UNIVERSITY OF NAIROBI
FACULTY OF ENGINEERING
DEPARTMENT OF ELECTRICAL AND INFORMATION ENGINEERING
ULTRA-WIDEBAND (UWB) MODEM FOR WIRELESS BODY AREA NETWORK
(WBAN) APPLICATIONS
PROJECT INDEX: PRJ 063
BY
ONYANGO BEN SEWE
F17/2394/2009
SUPERVISOR: PROF. V K ODUOL
EXAMINER: DR. G S O ODHIAMBO
Project report submitted in partial fulfillment of the
requirement for the award of the degree
of
Bachelor of Science in ELECTRICAL AND ELECTRONIC ENGINEERING of the
University of Nairobi 2014
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DEDICATION
To my wonderful family, for their unwavering support throughout my education.
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ACKNOWLADGEMENT
First and foremost, I wish to thank the Almighty God for guiding me and being by my side throughout my
studies.
I would like to express my sincere and heartfelt gratitude to my supervisor Prof. Vitalis K Oduol for his
guidance and insight during this project.
I would not forget to express my gratitude to our Telecommunications lecturer Dr G S O Odhiambo for
availing such a bank of knowledge to withdraw from.
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DECLARATION AND CERTIFICATION
This is my original work and has not been presented for a degree award in this or any other
university.
………………………………………………………..
ONYANGO BEN SEWE
F17/2394/2009
This report has been submitted to the Department of Electrical and Information Engineering, The
University of Nairobi with my approval as supervisor:
………………………………
PROF. V K ODUOL
Date: ……………………
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Table of contents
DEDICATION……………………………………………………………………………..2
ACKNOWLADEMENT……………………………………………………………………3
DECLARETION AND CERTIFICATION…………………………………………………………4
TABLE OF CONTENTS……………………………………………………………………………5
CHAPTER 1 INTRODUCTION……………………………………………………………………7
1.1 Problem Statement
1.2 Project Objectives
CHAPTER 2 LITERATURE REVIEW…………………………………………………………….9
2.1 WBAN……………………………………………………………………………9
2.1.1 Definition
2.1.2 BAN Regulations
2.1.3 BAN Sensing and Monitoring
2.1.4 BAN Applications
2.1.5 BAN Challenges
2.2 Ultra wideband UWB……………………………………………………………..13
2.2.1 Definition
2.2.2 Regulations
2.2.3 Advantages
2.2.4 Applications
2.2.5 Properties of UWB
2.2.6 UWB transmission Channels
2.3 Multiband OFDM Approach……………………………………………………..16
2.3.1 Signal Model
2.3.2 Transceiver model
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CHAPTER 3 DESIGN………………………………………………………………………………..19
CHAPTER 4 RESULTS………………………………………………………………………………25
CHAPTER 5 ANALYSIS…………………………………………………………………………….46
CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS……………………………………..47
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ABSTRACT
The major constraints in the design of Wireless Body Area Networks can be attributed to the
battery autonomy, need for high data rate services and low interference from the devices
operating within the ISM bands. To meet the demand for high data rate services and low power
spectral density to avoid ISM band interference, an Ultra-Wide Band system based technology
has been proposed.
This paper focuses on the design and demonstration of an Ultra-wide Band modem to be used in
the Body Area Network (BAN) applications and the evaluation of its performance in a near- real
world scenarios affected by noise interference and multi path fading.
It also highlights the various applications of Body Area Network.
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CHAPTER 1
INTRODUCTION
The advancement in technology can also be seen in miniaturization of electronic devices,
sensors, battery and wireless communication, which have led to the development of Wireless
Body Area Networks (WBAN). Wireless body area network in simple terminology, can be
described as a network around the body which consist of smart miniaturized devices that are able
to sense, process and communicate.[1]
Typical body area network kits consist of battery, sensor, signal processor, and a transceiver [1]
(modem). A modem is a device that modulates an analog signal, encode the signal then transmit,
similarly it receives the signal, decodes it and demodulate it. The main objective of a transceiver
is to produce a signal that can be transmitted easily and then decoded to produce the original
signal.
Ultra-wideband (UWB) technology provides the high rate of data transmission due to its
relatively large bandwidth of transmission. According to ITU-R, UWB spans a frequency range
of 3.1GHz to 10.6GHz with a transmission bandwidth of more than 20% of its centre frequency
i.e. more than 500MHz. Based on this transmission bandwidth, it can be seen that the white
Gaussian channel capacity of a UWB system is large for a given SNR according to Hartley
Shannon law.[6]
1.1 Problem statement
The major constraint in the design of BAN is the battery autonomy, high data rate services and
interference from the devices operating within the ISM bands. To meet the demand for high data
rate services and low power spectral density to avoid ISM band interference, an Ultra-Wide
Band system based technology has been proposed.
1.2 Project objective
The objectives of this project were to study the ultra-wideband wireless communication systems,
wireless body area network (BAN) applications and then design and demonstrate a modem to be
used in those applications.
