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GTUC
MASTERS IN TELECOM ENGINEERING (MTE)
COURSE: WIRELESS COMMUNICATIONS
DATE: 21st OCT 2016
COURSE CODE: MTE 507
CREDIT HOURS: 3 LECTURER:Dr. D. M. O. Adjin
OFFICE HOURS: 08:00 – 16:00 GMT
ROOM: HOD / Telecom Eng. PHONE: 020 – 269 -8175
TIME: 08:00 – 16:00 GMT E-MAIL: dadjin@gtuc.edu.gh
CHAPTER 4 – PERFORMANCE OF
DIGITAL MODULATION OVER
WIRELESS CHANNELS
 AWGN Channels
 Fading
 Doppler Spread
 Inter-Symbol-Interference
 Diversity
AWGN CHANNELS
 This section discusses the SNR and its relation to
energy per bit (Eb) & energy per symbol (Es).
 Error probability on AWGN channels is also examined for
different modulation techniques as parameterized by these
energy metrics.
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 Signal-to-Noise Power Ratio & Bit/Symbol Energy
 In an AWGN channel the modulated signal s(t) =
Re{u(t)ej2πfc t } has noise n(t) added to it prior to reception.
 The noise n(t) is a white Gaussian random process with
mean zero & power spectral density (PSD) N0 / B.
 The received signal is thus r(t) = s(t) + n(t ).
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 We define the received SNR as the ratio of the
Rx’d signal power Pr to the power of the noise
within the bandwidth of the Tx’d signal s(t).
 The Rx’d power Pr is determined by the Tx’d power & the
path loss, shadowing, & multipath fading.
 The noise power is determined by the bandwidth of the
Tx’d signal & the spectral properties of n(t ).
 If the bandwidth of the complex envelope u(t) of s(t) is B,
 Then the bandwidth of the transmitted signal s(t) is 2B.
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 Since the noise n(t) has uniform PSD N0/B,
 The total noise power within the bandwidth 2B is N =
N0/B · 2B = N0B. Hence the received SNR is given by:
SNR = Pr / N0B
 In systems with interference, we often use the Rx’d signal-
to-interference-plus-noise power ratio (SINR) in place of
SNR for calculating error probability.
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 This is a reasonable approximation if the
interference statistics approximate those of
Gaussian noise.
 The received SINR is given by: SINR = Pr / (N0B
+ Pi ),
 Where Pi is the average power of the interference.
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 The SNR is often expressed in terms of the signal energy
per bit Eb (or per symbol, Es) as:
SNR = Pr /N0B = Es/N0BTs = Eb / N0BTb
 Where:
 Ts is the symbol time
 Tb is the bit time (for binary modulation Ts = Tb and Es
= Eb).
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 For pulse shaping with Ts =1/B (e.g., raised cosine pulses
with β =1),
 We have SNR = Es/N0 for multilevel signaling and SNR
= Eb/N0 for binary signaling.
 For general pulses, Ts = k/B for some constant k, in which
case k · SNR = Es/N0.
 The quantities γs = Es/N0 and γb = Eb/N0 are sometimes
called the SNR per symbol & the SNR per bit,
respectively.
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 For performance specification, we are interested in the bit
error probability Pb as a function of γb.
 With M-ary signalling (e.g., MPAM & MPSK) the Pb
depends on both the symbol error probability & the
mapping of bits to symbols.
 Thus, we typically compute the symbol error
probability Ps as a function of γs based on the signal
space concepts
 Then obtain Pb as a function of γb using an exact or
approximate conversion.
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 The approximate conversion typically assumes that,
 The symbol energy is divided equally among all bits
 Gray encoding is used, so that (at reasonable SNRs) one symbol
error corresponds to exactly one bit error.
 These assumptions for M-ary signaling lead to the
approximations
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Error Probability for BPSK & QPSK
 We first consider BPSK modulation with coherent
detection & perfect recovery of the carrier freq & phase.
 With binary modulation each symbol corresponds to
one bit, so the symbol & bit error rates are the same.
 The Tx’d signal is s1(t) = Ag(t ) cos(2πfc t) to send a 0-bit
and s2(t) = −Ag(t ) cos(2πfc t) to send a 1-bit for A > 0.
 Thus, Pb = Q(√dmin / 2N0)
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 dmin = s1 − s0 = A − (−A) = 2A.
 Let us now relate A to the energy per bit.
 We have:
 Thus, the signal constellation for BPSK in terms of energy
per bit is given by s0 = √Eb and s1 = − √Eb.
