.15.6 No NA Ultra wide PLR Numerical +
band Simulation
Alasti et al. (2014) Yes NA No NA Narrow Numerical +
band Simulation
Jamthe et al. (2014) Yes NA No NA Ultra wide SNR, BER, OMNeT++
band EbNo Simulator
Ref.: References; PLR: packet loss rate; NA: not applicable/considered.
PHY and MAC layers are highlighted within the context of
this paper.
Figure 1 Radio frequency spectrum for WBAN communications
in IEEE 802.15.6 standard (see online version
for colours)
3.1 IEEE 802.15.6 MAC and coexistence strategies
MAC layer plays a pivotal role to not only effectively
coordinate and communicate but also to optimise the energy
consumption, quality of service and reliability of the system.
In IEEE 802.15.6 standard multiple MAC protocols are
recommended as guidelines for channel access along with
several coexistence schemes. Below an overview of the
important features is presented.
3.1.1 MAC protocols
In classical healthcare WBAN systems, time division multiple
access (TDMA) based medium access control is most often
considered. Every sensor node has a dedicated slot to transfer
its data to the other sensors or coordinator. Moreover, works
such as Marinkovic et al. (2009) and Omeni and Toumazou
(2008) can further help to optimise the slot scheduling based on
the traffic load. Historically, limited attention has been given
to CSMA/CA, however, very-low duty cycle CSMA/CA based
protocols such as Alam et al. (2012) seems very attractive. The
IEEE 802.15.6 standard provided a great flexibility to adapt the
medium access according to the specific users requirements.
IEEE 802.15.6 MAC can be implemented through random
access (i.e., CSMA/CA, Aloha, Slotted Aloha, improvised
access (i.e., polling and posting) and scheduled access (i.e.,
TDMA) mechanisms. The MAC layer can operate in three
different modes, i.e., beacon mode with superframe boundary,
beacon mode without superframe boundary and non-beacon
mode without superframe boundary. In beacon mode with
superframe boundary, the higher priority and emergency
data transfer can execute in exclusive access phase (EAP)
including both EAP1 and EAP2. For regular non emergency
traffic two random access phase (i.e., RAP1 and RAP2) or
contention access phase (CAP) can be considered. CAP, EAP
and RAP can use only CSMA/CA, or aloha, or slotted aloha
channel access schemes. Whereas, managed access phase
(MAP) can be implemented through either scheduled access
or improvised access as shown in Figure 2.
Figure 2 Beacon mode with superframe boundary structure. EAP,
RAP and CAP phases can be implemented through
random access mechanisms (i.e., CSMA/CA, aloha and
slotted aloha), whereas, MAP phase can be implemented
through improvised and scheduled access
Source: IEEE 802.15.6 (2012)
3.1.2 Coexistence strategies
The IEEE 802.15.6 standard proposed three techniques for
coexistence as briefly mentioned earlier in Section 2.
•Beacon shifting technique is important to avoid the
collisions of the beacons (from multiple BANs) being
Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference 5
used at the start of every superframe. The format of
beacon shifting is composed of
a beacon shifting sequence index (BSSI)
b beacon shifting sequence phase (BSSP).
The BSSP is incremented by 1 in every superframe
through modulo 16 with reference to the previous value.
Whereas, the BSSI is computed by having a different
pseudo random sequence at each BAN coordinator
which helps to randomise the start of the superframe.