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CHAPTER 2
LITERATURE REVIEW
2.1 WIRELESS BODY AREA NETWORKS (WBAN)
2.1.1 Definition
Wireless Body Area network (WBAN) or simply BAN is defined as a network of wearable
computing devices. In particular the network consists of several miniaturized body sensor units
(BSUs) placed at different points on the body referred to as nodes, and a single body central unit
(BCUs) that acts as the hub for the network [3].
2.1.2 BAN Regulation
The body area network is regulated by the IEEE.802.15.6 recommendation. This task group was
formed to focus on a low power and short range wireless standard of optimization for BAN.
According to IEEE.802.15.6, BAN can be used in, on or around the human body to enable
medical, consumer electronics and personal communications. This recommendation started
specifically for wireless networks in or on the body with low power as in figure (1). [14]
Figure1. Data and power profile
IEEE 802.15.6 regulation also extends to the requirements for various BAN applications: [17]
QoS: the applications need an assurance in the data connections to the nodes, therefore emphasis
is taken to ensure reduced number of delays and losses.
Data rates: several applications needs specific data rates [16], which ranges from 10Kbps to
10Mbps. 10Mbps is achievable with Ultra-wideband (UWB).
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Security: secure transmission is needed for sensitive data. [16]
2.1.3 BAN sensing and monitoring
The BAN monitoring is done by special sensors located at various locations on the body. The
sensors are of two categories: wearable and implanted [1]
2.1.3a Wearable sensors
Pulse oxy-meter
This is a device that measures oxygen saturation levels (SpO2) in an individual’s blood as well as
changes in blood volume that coincide with the cardiac cycle. Pulse oxy-meter is attached to a
finger or an earlobe. It consists of red and infra-red LEDs and a photo detector. The photodetector measures the amount of red and infra-red light that is transmitted through or reflected by
the body parts which is partially dependent on the amount of light absorbed by the blood that
perfuse the body part. This absorption of red or infra-red light by the blood is related to the ratio
of oxygenated hemoglobin to deoxygenated hemoglobin and this serves as the basis for SpO2
measurements. [1]
.
Figure3 pulse oximeter
Electrocardiography
Electrocardiography (ECG) simply means recording of the heart electrical activity. ECG is used to
measure the heart’s electrical conduction system. It picks up electrical impulses generated by the
polarization and depolarization of cardiac tissue and translates into a waveform. The waveform is
the used to measure the rate and regularity of the heart beats as well as the position and size of
the chambers [14].
Blood pressure sensor
A blood pressure (BP) reading is a measure of the force exerted by circulating blood on the walls of blood
vessels. BP varies between a maximum (systolic) and a minimum (diastolic) pressure during a cardiac
cycle. Normally blood pressure is measured in the arteries in the arm, but the pressure at the heart might
be a better predictor of future health problems [1]. This sensor is always worn on the wrist
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Fig4 Cuff-less Blood Pressure Watch Prototype (Courtesy of Poon et. al. [17])
Electromyography (EMG)
Electromyography is the study of muscle function through the monitoring of the electrical
signals emitted by the muscle [1]. When a surface electrode is placed on the skin above a
superficial muscle while it is contracting, it will receive electrical signals emanating from several
muscle fibers associated with different motor units. The spatio-temporal summation of these
electrical signals results in what is called an electromyogram (EMG) signal. Therefore, the EMG
signal provides an effective means of monitoring muscle activity.
Accelerometer and Gyroscope
An accelerometer is a sensor that measures acceleration with respect to gravity, and can be used
to determine the orientation of a body part in the absence of movement. A gyroscope is a sensor
that measures angular velocity and can be used to determine the orientation of a moving body
part as a function of time. [1]
Electroencephalography (EEG)
Electroencephalography (EEG) is a representation of the electrical activity of the brain.
Electroencephalograph sensor measures the electrical activities of the brain. This particular
sensor is important especially in healthcare application for patients diagnosed with epilepsy and
in monitoring their response to therapy.[1]
2.1.3b Implantable sensors
Glucose Monitoring
It has been shown in [1] that real-time continuous blood glucose data will assist in reducing
hyperglycemic excursions for individuals with type1 diabetes, while lowering the risk of
episodes of hypoglycemia caused by the administered levels of insulin being too high.
Continuous monitoring is enabled by placing an implantable sensor covered with a multilayered
membrane in the subcutaneous tissue of the abdomen.
Implantable Neural Stimulators
Implantable neural stimulators send electrical impulses into the brain or spinal cord for the
treatment of Parkinson’s disease, intractable epilepsy and chronic pain. [1]
Endoscope capsule (gastrointestinal)
A swallowable capsule that travels through the gastrointestinal tract transmitting video;
The implantable sensors are used mainly in health care applications. [1]
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2.1.4 BAN applications
Healthcare applications
These applications are typically associated with low data rates needed to communicate vital data
about human health e.g. heart rate, brain activity, blood pressure, muscle activity, blood sugar
level, body temperature, levels of oxygen in the blood, motion etc. the BAN allows reliable
monitoring and data transfer for patients without interfering with their mobility [1]. [2] [4] [5]
Military applications
In the military, a battle dress uniform is integrated with a BAN that connects devices such as life
support sensors, cameras, and health monitoring GPS. These devices relay real time information.
