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Institute for Electronics, signal Processing and C
omm
unication (IE
SK)
http://iesk.et.uni-magdeburg.de
Otto-von-Guericke
Uni-Magdeburg
1
Digital Communication Systems
Prof. Dr. A.S. Omar [email protected]
Tariq Jamil Saifullah,Khanzada [email protected], [email protected]
FET,IESK,
Unversity of Magdeburg , Germany
International Master Studies in
Electrical Engineering and Information Technology
http://www.iesk.uni-magdeburg.de/hf_technik/hauptmenue/mitarbeiter_hf/prof__omar.html Omar
http://www.iesk.uni-magdeburg.de/en/microwave_eng_-p-1903/Hauptmen%C3%BC/Mitarbeiter+HF/tariq_j__s__khanzada.html Khanzada
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• Objectives
• Contents
• Course Details
• Communication Systems & Basic Concepts
• Introduction to OFDM and its concept
Outline
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In order to comprehend learning
• Digitize and Code Information Signals
• Transmit Digital Signals over different types of Channels
• De-noise and Decode received Digital Signals
• Characterize Communication Channels
Objectives
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Contents
•Sampling and Source Coding
•Base-Band Techniques (DM, ADM, PCM, DPCM)
•Pass-Band Techniques (ASK, PSK, FSK, QAM, MSK, GMSK)
•Wideband Techniques (SS-DS, SS-FH, CDMA, WCDMA, OFDM)
•Noise Reduction Techniques
•Terrestrial, Mobile and Satellite Communication Networks
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Teaching Lecture and exercises
Prerequisites Bachelor in Electrical Engineering or related studiesProbability and Random Processes
Weight Compulsory module for the Master Course “Electrical Engineering and Information Technology”
Exam Written test at the end of the course
Credit points 4 Credit points = 120 h (42 h time of attendance and
78 h autonomous work)
Work load 2 hours/week - lecture1 hours/week - exercises
Autonomous work Post processing of lectures, Preparation of exercises and exam
Responsibly Lectures Prof. Dr. A.S. Omar [email protected] Exercises M. Eng. Tariq J.S. Khanzada
Location & Time Lectures (Every Tuesday 9:15-10:45 Building 22a, Room 04) Exercises (Every Alternate Thursday 9:15-10:45 Building 05, Room 313)
Course Details
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Textbook
Digital Communication, 4th Ed.
John Proakis, MCGraw Hill 2000
Textbook website www.mhhe.com/engcs/electrical/proakis
Additional Books
Introduction to Digital Communication,
Rodger E. Zeimer and Roger L. Peterson,
Second Edition, Prentice Hall, 2001.
Communication Systems (4th ed.), A. B. Carlson
Digital Communications, by Bernard Sklar,
Second Edition, Prentice Hall, 2001
Communication Systems , Simon Haykin, 4th Ed.
Wiley, 2001, ISBN 0-471-17869-1
Useful literature Textbook
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Excercises & Resources
Exercises Theoritical problems about the topics covered in lectures
Implementation of concepts in programming language
of the choice
Recommonded tool Matlab, C++, Java
Some Learning Web Resources
http://www.mathworks.com/moler/intro.pdf http://www.mathworks
.com/access/helpdesk/help/techdoc/matlab.html http://jdsp.
asu.edu/jdsp.html
www.complextoreal.com
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Device transfer information from one location (time) to another location (time)
Digital: Smoke, Morse Code Telegraph
Analog: Commercial Radio, TV
Digital: Data, Computer, HDTV
Communication
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Communication Systems
Systems communicate in order to share information.
To communicate means to pass information from one place to another.
It is more convenient to convert information into a signal. Your
concern as a communication engineer is with the transmission and
reception of these signals.