The approach is targeted for static network (i.e., for
fixed number of BANs). The IEEE 802.15.6 standard
proposed beacon shifting coexistence scheme is much
more complex because it implements BSSI and BSSP
(IEEE 802.15.6, 2012). This is achieved through
complex pseudo random sequence generation to control
the beacon transmission pattern among multiple BANs
in a timely shared manner. However, beacon shifting
can be achieved from many ways as reported in
Seungku Kim and Eom (2012), IEEE 802.15.6 (2012)
and Thaier et al. (2014) etc. However, the purpose in
this study is to use the approach in a simpler and easier
way. In this paper, we adapted beacon shifting
technique as time-shared approach by knowing the
number of co-located BANs in much simpler way as
shown in Figure 3. This technique does not require to
manage any pseudo random sequence and is more
simple to implement especially under static network
where each superframe period is selected according to
number of BANs in the surroundings. In this approach,
during the active duration of one BAN, all the other
BANs will be in sleep mode and the body-to-body
interference can be avoided.1
•Channel hopping is another coexistence approach
proposed in IEEE 802.15.6 standard which can be
applied in scheduled access MAC. In this method the
coordinator, generate a channel hopping sequence based
on 16-bits Galois linear feedback shift register (LFSR)
with a generator polynomial function:
g(x) = X16 +X14 +X13 +X11 + 1. In channel
hoping technique, we used a random channel
mechanism with every channel has equal probability to
be selected. Each BAN operate in one fixed channel for
its intra-BAN communication. In narrow band
spectrum, there are 79 channels which can be used
within the frequency range of [2400 −2483.5] MHz,
having centre frequency as fc = 2402.00+
1.00 ×nc(MHz), where nc = 0,1, . . . , 77,78.
•Finally we have implemented CSMA/CA medium
access method (an example is shown in Figure 4), which
can be considered as an implicit collaborative technique
for coexistence. In CSMA/CA access technique every
node sense the channel before transmitting the data and
this sensing of channel occupancy can act as implicit
information which can help to minimise the inter-BAN
interference. Similar concept has also been adapted in
Seungku Kim and Eom (2012), where authors have
used CSMA/CA based channel sensing and back-off
concept for beacon interval shifting to avoid wakeup
collisions and interference.
Figure 3 Time-shared coexistence strategy for wireless
body-to-body networks
Figure 4 CSMA/CA and backoff mechanism of IEEE 802.15.6
standard
Source: IEEE 802.15.6 (2012)
3.2 Radio link and PHY layer
In order to correctly model the interference, one common
way consists in replacing the signal-to-noise-ratio (SNR)
(Alam and Hamida, 2014b) by a signal-to-interference-plus-
noise-ratio (SINR). Sources of interference include Intra-BAN
and/or Inter-BAN nodes operating in the same frequency band,
i.e., co-channel interference, or in different frequencies bands,
i.e., adjacent channel interference. The proper calculation of
the SINR value for a given radio link, between the two nodes i
(transmitter) and j(receiver), requires the knowledge of all the
signals which are currently and concurrently being received
at the receiver j. At any time instant t, the current SINR value
can be computed as follows (Xiong, 2006):
SINRt
ij [mW ] = PT X
i·P L(dij )
Nj+∑k̸=i,j αik ·PT X
k·P L(dkj ),(1)
6M.M. Alam and E.B Hamida
where PT X
istands for the transmission power of the
transmitter node i;P L(dij )is the distance dependent pathloss
between the node iand node j;Njis the power of the thermal
background noise at the receiver node j;αik the rejection
factor between the channels associated with the nodes iand
k(αik = 1 in this work); PT X
kis the transmission power of
the interfering node k. We consider a full interference model
where any node kcan potentially generate interference at
a given receiver jas shown in Figure 5(a). For example,
considering a given transmission between two nodes iand j,
since other transmissions can also happen concurrently (within
the same frequency band), thus the interference and noise
level at the receiver jcan vary during the time, as shown in
Figure 5(b).
Finally, in order to determine if a given transmission was
successful (despite of interference), it is important to evaluate
the corresponding packet-error-rate (PER), as: PERij = 1 −
(1 −BERt
ij )n; where nis the packet length in bits, and BERt
ij
is the corresponding bit-error-rate (BER) which is computed
based on the current SINR level at time t(i.e., SIN Rt
ij ), and
the considered physical layer characteristics (e.g., data rates
and modulation schema), as follows:
BERt
ij ={0.5×e−Eb/No DBPSK
Q(√4×Eb/No ×sin( π
4×√2)) DQPSK,(2)
where Eb/No is the energy per bit to noise power spectral
density ratio in dBm which is computed based on the
current SINR level, as: Eb/No[dB] = SINRt
ij [dB] + 10 ×
log10(BW/R); where BW is the bandwidth in Hz, and Ris
the data rate in bps.