 This yields the minimum distance dmin = 2A = 2√Eb.
 By Substitution yields:
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 QPSK modulation consists of BPSK modulation on both
the in-phase & quadrature components of the signal.
 With perfect phase & carrier recovery, the received signal
components corresponding to each of these branches are
orthogonal.
 Therefore, the bit error probability on each branch is
the same as for BPSK: Pb = Q(√2γb)
 The symbol error probability equals the probability that
either branch has a bit error:
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FADING
 In AWGN the probability of symbol error depends
on the received SNR or, equivalently, on γs .
 In a fading environment,
 The Prx varies randomly over distance or time as a result of
shadowing and/or multipath fading.
 Thus, in fading, γs is a random variable with distribution
pγs(γ ) , thus, Ps(γs) is also random.
 The performance metric when γs is random depends on the
rate of change of the fading.
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 There are three different performance criteria that
can be used to characterize the random variable Ps :
 The outage probability, Pout, defined as the probability that γs falls
below a given value corresponding to the maximum allowable
Ps ;
 The average error probability, Ps
- , averaged over the distribution of
γs;
 Combined average error probability & outage,
 Defined as the average error probability that can be achieved
some percentage of time or spatial locations.
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 The Average Probability Of Symbol Error Applies When
The Fading Coherence Time Is On The Order Of A
Symbol Time (Ts ≈ Tc),
 Thus, The Signal Fade Level Is Roughly Constant Over
A Symbol Period.
 The Average Error Probability Is A Reasonably Good
Figure Of Merit For The Channel Quality Under These
Conditions.
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 If The Signal Fading Is Changing Slowly (Ts << Tc) Then
A Deep Fade Will Affect Many Simultaneous Symbols.
 Thus, Fading May Lead To Large Error Bursts,
 Which Cannot Be Corrected For With Coding Of Reasonable
Complexity.
 Hence, These Error Bursts Can Seriously Degrade End-to-
end Performance.
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 Outage & Average Error Probability Are Often
Combined,
 When The Channel Is Modeled As A Combination Of Fast & Slow
Fading
E.g., Log-normal Shadowing With Fast Rayleigh Fading.
 Note That,
 If Tc << Ts, Then The Fading Will Be Averaged Out By
The Matched Filter In The Demodulator.
 Thus, For Very Fast Fading, Performance Is The Same As
In AWGN.
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Outage Probability
 The outage probability relative to γ0 is defined
as:
Where γ0 typically specifies the minimum
SNR required for acceptable performance.
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 For example, if we consider digitized voice, Pb = 10−3
is an acceptable error rate
 It Can’t Be Detected By The Human Ear.
 Thus, for a BPSK signal in Rayleigh fading,
γb < 7 dB would be declared an outage;
hence we obtain γ0 = 7 dB.
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 In Rayleigh fading the outage probability
becomes:
 Inverting this formula shows that, for a given
outage probability, the required average SNR
 γ-
s is:
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 In decibels this means that,
10 log γs must exceed the target 10 log γ0 by Fd = −10
log[−ln(1− Pout )],
In order to maintain acceptable performance more
than 100(1− Pout ) percent of the time.
 The quantity Fd is known as the dB Fade Margin.
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Average Probability of Error
 The average probability of error is used as a
performance metric when Ts ≈ Tc.
 Thus, assume that γs is constant over a symbol time.
 Then the average probability of error is computed by
integrating the error probability in AWGN over the
fading distribution:
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 Where Ps(γ ) is the probability of symbol error
inAWGN with SNR γ,
 For a given distribution of the fading amplitude r
E.g., In Rayleigh, Rician & log-normal, we compute pγs(γ )
by making the change of variable:
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 Combined Outage and Average Error Probability
 When The Fading Environment Is A Superposition Of
Both Fast And Slow Fading (E.g., Log-normal Shadowing
& Rayleigh Fading),
A Common Performance Metric Is, “Combined Outage
& Average Error Probability”,
Where Outage Occurs When The Slow Fading Falls Below
Some Target Value And The Average Performance In Non-
outage Is Obtained By Averaging Over The Fast Fading.
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 We Use The Following Notation:
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 We can specify an average error probability P-
s with some
probability 1 − Pout.
 An outage is declared,
 When the received SNR per symbol due to shadowing &
path loss alone, γ-
s , falls below a given target value γ-
s0 .