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Components of Communication System
Channel(distortion)
TransmitterSource Receiver Destination
Noise
Block diagram of Communication System
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• Point to Point: Telephone, Fax
• Point to Multipoint: Broadcast (Radio, TV)
• Simplex: One Way
• Duplex: Two Ways
Types of Communication Systems
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Cost/Performance Trade Off
Cost Performance
Data Rate
Power Bit Error Probability
Transmission Range
Bandwidth Fault Tolerance
Adaptive to Environment
Complexity Security
Anti Jamming Capability
Low Probability of Interception
Design Consideration
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Digital Communication System
•Source are converted into a sequence of binary digits which is called information sequence Represent the source by an efficient number of binary digits
•Efficiently converting the source into a sequence of binary digits is a process, which is called source encoding of data compression
•Channel encoder adds some redundancy into binary information sequence that can be used for handle noise and interference effects at the receiver.
•Digital modulator maps the binary information sequence into signal waveforms.
•Communication channel is used to send the signal from the transmitter to the receiver. Physical channels: the atmosphere, wireless, optical, compact disk,….
•Digital demodulator receives transmitted signal contains the information which is corrupted by noise
•Cannel decoderattempts the reconstruct the original information sequence from knowledge of the code used by channel encoder.
•Source decoder attempts the reconstruct the original signal from the binary information sequence using the knowledge of the source encoding methods.
•The difference between the original signal and the reconstructed signal is measured of the distortion introduced by the digital communication system
•Estimate what was send, aiming at the minimum possible probability of making mistakes
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Communication Channels and their Characteristics
Physical Channel Media magnetic-electrical signaled wire channel modulated light beam optical (fiber) channel antenna radiated wireless channel acoustical signaled water channel
• Virtual Channel magnetic storage media• Noise Characteristic
thermal noise (additive noise) signal attenuation phase distortion multi-path distortion
• Limitation of Channel Usage transmitter power receiver sensitivity channel capacity (such as bandwidth)
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Communication Channels and their Characteristics
Additive Noise Channel
where α is the attenuation factor, s(t) is the transmitted signal, and n(t) is the additive random noise process.
• Called Additive Gaussian noise channel if n(t) is a Gaussian noise process.
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Overview of Wireless Systems
• Guglielmo Marconi invented the wireless telegraph in 1896
– Communication by encoding alphanumeric characters in analog signal
– Sent telegraphic signals across the Atlantic Ocean
• Communications satellites launched in 1960s
• Advances in wireless technology
– Radio, television, mobile telephone, communication satellites
• More recently
– Satellite communications, wireless networking, cellular technology
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Broadband Wireless Technology
• Higher data rates obtainable with broadband wireless technology
– Graphics, video, audio
• Shares same advantages of all wireless services: convenience and reduced cost
– Service can be deployed faster than fixed service
– No cost of cable plant
– Service is mobile, deployed almost anywhere
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Limitations and Difficulties of Wireless Technologies
• Wireless is convenient and less expensive
• Limitations and political and technical difficulties inhibit wireless technologies
• Lack of an industry-wide standard
• Device limitations
– E.g., small LCD on a mobile telephone can only displaying a few lines of text
– E.g., browsers of most mobile wireless devices use wireless markup language (WML) instead of HTML
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Electromagnetic Signal
• Function of time
• Can also be expressed as a function of frequency
– Signal consists of components of different frequencies
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Time-Domain Concepts
• Analog signal - signal intensity varies in a smooth fashion over time– No breaks or discontinuities in the signal
• Digital signal - signal intensity maintains a constant level for some period of time and then changes to another constant level
• Periodic signal - analog or digital signal pattern that repeats over time– s(t +T ) = s(t ) -< t < +
• where T is the period of the signal
• Aperiodic signal - analog or digital signal pattern that doesn't repeat over time
• Peak amplitude (A) - maximum value or strength of the signal over time; typically measured in volts
• Frequency (f )– Rate, in cycles per second, or Hertz (Hz) at which the signal repeats