Figure 5 Interference modelling in BANs and BBNs: (a)
interference overview (i: transmitter, j: receiver, and k:
interfering nodes) and (b) interference and noise level at
a given receiving node (see online version for colours)
(a)
(b)
4 Proposed system models
Wireless body-to-body networks (BBN) is relatively a new
dimension of WBAN in which multiple bodies interact and
share certain information. Figure 6, to illustrate an example,
it shows an overview of the on-body sensor locations and
body-to-body interfering links. The interfering links are just
to illustrate the concept, in reality all the on-body nodes
contribute towards the interference on all the BANs. It is
important to note that, during the dynamic mobility patterns
(i.e., walking, sitting, standing and running), the link types
keeps changing between the coordinator (node 1) and the other
nodes for example located at hands, wrists, fingers, legs, foot,
knees etc. Depending upon the specific body posture during the
mobility the time varying links vary from line-of-sight (LOS)
to non line-of-sight (NLOS). This specific link type variations
in the bio mechanical modelling are calculated as follows.
If the two links are intersected by the body shadowing, it is
considered as NLOS link, whereas, if the link is not intersected
it is considered as LOS. For example during the walking
pattern, a link between left wrist and waist (coordinator) will
be intersected by the back and torso if the wrist position is in the
back of the body. In addition, we also compute the penetration
distance to calculate the exact pathloss factor for the NLOS
links as mentioned in Alam and Hamida (2014a).
Figure 6 Intra-BAN and inter-BAN networks and interference
scenarios (see online version for colours)
In this section, we will explain various cross-layer components
of the BBN system which has a direct impact on the
performance evaluation of BBN. The accurate mobility, path-
loss and channel models are essential to get more insight into
the performance of wireless communication stacks under real
deployment and operating assumptions (Alam and Hamida,
2014b; Hamida et al., 2009; Hamida and Chelius, 2010).
This is especially true in the context of BANs and BBNs,
whose radio channels might undergo harsh multi-path fast
fading and time-varying slow fading due to human body
shadowing effects (Hamida et al., 2011). To that end, we
consider in this work the Intra-BAN biomechanical mobility
and radio link models which we recently introduced in
Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference 7
Alam and Hamida (2014b), and we extend these to handle the
inter-BANs case.
In this regards, a bio vision hierarchical (BVH) file is
utilised which extracts the skeleton to obtain the markers
locations/positions. The BVH data file consist of two parts:
skeleton part and motion data. The skeleton part of BVH
described the hierarchy and initial pose of the skeleton. The
motion part contains the rotation and translation of skeleton
joints. The root of BVH skeleton is always zero. All other non-
root joints has three Euler angle rotation data of joints. Then we
need to calculate the rotation matrix and translation matrix of
every joint relative to its parent joint. More details can be found
in Meredith and Maddock (2001) and Razzaq et al. (2015).
The above biomechanical modelling and transformation helps
to introduces space and time variations in the IEEE 802.15.6
proposed channel models to make them more dynamic and
realistic.