Future advancements will include missile detection sensors and this will indeed revolutionize
warfare.[1] [2] [4] [5]
Lifestyle and sports
Lifestyle and sports are revolutionized since new services like wearable entertainment systems,
navigation support in the car or while walking, museum or city guide, heart rate and performance
monitoring in sports using muscle activity sensors are made possible by the BAN technology.
Monitoring of persons operating in harsh or hostile environments
There are professions or jobs that require the integration of BAN, for example, miners, fire
fighters, etc to monitor their health and also improve the general working conditions.
2.1.5 BAN challenges
Cost: Today's consumers expect low cost health monitoring solutions which provide high
functionality. WBAN implementations will need to be cost optimized to be appealing
alternatives to health conscious consumers.[12] [17]
Consistent performance: The performance of the WBAN should be consistent. Sensor
measurements should be accurate and calibrated even when the WBAN is switched off and
switched on again. The wireless links should be robust and work under various user
environments [12] [17]
Interference: The wireless link used for body sensors should reduce the interference and
increase the coexistence of sensor node devices with other network devices available in the
environment. This is especially important for large scale implementation of WBAN systems [12]
[17]
Invasion of privacy: People might consider the WBAN technology as a potential threat to
freedom, if the applications go beyond "secure" medical usage. Social acceptance would be key
to this technology finding a wider application.[12] [17]
System devices: The sensors used in WBAN would have to be low on complexity, small in form
factor, light in weight, power efficient, easy to use and reconfigurable. Further, the storage
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devices need to facilitate remote storage and viewing of patient data as well as access to external
processing and analysis tools via the internet [12] [17]
2.2. ULTRA-WIDEBAND
2.2.1 Definition
UWB is defined as a system signal that occupies a bandwidth greater than 500MHz or 25% of
the center frequency. This is given as
Fractional bandwidth =
𝑓𝑈 −𝑓𝐿
𝑓𝑐
≥ 0.25 where center frequency fc =
𝑓𝑈 +𝑓𝐿
2
Hz
Where 𝑓𝑈 is the upper frequency limit and 𝑓𝐿 is the lower frequency limit for that particular
frequency band.[6]
ITU-R defines UWB as technology for short-range radio communication, involving the
intentional generation and transmission of radio-frequency energy that spreads over a very large
frequency range, which may overlap several frequency bands allocated to radio communication
services. Devices using UWB technology typically have intentional radiation from the antenna
with either a –10 dB bandwidth of at least 500 MHz or a –10 dB fractional bandwidth greater
than 0.2
2.2.2 UWB regulations
Ultra-wideband technology is governed by several international bodies, but of interest is the
ITU-R which restricts the UWB frequency band as from 3.1GHz. Federal Communications
Commission (FCC) in the USA allows the UWB technology to operate in the unlicensed 3.1GHz
to 10.6GHz. These bodies also specifies the power spectral density mask for the UWB to be 41.3dBm/MHz [6]
2.2.3Advantages of UWB
Principal advantages of UWB can be summarized as follows:[6]
 Potential for high data rates. The high data rates are obtained from the extremely large
bandwidth yielding high theoretical capacity.
 Extensive multipath diversity. The ultra-short duration of the UWB waveforms gives rise
to a finer resolution of reflected pulses at the receiver hence low susceptibility to
multipath interference.
 Potential small size and processing power with low equipment cost
 Very low power density leads to low probability of signal detection. The low power
density is obtained through the radio regulation emission masks
 UWB systems are suitable for coexistence with the already existing narrow band
technologies
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2.2.4 UWB applications
UWB offers potential for deployment of two basic communication systems:
 High data rate short range communications eg high data rate wireless personal area
networks (WPAN). An example of WPAN application is the high speed universal serial
bus (WUSB) connectivity for PCs
 Low data rate and location e.g. sensor, positioning and identification networks.
It is of a particular interest to note that, UWB can trade a reduction in data rate for an increase in
transmission range. [6]
2.2.6 Basic properties of UWB[10]
Power spectral density
Generally considered to be low and is given by
𝑝𝑜𝑤𝑒𝑟 𝑡𝑟𝑎𝑛𝑠𝑚𝑖𝑡𝑡𝑒𝑑(𝑤𝑎𝑡𝑡𝑠)
𝑃𝑆𝐷 = 𝑏𝑎𝑛𝑑𝑤𝑖𝑑𝑡ℎ 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑖𝑔𝑛𝑎𝑙 (𝐻𝑧)
This means that the energy is spread out over a very large bandwidth hence low PSD.