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Time-Domain Concepts
• Period (T ) - amount of time it takes for one repetition of the signal– T = 1/f
• Phase () - measure of the relative position in time within a single period of a signal
• Wavelength () - distance occupied by a single cycle of the signal– Or, the distance between two points of corresponding
phase of two consecutive cycles
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Sine Wave Parameters
• General sine wave
– s(t ) = A sin(2ft + )
• Figure 2.3 shows the effect of varying each of the three parameters
– (a) A = 1, f = 1 Hz, = 0; thus T = 1s
– (b) Reduced peak amplitude; A=0.5
– (c) Increased frequency; f = 2, thus T = ½
– (d) Phase shift; = /4 radians (45 degrees)
• note: 2 radians = 360° = 1 period
Sine Wave Parameters
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Time vs. Distance
• When the horizontal axis is time, as in Figure 2.3, graphs
display the value of a signal at a given point in space as a
function of time
• With the horizontal axis in space, graphs display the value
of a signal at a given point in time as a function of distance
– At a particular instant of time, the intensity of the signal
varies as a function of distance from the source
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Frequency-Domain Concepts
• Fundamental frequency - when all frequency components
of a signal are integer multiples of one frequency, it’s
referred to as the fundamental frequency
• Spectrum - range of frequencies that a signal contains
• Absolute bandwidth - width of the spectrum of a signal
• Effective bandwidth (or just bandwidth) - narrow band of
frequencies that most of the signal’s energy is contained in
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Frequency-Domain Concepts
• Any electromagnetic signal can be shown to consist of a collection of
periodic analog signals (sine waves) at different amplitudes,
frequencies, and phases
• The period of the total signal is equal to the period of the fundamental
frequency
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Relationship between Data Rate and Bandwidth
• The greater the bandwidth, the higher the information-carrying
capacity
• Conclusions
– Any digital waveform will have infinite bandwidth
– BUT the transmission system will limit the bandwidth that can be
transmitted
– AND, for any given medium, the greater the bandwidth
transmitted, the greater the cost
– HOWEVER, limiting the bandwidth creates distortions
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Data Communication Terms
• Data - entities that convey meaning, or information
• Signals - electric or electromagnetic representations of data
• Transmission - communication of data by the propagation and
processing of signals
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Examples of Analog and Digital Data
• Analog
– Video
– Audio
• Digital
– Text
– Integers
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Analog Signals
• A continuously varying electromagnetic wave that may be
propagated over a variety of media, depending on
frequency
• Examples of media:
– Copper wire media (twisted pair and coaxial cable)
– Fiber optic cable
– Atmosphere or space propagation
• Analog signals can propagate analog and digital data
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Digital Signals
• A sequence of voltage pulses that may be transmitted over a copper
wire medium
• Generally cheaper than analog signaling
• Less susceptible to noise interference
• Suffer more from attenuation
• Digital signals can propagate analog and digital data
Analog Signaling
Digital Signaling
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Reasons for Choosing Data and Signal Combinations
• Digital data, digital signal
– Equipment for encoding is less expensive than digital-to-analog
equipment
• Analog data, digital signal
– Conversion permits use of modern digital transmission and switching
equipment
• Digital data, analog signal
– Some transmission media will only propagate analog signals
– Examples include optical fiber and satellite
• Analog data, analog signal
– Analog data easily converted to analog signal
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Analog Transmission
• Transmit analog signals without regard to content
• Attenuation limits length of transmission link
• Cascaded amplifiers boost signal’s energy for longer
distances but cause distortion
– Analog data can tolerate distortion
– Introduces errors in digital data
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Digital Transmission
• Concerned with the content of the signal
• Attenuation endangers integrity of data
• Digital Signal
– Repeaters achieve greater distance
– Repeaters recover the signal and retransmit
• Analog signal carrying digital data
– Retransmission device recovers the digital data from analog signal
– Generates new, clean analog signal
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About Channel Capacity
• Impairments, such as noise, limit data rate that can be achieved
• For digital data, to what extent do impairments limit data rate?