4.1 Intra/inter-BANs biomechanical mobility
modelling
Modelling the mobility and posture behaviours of real
human bodies is a complex task. One solution consists in
exploiting real-time motion capture data and to couple them
with geometrical transformation and analysis techniques to
properly investigate the performance of BANs and BBNs
under different mobility scenarios (e.g., walking, running,
exercising, etc.). As shown in Figure 7, our proposed Intra and
Inter-BANs mobility modelling works based on six main steps:
Step 1: real motion capture measurements, which contain the
actual human mobility traces according to different mobility
scenarios (e.g., walking, running, etc.), are extracted into our
Matlab mobility modelling tool (Alam and Hamida, 2014b);
Step 2: the complete human body skeleton is captured from
the input motion capture measurements and which consists
in a set of markers (i.e., the joints between the different
parts of the body) and segments (i.e., the body parts). These
markers provide the dynamic distances among all the locations
over time. An example of human body skeleton is shown
in Figure 7; Step 3: In order to properly model the human
body parts (e.g., arms, torso, head, legs, etc.), cylinders are
applied around the different segments of the human body
skeleton. This is an important step to take into account for
the body shadowing effects on the performance of radio links;
which can either be in direct LOS or NLOS condition; Step
4: geographical transformations are then applied in order to
scale the dimensions into a normal human height and width.
Moreover, the determined human body is replicated into a
configurable numbers of other human bodies in order to enable
the simulation of complex and highly dynamic inter-BANs
scenarios; Step 5: geometrical analysis is thus applied in order
to determine the types of all the available links (e.g., LOS
or NLOS, Intra or Inter BANs) and during the whole trace
duration. Exact link types during mobility are evaluated by
checking the intersection of the cylinders between all the links.
If a link intersects with a cylinder, then the link is declared as
NLOS, otherwise it is in LOS state; Step 6: finally, space-time
varying links and mobility traces are generated and stored in
an external file, which ultimately can be fed into the WSNet
packet-oriented simulation environment (Hamida et al., 2009)
to enable the realistic performance evaluation of high level
communication protocols.
4.2 Intra-BAN and inter-BANs channel models
Once the space-time varying links and mobility traces are
properly generated for a given mobility scenario, channel
models can be applied in order to assess the performance
of radio-links. The IEEE 802.15.6 standard has already
proposed various channel models, including the CM3 (body
surface to body surface) and CM4 (body surface to external)
models. However, it was shown that these models provide
only basic distance-based path-loss without any time varying
effects and correlations features (Alam and Hamida, 2014b).
To that end, consider two on-body nodes i(transmitter) and j
(receiver) located on the same BAN, the corresponding time-
varying path-loss variation, P L(dij), is computed based on
the enhanced IEEE 802.15.6 path-loss models as proposed
in Alam and Hamida (2014b). For example, considering the
CM3-B model, the path-loss is computed as: P L(dij )[dB] =
a·log10(dij ) + b+N; where dij refers to the distance
between the nodes iand j,aand bare the coefficients
of the linear fitting, and Nis the normally distributed
random variable with standard deviation which have different
values based on the frequency bands and the environment
(Alam and Hamida, 2014b). However, in case of a radio
link of type inter-BAN, i.e., the two nodes iand jare
located on different BANs, the corresponding path-loss is
computed as WiserBAN (2011): PL(dij ) = G(d0) + 10 ·n·
log10(dij /d0) + F; where G(d0)is the channel gain at the
reference distance, d0is the reference distance which is equal
to 1m,nis the path-loss exponent factor, and Fis the
fading. Typical values (validated experimentally) for these
components are provided in WiserBAN (2011).
Figure 7 Joint biomechanical, group mobility and radio link
modelling for BANs and BBNs (see online version
for colours)
5 Performance evaluation
In this section, body-to-body (B2B) communication is
evaluated under the impact of inter-BANs interference and
coexistence strategies presented earlier in Section 3.1.2
8M.M. Alam and E.B Hamida
are compared. Energy consumption, latency and PRR are
considered as main performance metrics.
5.1 Simulations setup
A packet-oriented network simulator called WSNet (Hamida
et al., 2009), is used as shown in Figure 7. It contains
various models for wireless sensor networks, wireless local
area network and ad hoc networks. However, previously it
does not contain WBAN specific modules. Therefore, we have
enhanced the simulator (with focus on IEEE 802.15.6 standard
compliance) to accurately model wearable networks (i.e., both
intra and inter BAN) using enhanced channel models, accurate
radio-link and mobility models. Following are the brief details
of the simulation development.