Pulse shape
UWB pulses are typically of nanosecond or picoseconds order. A fast switching on and off leads
to a pulse that is not rectangular but has edges smoothed off. This approximates Gaussian
function curve
Pulse trains
Information needs to be modulated onto a sequence of pulses called pulse trains. When pulses
are sent at regular intervals, the resulting spectrum will contain peaks of power at certain
frequencies. These peaks of power are called comb lines and they limit the total transmit power.
This effect is minimized by making the spectrum more noise like i.e. adding a small random
offset to each pulse.
Spectral masks
UWB systems cover a large spectrum and interface with existing users. In order to keep this
interference to a minimum, the regulatory groups specify the spectral mask for different
applications which shows the allowed power output for specific frequencies
Penetration characteristics
UWB pulses are composed of large range of frequencies. The penetration capability is therefore
noted to decrease with the higher frequencies. This means that, the higher frequency waves will
have more of their energy reflected from walls and doors since their wavelengths are much
shorter.
Spatial and Spectral capacities
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Spatial capacity is measured in bits/second/square meter. Spatial capacity is calculated as
𝑠𝑝𝑎𝑡𝑖𝑎𝑙 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 =
𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑑𝑎𝑡𝑎 𝑟𝑎𝑡𝑒(𝑏𝑝𝑠)
𝑡𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑎𝑟𝑒𝑎(𝑚2 )
While spectral capacity is calculated as
𝑠𝑝𝑒𝑐𝑡𝑟𝑎𝑙 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 =
𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑑𝑎𝑡𝑎 𝑟𝑎𝑡𝑒(𝑏𝑝𝑠)
𝑏𝑎𝑛𝑑𝑤𝑖𝑑𝑡ℎ(𝐻𝑧)
Since UWB systems have a large bandwidth, it therefore has very low spectral capacity
compared with the existing systems.
Speed of data transmission
UWB communications are targeting the range of 100-500Mbps. The lower speeds of close to
100Mbps are for a target of a minimum distance of 10m, above 200Mbps for not less than 4m,
and 480Mbps has no fixed minimum distance
2.2.6 UWB Transmission Schemes
The transmission schemes can be categorized into two:
 Single band approach
 Multi-band approach
2.2.6a Single band approach
This scheme employs carrier free or impulse radio communication. Impulse radio refers a generation of
series of impulse like waveforms each of duration in the order of hundreds of picoseconds. Data could
be modulated using PAM, PPM, OOK and PSK, and multiple users could be supported via the
use of time-hopping or direct-sequence spreading approaches [6]
This approach treats the whole frequency span of 7.5GHz (3.1GHz to 10.6GHz) as a whole
transmission bandwidth. And therefore exploits Shannon principle to a greater degree.
Channel capacity 𝐶 = 𝐵𝑇 𝑙𝑜𝑔2 (1 + 𝑆𝑁𝑅)
This scheme suffers from certain drawbacks such as:
 Building RF and analog circuits as well as high speed ADC to process the large
bandwidth signal is challenging and requires high power consumption
 Less flexible with regard to foreign spectral regulation and may be too broadband if
foreign governments choose to limit their UWB spectral allocations.
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2.2.6b Multiband approach
This scheme divides the frequency band from 3.1 to 10.6GHz into several smaller bands called
subbands. Each subband occupies a bandwidth of at least 500MHz in conformity with the ITU-R
recommendations.
The transmitted symbols are interleaved across subbands therefore the multiband approach can
maintain the power being transmitted as if a large BW were being utilized
This approach uses the OFDM as the modulation scheme.
Advantages of multiband approach
 Ability for a fine grained control of the PSD so as to maximize the power transmitted
while meeting the spectral mask
 Allows for peaceful coexistence with a flexible spectral coverage, and is easier to adapt to
different world wide regulatory environment.
 Processing over a smaller bandwidth eases the requirement on ADC sampling rates and
consequently facilitates greater digital processing
 Using the OFDM as a modulation scheme, reduces the effect of inter symbol interference
(ISI)
This scheme suffers from a complex transceiver design
2.3 MULTIBAND OFDM APPROACH
OFDM relies on splitting the information to be transmitted over a large number of carriers in
such a way that the signaling rate on each of them becomes significantly longer than the echo
delay period
The multiband OFDM approach is one of the leading proposals of IEEE 802.15.3a standards to
capture the multipath energy efficiently by using OFDM technique to modulate information on
each subband. The OFDM symbols are then interleaved over different subbands across both time
and frequency.