• Channel Capacity – the maximum rate at which data can be
transmitted over a given communication path, or channel, under given
conditions
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Concepts Related to Channel Capacity
• Data rate - rate at which data can be communicated (bps)
• Bandwidth - the bandwidth of the transmitted signal as constrained by
the transmitter and the nature of the transmission medium (Hertz)
• Noise - average level of noise over the communications path
• Error rate - rate at which errors occur
– Error = transmit 1 and receive 0; transmit 0 and receive 1
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Spread-Spectrum• Spread-spectrum techniques are methods by which energy generated in a particular
bandwidth is deliberately spread in the frequency domain, resulting in a signal with a wider bandwidth. These techniques are used for a variety of reasons, including the establishment of secure communications, increasing resistance to natural interference and jamming, and to prevent detection
• Direct-sequence spread spectrum (DSSS) is a modulation technique. As with other spread spectrum technologies, the transmitted signal takes up more bandwidth than the information signal that is being modulated. The name 'spread spectrum' comes from the fact that the carrier signals occur over the full bandwidth (spectrum) of a device's transmitting frequency.
• Frequency-hopping spread spectrum (FHSS) is a method of transmitting radio signals by rapidly switching a carrier among many frequency channels, using a pseudorandom sequence known to both transmitter and receiver.
• Code division multiple access (CDMA) describes a communication channel access principle that employs spread-spectrum technology and a special coding scheme (where each transmitter is assigned a code). By contrast, time division multiple access (TDMA) divides access by time, while frequency-division multiple access (FDMA) divides it by frequency. CDMA is a form of "spread-spectrum" signaling, since the modulated coded signal has a much higher bandwidth than the data being communicated.
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Orthogonal Frequency Division Multiplexing;
Part of xDSL, IEEE 802.11a standards
Improves Data rates, such as 56Mbps in IEEE 802.11a
Introduction to OFDM
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OFDM Concept
The information bit stream of high data rate r is Subdivided into M bit blocks that are mapped onto symbols of a lower transmission rate rs = r / M
M
Bit stream
TsTg
rs
Each Symbol has Duration Ts
and separated by guard intervals of duration Tg
Time Domain Freq Domain
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OFDM Concept
• OFDM as multicarrier system uses Discrete Fourier Transform/Fast
Fourier Transform (DFT/FFT)
• Sin(x)/x spectra for subcarriers
• Available bandwidth is divided
into very many narrow bands
~2000-8000 for digital TV
~48 for Hiperlan 2
• Data is transmitted in parallel
on these bands
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How are Signals transmitted inparallel without interference?
• Each subcarrier has a different frequency
• Frequencies chosen so that an integral number of cycles in a symbol period
• Signals are mathematically Orthogonal
First three Subcarriers
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How is data carried on the Subcarriers?
•Data is carried by varying the phase or
amplitude of each subcarrier
QPSK, 4-QAM, 16-QAM, 64-QAM
Two possible subcarrier values
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What is Multipath?
• More than one transmission path
between transmitter and receiver
• Received signal is the sum of many
versions of the transmitted signal with
varying delay and attenuation
1
0
)()(),(L
lll ttgth
)(tgl = Path Gain
),( th Chnnel Impulse Response
=
l Time delay of path l
=
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10,1
0
2)()(
NnesxN
m
N
nmj
im
in
1
01
)1(1
)1()0()( .....L
l
nLnLnnnnnnln
lnn wxhxhxhwxhy
Symbol Generation in MultiPath
l = multipath index
ms = Trnsmitted Symbol on mth Sub carrier
N = no of SubCarriers
nwAdditive White Guassian Noise at time n
=
)(lnh
Complex Random variable for lth path of channel
=
i = Symbol Iindex
)(inx
nth Sample of ith OFDM Symbol=
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Effect of Multipath on received Baseband Signal
Received signal at any time depends on a number of transmitted bits
•Inter Symbol Interference (ISI)
•Need equalizer to recover data Overlapping the delayed multipath signal with the following symbols causes Inter-Symbol-Interference ISI.
