Performance analysis of DQPSK and DBPSK [602735]

Performance analysis of DQPSK and DBPSK
modulation schemes f or a scheduled access phase
based Wireless Body Area Network
Marwa BOUMAIZ1, M. EL GHAZI1, A. BOUAYAD2, M. FATTAH3, S. MAZER1, M. EL BEKKALI1
1Laboratoire de Transmission et T raitement de l’Inform ation, USMBA, Fez, Maroc
2 ENSA, UIT, Kenitra
3 FPE, UMI, Meknès
[anonimizat] , [anonimizat] , mazersaid@gma il.com , [anonimizat]
Abstract — The recent development of electronics and
technological advances in wireless networks have led to the
development of miniaturized wireless sensors, that can be used in
the fiel d of remote healthcare patients monitoring. When
interconnected in a Wireless Body Area Network (WBAN) , these
tinny sensors, , can be positionned on or implanted inside the
human body to continuously monitor several physiological
parameters (temperature, b lood pressure, ECG, etc … ) of the
patient.
The purpose of this paper is to compare the impact of the
two modulation schemes specific to the NB physical layer at
2.4Ghz when the scheduled access is considered , for a WBAN
model consisting of 11 sensor nod es (one of which is the hub )
based on the IEEE 802.15.6 standard. The numerical study
focuses on three metrics: packet reception, latency, and node –
level energy consumption, and is performed using the Castalia
3.3 framework, based on the OMNeT ++ platform (4.6).
Castalia simulator supports the IEEE 802.15.6 standard,
which justifies the choice of its use in the simulations carried out.

Key words — Wireless Body Area Network (WBAN), IEEE
802.15.6, Differential Binary Phase Shift -Keying (DBPSK) ,
Differentia l Quadrature Phase Shift -Keying ( DQPSK),
Narrowband physical layer, 2.4Ghz , Castalia 3.3 , latency, packets
reception, energy efficiency.
I. INTRODUCTION
The very low power operation of a WBAN is crucial [1],
because the sensor nodes are generally self -powered, each with
an integrated battery. Furthermore, the transmission reliability
is another major requirement in a WBAN [2], especially for
medical applicatio ns that do not tolerate data loss [3].
Due to these key requirements and considerations, existing
wireless stan dards such as IEEE 802.15.1 Bluetooth, 15.4
Zigbee and 802.11 a / big WiFi are not sufficiently suitable to
provide appropriate solutions for a wid e range of WBAN
applications [4].
The IEEE 802.15.6_2012 standard, established specifically
for WBAN networks, defines thre e types of physical layers
(PHY) and a data link layer (MAC). The choice of each
physical layer (NarrowBand (NB), Ultra Wide Band (UWB) or
Human Body Communication (HBC)) depends on the desired
application.
The aim of our research is to propose an optimise d physical
layer setting for an on -body BAN solution, designed for remote patient monitoring of the usual physiological signs , based on
the IEEE 802.15.6 standard. Hence, this paper is limited to a
simulation study of the effect of Differential Binary Phas e Shift
Keying (DBPSK) and Differential Quadrature Phase Shift
Keying (DQPSK) modulations on the performance of the
standard when scheduled access is adopted, for the WBAN
model illustrated in the figure 1.
The rest of this paper is structured as follows, section II
describes the adopted WBAN model and t he configuration of
MAC, Radio and Energy modules under Castalia 3.3 software
[5]. Section III presents the simulation re sults of the effe cts of
the two modulation schemes on the performance of the
proposed WBAN model , in terms of packets reception, latency
and consumed energy in each node, when the scheduled access
is considered. and section IV concludes the paper.
II. THE PROPOSED WBAN MODEL
As shown in figure 1, the considered wireless body area
network consists of ten sensor nodes and a coordinator (hub),
placed on the su rface of the human body, in order to record the
known physiological parameters of a patient (ECG, blood
pressure, temperature…) and to send them back to a remote
healthcare center.

Figure 1. The proposed WBAN model design

A. On-body BAN channel modeling:
as mentioned in table 1, the IEEE 802.15.6 s tandard defines
four wireless channel m odels according to the node position
and the propagation scenario [6].
in the case of our study, all the nodes ar e positioned on the
body surface of the patient. We, therefore, choose the CM3 ( on
body – on body link) channel model, which mainly takes into
account the path loss and temporal variation characterization.
TABLE I. PROPOSED CHANNEL MODE LS IN THE IEEE 802.15.6 STAND ARD

1) Path loss modeling :
One of the most important aspects in wireless channel
modeling is the average path loss definition between the two
communicating nodes [7]. However, i n WBANs, the
shadowing caused by the human body should also be
considered [8], not only the frequency and the distance
separating the transmitting and receiving antennas [7]. Thus,
the path loss at a given distance can be statistically modeled by
the log -normal shadowing model, presented in equation (1).