2.3.1 Signal model
The available UWB spectrum is divided into S subbands with a BW>500MHz. The OFDM has
N subcarriers and the OFDM symbols are then transmitted over one of the S subbands. Each
OFDM symbol 𝑥𝑘 (𝑡) is constructed using an IFFT as
𝑁−1
𝑥𝑘 (𝑡) = ∑ 𝑑𝑘 (𝑛)exp(𝑗2𝜋𝑛∆𝑓𝑡)
𝑛=0
Where 𝑑𝑘 (𝑛)is the complex coefficient to be transmitted in subcarrier n during the kth OFDM
symbol period and ∆𝑓 = BW/N is the frequency spacing between the adjacent carriers
The resulting waveform has duration of 𝑇𝐹𝐹𝑇 = 1/∆𝑓. The cyclic prefix of length 𝑇𝐶𝑃 is
appended in order to mitigate the effect of multipath interference. Also a guard interval 𝑇𝐺𝐼 is
used to provide sufficient time for switching between bands.
The symbol duration 𝑇𝑆𝑌𝑀 = 𝑇𝐹𝐹𝑇 + 𝑇𝐶𝑃 + 𝑇𝐺𝐼
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The complex baseband signal 𝑥𝑘 (𝑡) is modulated to RF signal with a carrier frequency𝑓𝑘 . The
transmitted RF signal 𝑠(𝑡) is given as
𝑠(𝑡) = ∑𝑘 𝑅𝑒{𝑥𝑘 (𝑡 − 𝑘𝑇𝑆𝑌𝑀 )exp(𝑗2𝜋𝑓𝑘 𝑡)}
According to the IEEE 802.15.3a WPAN standard proposal,
UWB signal is shaped so that it occupies only 528MHz of bandwidth
This allows 14 such signals to cover the entire 7.5GHz band. OFDM allows each UWB band to
be divided into a set of orthogonal narrowband channels with a much longer symbol period
duration. QPSK is used to modulate the transmitter signal at the subcarriers due to the limitation
on transmitter power.
IEEE 802.15.3a timing parameters:[6]
OFDM sub carriers
128
Data sub carriers
100
Number of defined pilot sub carriers
12
∆𝑓 sub carrier frequency spacing
(528MHz/128)=4.125MHz
𝑇𝐹𝐹𝑇 = 1/∆𝑓.
242.42ns
𝑇𝐶𝑃 : cyclic prefix
(32/528MHz)= 60.61ns
𝑇𝐺𝐼 : guard interval
(5/528MHz) = 9.47ns
𝑇𝑆𝑌𝑀 = (𝑇𝐹𝐹𝑇 + 𝑇𝐶𝑃 + 𝑇𝐺𝐼 ) : symbol duration
312.5ns
2.4 TRANSCEIVER MODEL
A typical digital communication system is as in the diagram below.
information
source
Source
encoder
Error control
encoder
Modulator
Noise
Information
Received
Source
decoder
Error control
decoder
Equalizer
fig digital communication system
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Channel
Demodulator
The source encoder converts the analog signal to digital signal eg the ADC. The forward error
control encoder places extra parity check digits to protect the information from channel error.
This parity check digits are used by the decoder to check the errors that might have occurred
during transmission and correct some of them.
The modulator converts the bits to a waveform that is suitable for transmission through the
physical channel. The receiver demodulates the signal that comes out from the channel and
converts the signal into base-band signal.
The equalizer is used to reduce the inter-symbol interference (ISI). The error free output of the
ARQ is sent to the source decoder for conversion to a suitable form for the information sink.
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CHAPTER 3
UWB MODEM DESIGN
Since the BAN sensors have an integrated signal processing chips, the input to the transceiver is
in digital form hence no need to include source coding as part of the transceiver design.
The physical UWB transceiver design simulation includes:
 Random binary generator
 Concatenated codes
 QPSK modulator/ demodulator
 OFDM transceiver.
 Channel
3.1 Random binary generator
The Bernoulli binary generator is used to generate random binary digits using the Bernoulli
distribution. It produces a zero bit (0) with a probability of p and a one bit (1) with probability of
1-p.
In this case an equiprobable situation is simulated where both ‘0’ and ‘1’ are produced with a
probability of 0.5. The output of this generator is frame based having 256 bits per frame at a
sampling rate of 1/528MHz
3.2 Concatenated codes
In wireless communications, burst errors occur due to the reflection of the symbols on large
surfaces e.g. buildings, trees, hills etc. in addition to that random errors also occur due to the
thermal noise generated in the electronic circuitry [11]. This calls for a coding scheme with a
large codeword length. A serial concatenation of codes is the most commonly used for powerlimited systems
In this case a (48, 32, 8) R-S code (outer code) with symbols over GF (28 ) and a (2, 1)
convolution code of constraint length 7 was used.
3.2a Reed Solomon coding/decoding
A (48, 32, 8) R-S code over GF (28 ) was obtained by code shortening scheme of puncturing
(zero padding) as shown in below in a matlab simulink model
This code corrects up to 8 symbol errors out of the 48 symbols
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Since R-S encoder is a non binary coding scheme, the 256 bit frame from the Bernoulli
generator is converted to integers using bit to integer converter of M=8,resulting into 32 bytes
This is the input sequence to the R-S encoder subsystem below
Fig3 R-S encoder
The 32 byte sequence is zero padded to 239 message bytes which is then fed to the integer input
R-S encoder.