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ISI gets Worse as Data Rate Increases
ISI covers more symbol periods
• Equalizer becomes too complicated
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Dealing with ISI in OFDM
OFDM is the most powerful technique to combat ISI because of the long symbol duration
ISI is almost completely eliminated using a guard interval
FFT IntervalGI
Symbol duration
Extract a portion of an OFDM symbol at the end and append it to the beginning to maintain the subcarriers orthogonal.
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Cyclic Prefix
Each Symbol is Cyclically Extended
Some loss in efficiency as cyclic prefix carries no new information
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Cyclic Prefix: Comparision
CP
TTc
copy CP functions: •It acomodates the decaying transient of the previous symbol•It avoids the initial transient reachs the current symbol
CP
Pas
sin
g t
he
chan
nel
h(n
)
h(n)=(1)–n/n n=0,…,23
Including the Cyclic Prefix
Symbol: 8 periods of fi
Symbol: 4 periods of fi
Initial transientremains within
the CP
Final transientremains within
the CP
The inclusion of a CPmaintains the orthogonality
Pas
sin
g t
he
chan
nel
h(n
)
Initial transient Decaying transient
Channel:
Symbol: 8 periods of fi
Symbol: 4 periods of fi
Without the Cyclic Prefix
Loss of orthogonality
To combat the time dispersion: including ‘special’ time guards in the symbol transitions
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ICI effect on one Subcarrier
•Received signal in one symbol period is not a sinusoid
•Causes InterCarrier Interference (ICI)
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Uni-Magdeburg
54
ICI Elimination
• ORTHOGONALITY : Sub Carrier Orthogonality eliminates the ICI (Time-Invariant Channels) ICI (Time-Variant Channels) Additional Signal Processing at receiver side is required to eliminate ICI ….necessitate continuous monitoring of the Channel
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Uni-Magdeburg
55
Cyclic Prefix: Multipath
If multipath delay is less than the Cyclic Prefix
• No InterSymbol or InterCarrier Interference
• Amplitude may increase or decrease
Guard time Tg is chosen longer than the Channel Delay Spread τc eliminates Inter Symbol Interference, Tg >> τc
τc
Tg >> τc
τc
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Uni-Magdeburg
56
OFDM System Model
.....to OFDM Reciever
Channel
AWGN
.....Bit StreamCoding
/ Interleaving
QAM / PSK
Modulation
IFFT P/S GI
RF Front End
D/A
Transmitter
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Otto-von-Guericke
Uni-Magdeburg
57
Modulation
•Varying the complex
numbers at the IFFT input
results in modulation of
the subcarriers
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Uni-Magdeburg
58
Spectrum of Received Signal
•Multipath fading causes some frequencies to be attenuated
•Fading is approximately constant over narrow band
•This is corrected in the receiver
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Uni-Magdeburg
59
Amplitude and Phase Change
•Multipath delay causes change in amplitude and phase of each subcarrier
•Change depends on subcarrier frequency
•Corrected in receiver by one complex multiplication per subcarrier
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Uni-Magdeburg
60
Advantages
High Spectral Efficiency
Simple Implementation
Tolerant to ISI
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Uni-Magdeburg
61
Applications of OFDM Uses of OFDM
OFDM was exploited for the following applications
• Wideband Data Communications over Mobile Radio FM Channels
• High-Bit-Rate Digital Subscriber Lines (HDSL; 1.6 Mbps)
• Asymmetric Digital Subscriber Lines (ADSL; up to 6 A4bps)
• Very-High-Speed Digital Subscriber Lines (VDSL; 100 Mbps)
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Uni-Magdeburg
62
Problems with OFDM High Peak-to-Average Power
• OFDM signal is sum of many separate sinusoids
• In worst case may all add constructively
• High peaks occur rarely
• High Peak to Average Power Ratio…caused by the constructive
interference between many carriers… may occur at few time instants
within the symbol duration.