(1)
Where :
 d: the measured distance on the perimeter of the
patient's body (between the antennas of the
transmitting and receiving sensors ),
 d0: a reference distance (d0 = 1 m)
 PL(d ) : the path loss (in dB) at a given distance d ,
 PL(d0 ) : the path loss (in dB) at a reference distance
d0.
 γ : the path loss exponent
 X: a Gaussian zero -mean random variable with
standard deviation.
The path loss modeling under Castalia 3. 3 is carried out in
an input file, called "pathlossMap" [5]. The calc ulated path loss
between the 11 nodes is presented in table 2 .
TABLE II. CALCULATED PATH LOSS BETWEEN NODES

2) Temporal variation modeling : In rapidly changing environments such as WBANs, power
distribution over time or so -called "time variation" is a very
important physical parameter in channel modeling [8]. To the
best of our knowledge, in literature, there is no single model
that de scribes the temporal variation. however, a general
modeling of this parameter is adopted [5]
B. Radio, MAC, and energy modules settings :
1) Radio module settings :
The parameters of the Radio, Mac and Ener gy modules ,
used in our simulations, are summarized in Tables 3 , 4 and 5
respectively .
TABLE III. THE ADOPTED RADIO MO DULE SETTINGS

Radio module parameters values
Data rate 1,024Kbps
modulation DiffQPSK
RX sensitivity −87dBm
Noise bandwidth 1MHz
Noisefloor −104dBm
Transimit power −10dBm
CCA time 1ms
CCA threshold -95
State switching times for:
Tx→Rx et Rx→Tx Temps 20μs
State switching times for :
Rx→Sleep, Tx →Sleep 0.194ms
State switching times for:
Sleep→Rx, Sleep →Tx 0.05ms
Power consumption of
transmission 3 mW

Power consumption of reception 3.1 mW
Power transition for :
Tx→Rx et du Rx →Tx 3 mW

Power trnsition for :
Sleep→Rx, Sleep →Tx ,
Rx→Sleep et TX →Sleep 1.5 mW

Idle mode power 0.05 mW
Frequency 2400 Mhz
RSSI symbols model 8
Collision model 2

2) MAC module settings
TABLE IV. THE ADOPTED MAC MODU LE SETTINGS
Mac module parameters values
isHub true for node 0, and
false for other nodes
beaconPeriodLength 32
RAP1Length 8
scheduledAccessLength 0
scheduledAccessPeriod définit 1
maxPacketTries 2
contentionSlotLength 0.36
pollingEnabled false
naivePollingScheme false
pTIFS 0.03
pTimeSleepToTX 0.2
phyLayerOverhead 6

0 1 2 3 4 5 6 7 8 9 10
0
*** 56 56.6
7 35 52.7
6 46.4
5 47.1
2 47.7
5 48.6
3 49.1
8 49.9
5
1 56
*** 46.4
5 56 57.3 59.3 59 59.5 59.8 60.8 60.4
5
2 56.6
7 46.4
5
*** 57.3 56 59.7 59.5 59.4 59.3 59.2 59.1
3 35 56 57.3
*** 55.2
8 48.0
5 48.5
5 48.9
1 49.3
1 49.7 50.1
4 52.7
6 57.3 56 55.2
8
*** 52.6
9 52.3
6 51.9
8 51.6
7 51.3 50.9
5 46.4
5 59.3 59.7 48.0
5 52.6
9
*** 22.4
5 29.6
7 33.9 36.9 39.2
2
6 47.1
2 59 59.5 48.5
5 52.3
6 22.4
5
*** 22.4
5 29.6
7 33.9 36.9
7 47.7
5 59.5 59.4 48.9
1 51.9
8 29.6
7 22.4
5
*** 22.4
5 29.6
7 33.9
8 48.6
3 59.8 59.3 49.3
1 59.6
7 33.9 29.6
7 22.4
5
*** 22.4
5 29.6
7
9 49.1
8 60.0
8 59.2 49.7 51.3 36.9 33.9 29.6
7 22.4
5
*** 22.4
5
10 49.9
5 60.4
5 59.1 50.1 50.9 39.2
2 36.9 33.9 29.6
7 22.4
5
***

3) Energy module settings :
TABLE V. THE ADOPTED ENERGY MODU LE SETTINGS

III. SIMULATION RESULTS
In this section we will investigate the performance analysis
of th e DBPSK and DQPSK modulations in terms of packet
reception, latency and energy consumption at each node, in the
Narrowband band at 2.4Ghz when scheduled access is
considered.
A. Packets reception
The total number of allocation intervals used in the beacon
period is 32 . If each node is provided with 3 slots reserved for
scheduled access , we end up with 30 slots allocated for the 10
nodes. The remaining two slots will be allocated using random
acces s.
Figure 2 shows the received packets per node (the hub)
according to the variati on of scheduled access phases ( 0 to 3)
for both DQPSK (a) and DBPSK (b) modulation schemes .