•Application layer: At the application layer, we consider
five human bodies, each of them having one
coordinating node and 12 sensor nodes as shown in
Figure 6. Five co-located BANs are moving altogether
within a distance of 3 m apart which is in compliant
with the IEEE 802.15.6 standard in which up to 10
BANs can co-locate in volume of (6×6×6)m3. A
constant bit rate (CBR) data generation application is
used to generate a traffic at a rate of 100 ms with
varying payloads sizes (i.e., 2, 16, 64, 128 and 256
bytes) as mentioned in Table 2.
•MAC layer:Protocols and coexistence schemes: From
the application layer, every packet is parsed into the
MAC layer. Two protocols are developed at the MAC
level to have base-line MAC protocols for two
independent evaluations of the coexistence schemes.
First, CSMA/CA with priorities using a state machine is
implemented. The back-off mechanism is followed
exactly as proposed in IEEE 802.15.6 standard (i.e., for
every odd back-off the contention window size is
doubled), where, maximum back-off and
re-transmissions are set as 5 and 4 respectively.
Further, three acknowledgment policies are developed.
Second, the scheduled access scheme is implemented
with a superframe architecture which includes a beacon
period, each node have one guaranteed time slot
(which is optimised based on the actual payload
and all the overheads of the MAC and PHY layers).
Specific timings details of the MAC configurations in
the scheduled access scheme can be found in our
previous work (Alam and Hamida, 2015). We have
explained about the two MAC protocols because
both of them are simulated and used separately
during coexistence evaluation. A reference scenario,
time-shared and random channel coexistence are
evaluated based on TDMA (scheduled access
MAC protocol), whereas, CSMA/CA scheme is
considered and used as implicit collaborative
coexistence scheme.
These coexistence schemes are explained as follows:
1Reference scenario (RS): The reference scenario is
simulated using scheduled access MAC in which
every node inside a BAN has a dedicated time slot
to transmit its data to the dedicated on body
coordinator. The ‘RS’ is a case which does not
use any coexistence scheme such as time shared
or random channel hopping, however it is
considered to compare and show the impact of
inter-BAN interference. Concerning the
interference, for the case of only Intra-BAN,
since every node has a dedicated time slot so,
intra-BAN interference and collisions at a single
BAN is minimal. Whereas, for the inter-BAN if
proper coexistence scheme is not applied the
interference can impact the performance because
different co-located BANs are operating on the
same channel.
2Time shared (TS): It is a non-collaborative
approach, more details are available in
Section 3.1.2.
3Random channel (RC): It is also a
non-collaborative coexistence technique as detailed
in Section 3.1.2.
4Carrier sense multiple access/collision avoidance
(CC): It is an implicit collaborative coexistence
approach with more details are provided in
Section 3.1.2.
All the schemes are comprehensively compared under
detailed MAC PHY configurations.
•PHY layer: Four narrow band PHY configurations are
considered (i.e., 900 MHz with lowest and highest rates
and 2450 MHz with lowest and highest rates) as
mentioned in Table 2. Accurate radio-link models using
BER, PER, SINR models along with DBPSK and
DQPSK modulation schemes as described in
Section 3.2 (i.e., by using equations (1) and (2)).
Finally, the real-time motion captured-based inter-BAN
mobility traces are imported in WSNet which provide
accurate space and time variations.
The simulation setup is based on version 3.0, which is
an up-to-date version of WSNet. By using all the above
explained models, extensive parameters and configuration, the
WSNet’s XML configuration files (i.e., xml) are generated
for simulation. The simulations are repeated for 50 iterations
and 95% confidence interval is considered. The simulations
are executed for number of scenarios including walking,
sitting/standing and running for dynamic mobility patterns
for a duration of 63 s. The detailed simulation parameters are
summarised in Table 2.