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Uni-Magdeburg
63
• Due to PAPR necessity of having very wide linearity dynamic-range for the
power amplifiers at the transmitter RF stage
Problems with OFDM
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Uni-Magdeburg
64
Problems with OFDM Frequency Offset Sensitivity
• Individual subcarriers have sin(x)/x spectrum
• Large sidelobes result in sensitivity to frequency offset
• Subcarriers no longer orthogonal
• Tight specifications on local oscillators
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Uni-Magdeburg
65
• OFDM is sensitive to frequency offsets and phase noise
• Doppler shifts cause ICI
Problems with OFDM ICI in Time Variant Channels
0 2 4 6 8 10 12 14 16 18 18.87-1
-0.5
0
0.5
1Non-orthogonality in time view
time
Magnitude
Non-orthogonality in frequency view
Frequency
Am
plit
ude
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Uni-Magdeburg
66
Solutions to ICI Channel Estimation Techniques
• Channel Estimation Techniques are applied to overcome ICI
• The estimated channel transfer function ( regularly updated
by sending pilots signals) is used to recover the ICI free signal
at the receiver
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Uni-Magdeburg
67
Solutions to Peak-to-Average Power
• Clipping the peaks
• Coding to avoid the peaks
• Peak windowing
• Predistort the signal to compensate for the amplifier nonlinearity
• But most of them are unable to achieve large rduction in PAPR with low complexity
These Techniques FAIL when the Channel Characteristics Change considerably within the Symbol Duration
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Uni-Magdeburg
68
The Alternative Technique maintains the Major Advantages of OFDM Keeping global OFDM Signal Structure
Transmitting Symbol duration Ts separated by guard intervals
Tg being longer than Maximum Channel Delay Spread τc to
eliminate ISI
A BETTER SOLUTION- AN ALTERNATIVE PROPOSED TECHNIQUE
SLTDM: Global OFDM structure Symbol Time
No ISIDelay Spread
Guard Time
… …… …… …
Sub-Symbol
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Uni-Magdeburg
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PROPOSED TECHNIQUE Different with OFDM
OFDM : Maps a data block onto corresponding Symbol using FDM Scheme SLTDM : uses Time Division Multiplexing Scheme … suggests Symbol Level Time Division Multiplexing Technique
SLTDM
The bit of M-bit block would be firstly Scrambled
Then subdivided into N equal Sub-Blocks, that would be mapped onto N Sub-Symbols
Symbol
Sub-Symbol
N1 . . .
Same Carrier fo
PSK / QAM fo
PSK / QAM fo
: fo
PSK / QAM fo
:
Delay Ts/N
Delay 2*Ts/N
Delay (N-1)*Ts/N
:
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70
PROPOSED TECHNIQUE Model of SLTDM
AWGN
.....to SLTDM Reciever
.....bit StreamCoding
/ Interleaving
QAM / PSK
Modulation
Sub Symbo
l
Sub Symbol
Seperation S / P
P/S GIRF
Front End
Channel
D/A
Time Division Multiplexing Scheme …
suggests Symbol Level Time Division Multiplexing Technique
SLTDM
Symbol Level TDM
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Uni-Magdeburg
71
PROPOSED TECHNIQUE Expected ISSI and its Resolution
To be Done
• The problem of ISSI (Inter Sub Symbol Interference) would occur
• ISSI can be eliminated, if enough information about the Channel
Characteristics is available to the receiver
• These can be gained using well known Channel Characterizing
and Channel Estimation Techniques
SLTDM benefit : All symbol have the same Envelop WaveForm
Can lead to very moderate PAPR
If the Sybmol Envelop WaveForm is properly designed