Figure 2. Packets reception according to the phase variation of the scheduled
access for DQPSK and DBPSK modulations
From the first simulation result , we notice that for low and
very low data rates, packets reception under the two
modulation schemes is roughly the same. However, for high
data rates (72 packets / sec / node) when the number of
scheduled access slots increases, a better packets reception is
observed when DQPSK modulation is considered (around
3560 packet / node while about 1860 packet / node for the case
of DBPSK modulation).
We can also see what happens at the mac layer level , when
the number of random access phases (RAP) is 2 and the
scheduled access phase is 3.

Figure 3. Packets breakdown at the mac layer when 3 scheduled access
phases are used for DQPSK and DBPSK modulations
At the MAC layer we visualize the percentage of packets
that were received on the first try, after 2 or more tries, and the
percentage of packets that were not received (because of the
saturation of the buffer for example …)
We note that the effectiveness of received packets increases
when the number of scheduled access phases gets higher. It is
also important to note that there are signs of saturation for high
data rates for both modulation schemes.
B. Latency evaluation in scheduled access based WBAN for
DQPSK and DBPSK modulation schemes
1) Latency for DQPSK modulatio n

Figure 4 shows the packets reception time in ms for
multiple data rates, when scheduled access is defined as the
channel access method , and DQPSK is the adopted modulation
scheme.

Figure 4. Latency evaluation for DQPSK
For DQPSK modulation, we note that for lo w and very low
data rates, 15 to 20% of packets are received in a time less than
40ms or greater than 200ms, while for high data rates, a
significant amount of packets (33.8%) is received after 200 ms.

2) Latency for DBPSK modulation :

The graph below (figu re 5) shows the packet s reception
time in ms for multiple data rates, when scheduled access is
used, and DB PSK modulation is considered. Energy module
Parameters description values
periodicEnergyCalculat
ionInterval Energy calculating
interval in ms
1000
baselineNodePower Minimum energy
consumption of a node in
mW
6
initialEnergy Initial energy of a node
in joules 18720
sigmaCPUClockDrift Standard deviation of
CPU drift 0.00003

Figure 5. Latency evaluation for DBPSK
When DBPSK modulation is used, we notice that for high
data rates, around 100% of packet s are only received after the
200ms, which is not desirable especially when it comes to
medical applications where latency is highly required, and
should not exceed 125 ms [4].
However, for low data rates, DBPSK modulation
guarantees, approximately, 18 % of received pac kets in a time
less than 20 ms, and almost 19% of the packets reception with
a latency time greater than 200 ms. the rest of the packets being
received in times varying between 20 and 200 ms.
C. energy consumption evaluation at each node of the
proposed WBAN for DBPSK and DQPSK modulations:
1) energy consumption for DQPSK modulation:

Another performance indicator in IEEE 802.15.6 based
WBANs is the energy efficiency. The graph below (figure 6)
describes the consumed energy at each node when DQPSK
modulation is
adopted.

Figure 6. Consumed energy at each node for DQPSK modul ation
As shown i n the graph above , the rates of energy
consumption, for low as for high data rates, with the DQPSK
modulation, are very comparable (34% in low data rate versus
37% in high data rates).

2) Energy consumption for DBPSK modulation:
Although DBPSK and DQPSK modulation schemes are
both recommende d by the IEEE 802 15.6 standard for the NB
(2.4 Ghz) physical layer, the use of eithe r of these two
schemes, as shown as a result in figure 7, seems to b e very
identical in terms of energy consumption at the sensors of the
studied WBAN model.

Figure 7. Consumed energy at each node for Db PSK modul ation
IV. CONCLUSION :
In this paper we have investigated the effect of the two
modulation schemes recommended by the IEE E 802.15.6
standard in the 2.4Ghz band of the Narrwoband physical layer,
for a wban model of 11 nodes, in terms of packets reception,
latency, and consumed energy.
The simulation results have shown that, for low and very
low data rates, packets reception u nder the two modulation
schemes is roughly the same. However, for high data rates a
better packets reception is observed when DQPSK modulation
is considered. We also noticed that that the effectiveness of
received packets increases when the number of sched uled
access phases gets higher. It is also important to note that there
are signs of saturation for high data rates for both modulation
schemes .
Regarding latency, for low data rates comparable results are
obtained for both modulation schemes, however, a c ritical
value is detected in high data rates especially when DBPSK is
considered.
Furthermore, the use of either of these two schemes, seems
to be very identical in terms of energy consumption at the
sensors of the studied WBAN model.
We can finally assume that DBPSK modulation can be
effective for low data rates medical applications, meanwhile
DQPSK modulation can promise better performance for h igh
rate medical applications.
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