5.2 Simulation results
In this section, the performance of the Inter-BAN
Communication using coexistence schemes and MAC
protocols are investigated and compared under the simulation
environment explained in previous section. As there are many
set of possible combinations with varying parameters, the
Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference 9
Figure 8 Average packet reception ratio of three coexistence schemes and one reference scenario at varying transmit power at 900 MHz and
2450 MHz without ACK under highest payloads (see online version for colours)
(a) (b)
(c) (d)
Table 2 List of simulations parameters and corresponding values
Protocol stack Configurations and parameters
Frequency (MHz)2450 900
PHY. layer Data rates (Kbps) 121.4–971.4 101.2–404.8
(Narrow TX. Power (dBm) 0, –10, –20, –25 0, –10, –20, –25
Band) TX. current consumption (mA) 17.4, 11, 9.2, 8 15, 9, 7.2, 6
RX. current consumption (mA) 19.7 23.5
Sleep. current consumption (mA) 0.9 0.0005
Sensitivity (dBm) –92 to –83 –94 to –87
Channel models (Alam and Hamida, 2014b) CM3-B-Enhanced CM3-B-Enhanced
Channel bandwidth (KHz) 1000 400
Protocols Scheduled access (MAP)CSMA/CA
MAC layer ACK policies Immediate, BLOCK, none Immediate, BLOCK, none
ACK packet size (Bytes) 5 5
Beacon packet size (Bytes) 21 0
Re-transmission limit 0 4
Priority-level 0 2
APP. layer Payloads (Bytes) 2, 16, 64, 128, 256 2, 16, 64, 128, 256
Number of BANs 1-to-5 1-to-5
results presented in this section are confined with highest
payload, lowest and highest transmit power unless specified
otherwise.
Figure 8 shows the average PRR of Reference Scenario,
Random Channel, Time Shared and CSMA/CA for varying
number of BANs. First of all, it is important to note that the
PRR of Reference Scenario starts decreasing sharply as the
number of BANs increases which reflect clearly that in the
context of body-to-body communication, proper coexistence
mechanism is very crucial. Focusing on to the coexistence
schemes, in general, both Random Channel and Time Shared
schemes perform very well and achieves more than 99% PRR.
The PRR of CSMA/CA continuously decreases with an
increase in number of BANs while using 256 bytes of payload
even with the high transmit power. This is expected and
mainly due to reason that with every increase in BANs
twelve nodes are added which contend on the same channel
to transmit their data packets. Most of the nodes keeps on
waiting (in the back-off state) since the channel is occupied
by one of the node which results in lower average PRR. Even
after the back-off timer expired, most of the nodes results
in collisions and consequently the average PRR continuously
decreases with an increase in number of BANs. Therefore
under most of the configurations, the average PRR do not
10 M.M. Alam and E.B Hamida
Figure 9 Average packet reception ratio of three coexistence schemes and one reference scenario at varying transmit power at 900 MHz and
2450 MHz without ACK under 16 bytes of payloads: (a) Modulation = DBPSK, Power = 0/–20 dBm and
(b) Modulation = DQPSK, Power = 0/–20 dBm (see online version for colours)
(a) (b)
Figure 10 Average energy consumption of three coexistence schemes and one reference scenario at varying transmit power at 900 MHz and
2450 MHz without ACK under highest payloads: (a) Modulation = DBPSK, Power = 0 dBm; (b) Modulation = DBPSK,
Power = –25 dBm; (c) Modulation = DQPSK, Power = 0 dBm and (d) Modulation = DQPSK, Power = –25 dBm (see online
version for colours)
(a) (b)
(c) (d)
satisfy 95% requirements mentioned in the standard (IEEE
802.15.6, 2012).