This block adds 16 parity check bytes to give 255 codeword length. Since we are interested in
the 48 code words, the zero padded 255 code words is passed through a selector to give the 48
codewords hence a (48, 32, 8) R-S code achieved from the (255, 239,8) R-S code. The 48 bytes
is converted back to binary to give 384 bits which is passed through to the convolution encoder.
In the decoder the 384 bits is converted to bytes, zero padded to and fed to the decoder which
decodes the message i.e. corrects any error introduced during the transmission and removes the
parity check bits. The zero padded 239 message digits from the decoder is passed through a
selector to obtain the 32 original message digits which are then converted back to binary.
Fig4 R-S decoder
3.2b Convolution coding/ virterbi decoding
This convolution code has an information rate of ½ and constraint length of 7.
It uses the poly2trellis (7, [171 133]) function to create a trellis using the constraint length, code
generator (octal) and feedback connection (octal).
As can be seen from the figure below
Output [a, b] = input[𝑥1 , 𝑥2 ]
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Where 𝑥1 , = (1111001) = (171)8
𝑥2 = (1011011) = (133)8
polytrellis(7[171,133]) structure 1
The viterbi decoder also uses the same polytrellis function while decoding the information
transmitted.
Since the information rate is ½, this implies that for every one bit, two codewords are produced
hence the output of the convolution encoder is 768 bits.
The viterbi decoder, detects and corrects the random errors and removes the parity check bits
hence its output is 384 bits
3.3 QPSK modulator /demodulator
This modulator maps the binary digits from the information sequence into discrete phases of the
carrier (𝜃𝑚 ). Where 𝜃𝑚 = 2π(m-1)⁄M for m=0,1,2…..M. [3]in this case M=4 hence gray coded
constellation mapping is as below [14].
The 768 message bits are converted to integers since m=0, 1, 2, 3 and 4, and then fed into the
QPSK modulator which maps the 384 integers to complex 384 integers.
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QPSK Constellation mapping
3.4 OFDM transceiver
OFDM symbol consist of the data carriers, guard subcarriers and the cyclic prefix, with time
durations as shown in the diagram below [13]. In this design, 128 sub carriers are used, with 96
being data carriers, 12 pilots and 20 nulls for guard. A cyclic prefix of 32 subcarriers is
appended.
OFDM symbol
The 384 complex integers are rearranged to form a 96x4 array matrix. The matrix is the
regrouped as
{1,[2:10],[11:19],[20:28],[29:37],[38:46],[47:50],[51:54],[55:62],[63:70],[71:78],[79:86],[87:96]
} to allow the insertion of the pilots.
The pilots are inserted at the positions (2, 12, 22, 32, 42, 52, 61, 70, 79, 88, 97, 108).
The guards are then inserted at the beginning and end of the data carriers. The symbol is then
passed through the IFFT to create the orthogonal signals.
A cyclic prefix is the appended by rearranging and reordering the sequence as [97:128 1:128].
This command repeats the last 32 carriers at the beginning of the OFDM symbol.
Page 22 of 47
The OFDM symbol is then power scaled and transmitted via the AWGN channel. The OFDM
transmitter was designed as shown in the diagram below
OFDM transmitter
At the receiver, the received symbol is down scaled; the cyclic prefix is removed by selecting the
message portion.
The received message is then transformed by FFT (Fast Fourier Transform) to remove the
orthogonality. The guards are then removed and subsequently the pilots.
The remaining data stream is then rearranged back to the 384 constellation points and then
demodulated using QPSK demodulator
Page 23 of 47
OFDM Receiver
3.5 The channel
Transmissions over three different channels are simulated:
 Additive White Gaussian Noise Channel (AWGN)
 Multipath Rayleigh Fading Channel
 Multipath Rician Fading Channel
3.5a AWGN channel
This channel adds white Gaussian noise to the input signal. The SNRs of 30dB to 50dB was
simulated and results displayed.
3.5b Multipath Rayleigh Fading Channel.
This channel depicts a situation where the transmitted signal arrives at the receiver via different
paths. This is caused by reflections from surfaces like walls. The different paths have their
associated path delays and losses.
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This channel multiplies the input signal by samples of a Rayleigh-distributed complex random
process. In this design up to three paths are simulated and the results displayed.
3.5c Multipath Rician Fading Channel
This channel portrays a situation where the transmitted signal can travel to the receiver along a
dominant line-of-sight or direct path.
Relative motion between the transmitter and receiver causes Doppler shifts in the signal
frequency. In addition to the channel having multiple path delays and fading, the signal
transmitted over this channel experiences changes in the frequency of propagation
In this design up to three paths are simulated and the results displayed.