The CSMA/CA protocol is under performed with the
highest payload, however, with lowest payloads the achievable
PRR increases and reaches upto 90%, more specifically
by using higher transmit power, high data rate, with both
900 MHz and 2450 MHz configurations. This can be seen in
Figure 9, where PRR of the CSMA/CA is presented for 16 bytes
of payload with high data rates at 900 MHz and 2450 MHz
operating frequencies. Moreover, it can be seen that CSMA/CA
performs much better even with an increase in number of
BANs. At 2450 MHz, the average PRR is about 95% and for
the case of 900 MHz it degrades maximum upto 90% for 5
BANs.
Figure 10 shows the average energy consumption of
the reference scenario, Random Channel, Time Shared
and CSMA/CA for varying number of BANs. The energy
consumption for each transmitted packet is calculated as
follows,
Epacket =Tpacket ×3Volts ×ImA,(3)
where, Tpacket is the physical-layer protocol data unit (PPDU)
duration in ms which is based on the effective packet length
(including all the PHY and MAC headers (Alam and Hamida,
2014a)) and is obtained from real propagation time in the
simulator, 3Volts is the considered battery voltage and ImA
is the current consumption which is used from the widely
used radio transceiver chip i.e., Texas Instrument’s cc2420
for 2450 MHz, whereas, for 900 MHz, AMI Semiconductor’s
transceiver chip amis52100 (A.N.S. Inc., 2014) is used. The
current consumption details of both transceivers are provided
in Table 2.
Generally CSMA/CA consumes more energy than other
coexistence schemes as it remains in the active state all the
Performance evaluation of IEEE 802.15.6-based WBANs under co-channel interference 11
Figure 11 Average latency of three coexistence schemes and one reference scenario at varying transmit power at 900 MHz and 2450 MHz
without ACK under highest payloads: (a) Modulation = DBPSK, Power = 0 dBm; (b) Modulation = DBPSK, Power = –25 dBm;
(c) Modulation = DQPSK, Power = 0 dBm and (d) Modulation = DQPSK, Power = –25 dBm (see online version for colours)
(a) (b)
(c) (d)
Figure 12 Average latency of three coexistence schemes and one reference scenario at varying transmit power at 900 MHz and 2450 MHz
without ACK under 16 bytes payload: (a) Modulation = DQPSK, Power = 0/–20 dBm and (b) Modulation = DBPSK,
Power = –25 dBm (see online version for colours)
(a) (b)
time and does not follow any duty cycling optimisation.
However, an important point to note is that CSMA/CA starts
consuming less energy with an increase in number of BANs
especially for 900 MHz configurations. One of the reason is
that, CSMA/CA protocol remains in sensing or receive state
most of time as the nodes are not able to transmit their data
due to channel interference, congestion and unavailability, and
since the current consumption level (of the considered radio
chips operating at 900 MHz) in the receive state (i.e., 23.5 mA)
is higher than in the transmit state (i.e., 15 mA). Therefore,
the energy consumption reduces with increased number of
BANs as shown in Figure 10(a) and (b). Further, this is very
much coincides with the results presented in Figure 8(a) and
(b), where packet reception also decreases with an increase
in number of BANs. Now, for the case of 2450 MHz, energy
consumption remain almost flat (as can be seen in Figure 10(c)
and (d) with an increase in number of BANs and even
though the PRR results of 2450 MHz are similar to that of
900 MHz. This is due to the fact that, in TI cc2420 radio
chip the current levels for both receive and transmit state are
very similar and therefore energy consumption remains almost
same with an increase in number of BANs or with reduced
PRR.
The energy consumption results of the Time Shared
scheme in all the configurations have very similar pattern, i.e.,
with the increased number of BANs the energy consumption
increases which means more number of BANs transmit
and receive more packets and hence consume more energy.
Whereas, Random Channel consumes minimum energy under
all the configurations mainly because it has very high
percentage of PRR and therefore can be considered as energy
efficient coexistence scheme.
With regards to the performance of the delay in various
coexistence schemes, Figure 11 shows the results under four
configurations. Definitely CSMA/CA is the best approach
under all scenarios as it meets both medical and non-medical
constraints of the IEEE 802.15.6 standard. Whereas, both Time
Shared and Random Channel suffers in achieving the required
delay constraints. Only with the configuration when operating
at 2450 MHz, high data rate and maximum transmit power,
12 M.M. Alam and E.B Hamida
with five BANs, both schemes are able to meet the lowest time
constraint (i.e., 125 ms). To analyse the impact of transmit
power, higher power has relatively lower delay in Random
Channel, though it has limited impact for the case of Time
Shared.
As we analysed the performance of CSMA/CA with
lower payloads and found that it achieves much better PRR.
Similarly, we also analyse the performance of both Time
Shared and Random Channel at 16 bytes of payload and the
results are presented in Figure 12. It can be seen that with
16 bytes, 900 MHz and highest rate only Random Channel
techniques achieves the minimum delay requirements of both
medical (125 ms) and non-medical signals (250 ms) according
to IEEE 802.15.6 standard as shown in Figure 12(a). Whereas
at 2450 MHz, low rate and 16 bytes, it is able to satisfy only
non-medical signals requirements.
To summarise, definitely both Time Shared and Random
Channel techniques are very reliable as they achieve better
performance in body-to-body communication. Both schemes
are able to achieve high packet reception and also consumes
relatively much lower energy, whereas, with regards to
delay requirements both of them only marginally able to
satisfy the IEEE 802.15.6 standard requirements. On the
other hand, CSMA/CA based approach performs very well
and meet the delay constraints in all configurations. It has
relatively three to four times lower energy efficiency in
comparison to both Time Shared and Random Channel.
However, the performance ofCSMA/CA based system in terms
of successful PDR is very low. So to conclude, there is a
trade-off between three coexistence schemes depending upon
the specific application and its design requirements a suitable
schemes can be selected.
6 Conclusions
Being the benchmark standard for WBAN, accurate
performance evaluation of IEEE 802.15.6 standard is
extremely important for the emerging novel protocols
and algorithms for body area networks. Concerning the
performance evaluation platform, we are using a network
simulator called WSNet. The performance evaluation of
IEEE 802.15.6 standard is limited to either numerical or
simulations based approaches mainly due to unavailability of
the IEEE 802.15.6 standard compliant hardware platform. It
is anticipated that by the end of 2015 or early 2016, we may
have few radio transceivers available (operating at sub-giga
or narrow band spectrums), compliant to the standard. In this
realm, we have developed the IEEE 802.15.6 compliant open-
source simulator (as an option) for the WBAN community
which is going to be first of its kind since the existing WBAN
simulator (i.e., OMNet++) is limited only to the WBAN
channel models and currently it does not contain PHY and
MAC models of the IEEE 802.15.6 standard.
Currently, closed-form MAC layer evaluation are available
without taking into account the impact of realistic channel
models (i.e., no space and time variations). Moreover,
limited mobility scenarios (which means channel and
radio-links are consistently static), and importantly,
without considering the impact of interference especially
for inter-body communication. This paper provides
a significant addition to the current state of the art
performance evaluation of IEEE 802.15.6 MAC layer by
taking into account all the above mentioned limitations.
Extensive set of parameters are utilised for a comprehensive
comparisons of two non-collaborative and one implicit
collaborative coexistence schemes. It can be seen that,
both Time Shared and Random Channel schemes are
better when energy efficiency and successful PRRs are the
desired performance metrics. While CSMA/CA is best for
the delay sensitive applications. In the future, we would like
to continue our study for the UWB spectrum especially for
60 GHz as it is expected to be used for WBAN in coming
years.
Acknowledgements
This publication was made possible by NPRP grant #[6-1508-
2-616] from the Qatar National Research Fund (a Member of
Qatar Foundation). The statements made herein are solely the
responsibility of the authors.
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Note
1Please note that, time synchronisation between multiple BANs at
the PHY layer is another problem which is beyond the scope of this
paper, however, synchronisation at the MAC layer is achieved by
using Beacon and acknowledgment (ACK) Frames.