3.6 Overall design diagram
Page 25 of 47
CHAPTER 4
RESULTS
4.1 AWGN CHANNEL
SNR = 30dB
4.1.1. Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
50
100
150
200
250
Time (ns)
300
350
400
450
Offset=0
Fig 4.1.1 1a transmitted signal
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Fig 4.1.1 .1b Received signal
Page 26 of 47
5
6
7
Error rate calculation
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
Page 27 of 47
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
10
Eye diagram
In-phase Amplitude
Eye Diagram
2
1
0
-1
-2
-3
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
2
1
0
-1
-2
-3
0
50
Time (ps)
Time scatter plot
Scatter Plot
1.5
Quadrature Amplitude
1
0.5
0
-0.5
-1
-1.5
-1.5
-1
-0.5
0
0.5
In-phase Amplitude
Page 28 of 47
1
1.5
SNR = 38dB
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
50
100
150
200
250
Time (ns)
300
350
400
450
Offset=0
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Page 29 of 47
5
6
7
Error rate calculation
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
Page 30 of 47
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
10
Eye diagram
Eye Diagram
In-phase Amplitude
1
0.5
0
-0.5
-1
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
1
0.5
0
-0.5
-1
0
50
Time (ps)
Time scatter plot
Scatter Plot
1
0.8
Quadrature Amplitude
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-1
-0.5
0
In-phase Amplitude
Page 31 of 47
0.5
1
SNR= 45dB
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
50
100
150
200
250
Time (ns)
300
350
400
450
Offset=0
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Error rate calculation
Page 32 of 47
5
6
7
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
Eye diagram
Eye Diagram
In-phase Amplitude
1
0.5
0
-0.5
-1
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
1
0.5
0
-0.5
-1
0
50
Time (ps)
Page 33 of 47
10
Time scatter plot
Scatter Plot
1
0.8
Quadrature Amplitude
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-1
-0.5
0
0.5
1
In-phase Amplitude
4.2 Multipath Rayleigh Fading Channel
Single path with no delay period
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
Offset=0
Page 34 of 47
50
100
150
200
250
Time (ns)
300
350
400
450
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
Time (ns)
Offset=0
Error rate calculation
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
Page 35 of 47
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
10
Eye diagram
In-phase Amplitude
Eye Diagram
1
0
-1
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
1
0
-1
0
50
Time (ps)
Time scatter plot
Scatter Plot
1.5
Quadrature Amplitude
1
0.5
0
-0.5
-1
-1.5
-1.5
-1
-0.5
0
0.5
In-phase Amplitude
Page 36 of 47
1
1.5
Multiple paths with no delay period
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
50
100
150
200
250
Time (ns)
300
350
400
450
Offset=0
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Page 37 of 47
5
6
7
Error rate calculation
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
Page 38 of 47
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
10
Eye diagram
Eye Diagram
In-phase Amplitude
0.4
0.2
0
-0.2
-0.4
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
0.4
0.2
0
-0.2
-0.4
0
50
Time (ps)
Time scatter plot
Scatter Plot
1.5
Quadrature Amplitude
1
0.5
0
-0.5
-1
-1.5
-1.5
-1
-0.5
0
0.5
In-phase Amplitude
Page 39 of 47
1
1.5
Multipath Rician Channel
Single path with no delay period
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
50
100
150
200
250
Time (ns)
300
350
400
450
Offset=0
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Page 40 of 47
5
6
7
Error rate calculation
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
Eye diagram
In-phase Amplitude
Eye Diagram
1
0
-1
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
1
0
-1
0
50
Time (ps)
Page 41 of 47
8
10
Time scatter plot
Scatter Plot
1.5
Quadrature Amplitude
1
0.5
0
-0.5
-1
-1.5
-1.5
-1
-0.5
0
0.5
1
1.5
In-phase Amplitude
Multiple paths with no delay period
Transmitted signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
Offset=0
Page 42 of 47
50
100
150
200
250
Time (ns)
300
350
400
450
Received signal
1
0.8
Amplitude
0.6
0.4
0.2
0
0
1
2
3
4
Time (ns)
Offset=0
Error rate calculation
Page 43 of 47
5
6
7
Signal spectrum
-80
-90
dBm / Hz
-100
-110
-120
-130
-140
RBW: 20.62 MHz, NFFT: 128, Span: 21.12 GHz, CF: 0 Hz
-10
-8
-6
-4
-2
0
Frequency (GHz)
2
4
6
8
Eye diagram
In-phase Amplitude
Eye Diagram
0.2
0
-0.2
0
50
100
150
100
150
Quadrature Amplitude
Time (ps)
0.2
0
-0.2
0
50
Time (ps)
Page 44 of 47
10
Time scatter plot
Scatter Plot
1.5
Quadrature Amplitude
1
0.5
0
-0.5
-1
-1.5
-1.5
-1
-0.5
0
0.5
In-phase Amplitude
Page 45 of 47
1
1.5
CHAPTER 5
RESULT ANALYSIS
AWGN Channel
From the results obtained, the time scatter plot and the Eye diagrams shows the ISI. The wider
the eye the lower the ISI. This is further proved by a keen look at the scatter plots, if the plots are
randomly distributed, it shows that the noise power is higher than the signal power. Another
possible explanation could be due to the effect of ISI.
This analysis plus the results shows that for a given transmission bandwidth, the system
performance improves as the SNR increases. This is in line with the Hartley- Shannon law for
white Gaussian channel
The error calculations done further proves that indeed as the SNR increases, an error free
transmission is possible
Multipath Rayleigh /Rician Fading channel
The results obtained thus far aren’t conclusive especially for the multipath portions of the
simulation. This is because the comparison done using matlab simulink especially the error rate
calculation does not take into account the delay effect and multiple paths from which the signal
arrives.
But a keen comparison of the transmitted signal and the received signal proves that the same
signal transmitted is the same one received even under multipath fading conditions. This can be
attributed to the advantage the OFDM scheme has of being robust against multipath interference.
One thing is clear though, for the simulation considering only one path, the error rate was found
to be zero with minimum ISI.
Signal spectrum
From the signal spectrum it is noted that the transmitted signal has a PSD of around -80dbm/Hz.
Thus this modem ensures low spectral density transmission though not in conformity to the -41.3
dBm/Hz required by the regulating bodies.
Transmission speed
From the parameters mentioned before, OFDM symbol duration is 312.5 ns this gives a
maximum throughput of 3.2MHz.
The speed is given by: 𝑟𝑎𝑡𝑒 =
(𝑑𝑎𝑡𝑎 𝑐𝑎𝑟𝑟𝑖𝑒𝑟𝑠 )𝑥 (𝑐𝑜𝑑𝑖𝑛𝑔 𝑟𝑎𝑡𝑒 )𝑥( 𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑡ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡)𝑥 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑏𝑖𝑡𝑠
32
= 96𝑥 (96) 𝑥 3.2 𝑥 2
= 204.8𝑀𝑏𝑝𝑠
This rate could be reduced to 102.4 Mbps by a time spreading gain of 2, i.e. the IFFT to transmit
at the same time the complex conjugate of the signal.
Page 46 of 47
CHAPTER 6
CONLUSIONS AND RECOMMENDATION
Conclusion
The objective of this project was to study both the UWB wireless communication systems and
WBAN applications and then design and demonstrate a modem to be used in those applications.
This has been achieved, and the modem simulation showed that it can achieve an error free
transmission at a lower PSD and at a very high data rate.
Recommendations
UWB and Body Area Networks are potential areas for research. They are still emerging
technologies which still needs to be explored for more applications.
REFERENCES
[1] Garth V. Crosby, Tirthankar Ghosh, Renita Murimi, Craig A. Chin “Wireless Body Area
Networks for Healthcare: A Survey”, International Journal of Ad hoc, Sensor & Ubiquitous
Computing (IJASUC) Vol.3, No.3, June 2012.
[2] Movassagi, Samaneh; Abolhasan, Meran and Lipman, Justin and Smith, “Wireless Body
Area Networks, “A survey of IEEE communications and tutorials
[3] Dr. GSO Odhiambo “ Digital Transmission Systems ” FEE 521 class notes University of
Nairobi. 2008
[4] Mehemet R Yuce, “Ultra-wideband and 60GHz communications for Biomedical
Applications,” Springer
[5] Ragesh G.K, Dr. Baskaran, “An Overview of Applications, Standards and Challenges in
Futuristic Wireless Body Area Networks.” International journal of computer science issues 2012
[7] W. Pam Sinwongpairat, K.J Ray Liu “Ultra-Wideband Communications Systems: Multiband
OFDM approach “John Wiley and Sons ltd 2007
[8] X. Shen, M Guizani, R.C Qui, T. Le-Ngoc “Ultra-wideband Wireless Communication and
Networks,” John Wiley and sons ltd 2006
[9] Man Young Rhee “Error Correcting Coding Theory,” McGraw Hill communication series
1989
[10] M. Ghavami, L. B. Michael, R. Kohno “Ultra wideband Signals and Systems in
Communication Engineering”, 2nd edition, John Wiley and Sons, 2007
[11] Dr GSO Odhiambo, “Information Theory and Error control coding”. FEE 522 class notes
University of Nairobi. 2007
[12]http://www.ni.com/white-paper/14285/en/
[13\///]http://en.wikipedia.org/wiki/Electrocardiography
[14] http://cnx.org/content/m32044/latest/graphics1.png
[15] http://cp.literature.agilent.com/litweb/pdf/ads2008/numeric/3125521/numeric-02-02-02.gif
(16 )Daniel Lewis (Ed). 802.15.6 call for applications - response summary. Technical report,
IEEE, January 2009 [visited June 2011].
[17] Pedro Brand˜ao, “Abstracting information on body area networks”, University of
Cambridge, 2012 http://www.cl.cam.ac.uk/techreports/
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