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 When not in outage (γ-
s ≥ γ-
s0 ),
The average probability of error is obtained by
averaging over the distribution of the fast fading
conditioned on the mean SNR:
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 The criterion used to determine the outage target γ-
s0 is
typically based on a given maximum acceptable average
probability of error P
-s0 .
 The threshold γ-
s0 must then satisfy the average probability
model below:
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DOPPLER SPREAD (DS)
 DS Is The Range Of Freqs Over Which The Rx’ved
Spectrum Is Essentially Non-zero.
 It Is The Measure Of Spectral Broadening Caused By The Time Rate
Of Change Of Mobile Radio Channel.
 One Consequence Of DS Is An Irreducible Error Floor For
Modulation Techniques,
 Using Differential Detection.
 Since In Differential Modulation The Signal Phase Associated
With One Symbol Is Used As A Phase Reference For The
Next Symbol.
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 If The Channel Phase Decorrelates Over A Symbol,
 Then The Phase Reference Becomes Extremely Noisy,
 Leading To A High Symbol Error Rate That Is Independent Of Prx.
 The Phase Correlation B/n Symbols & Consequent
Degradation In Performance Are Functions Of The
Doppler Frequency fD = v/λ & the symbol time Ts .
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 The channel correlation AC(τ ) over time τ equals the
inverse Fourier Transform of the Doppler power spectrum
SC(f )
As a function of Doppler frequency f.
 The correlation coefficient is thus ρC = AC(T )/AC(0)
evaluated at T = Ts for DQPSK
or at T = Tb for DPSK.
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INTER-SYMBOL-INTERFERENCE (ISI)
 Inter-symbol Interference Frequency-selective
fading gives rise to ISI,
 Where the received symbol over a given symbol period
experiences interference from other symbols that have
been delayed by multipath.
 Since increasing signal power also increases the
power of the ISI,
 This interference gives rise to an irreducible error floor
that is independent of signal power.
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 An approximation to symbol error probability with
ISI can be obtained by,
 Treating the ISI as uncorrelated white Gaussian noise.
 Then the SNR becomes:
 Where;
Pr is the received power associated with the LOS signal
component,
I is the received power associated with the ISI.
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 In a static channel,
 The resulting probability of symbol error will be
Ps(γˆs), where Ps is the probability of symbol error in
AWGN.
 If both the LOS signal component & the ISI experience flat
fading,
 Then γˆs will be a random variable with distribution
p(γˆs),
The average symbol error probability is then;
 P-s = Ps(γˆs)p(γˆs) dγs .
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 Note that,
 γˆs is the ratio of two random variables – the
LOS received power Pr & the ISI received
power I,
The resulting distribution p(γˆs) may be hard to
obtain
 Irreducible error floors due to ISI are often obtained by
simulation, which can easily
 incorporate different channel models, modulation formats,
and symbol sequence characteristics
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 Irreducible error floors due to ISI are often obtained by
simulation,
 Which Can Easily Incorporate Different Channel
Models, Modulation Formats & Symbol Sequence
Characteristics
 BPSK, DPSK, QPSK, OQPSK & MSK modulations are
simulated for:
 Different Pulse Shapes
 Channels With Different Power Delay Profiles, Including A
Gaussian, Exponential, Equal-amplitude Two-ray,
 Empirical Power Delay Profile.
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 The Simulation results indicate that;
The irreducible error floor is more sensitive to the rms
delay spread of the channel than to the shape of its
power delay profile.
Pulse shaping can significantly impact the error floor:
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DIVERSITY
 We Observed From The Fading Section That,
 Both Rayleigh Fading & Log-normal Shadowing Exact
A Large Power Penalty On The Performance Of
Modulation Over Wireless Channels.
 One Of The Best Techniques To Mitigate The Effects Of
Fading Is Diversity Combination Of Independently Fading
Signal Paths.
Diversity Combination Exploits The Fact That:
Independent Signal Paths Have A Low Probability
Of Experiencing Deep Fades Simultaneously.
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 Thus,
The Idea Behind Diversity Is To Send The Same
Data Over Independent Fading Paths.
These Independent Paths Are Combined In Such A
Way That The Fading Of The Resultant Signal Is
Reduced.
 Hence,
 The Main Purpose Of Diversity Is To:
 Coherently Combine Independent Fading Paths To
Alleviate The Effects Of Fading In Wireless Channels.
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 E.g., Assume A System With Two Antennas At
Either The Tx’r Or Rx’r That Experience
Independent Fading.
If The Antennas Are Spaced Sufficiently Far Apart, It
Is Unlikely That They Both Experience Deep Fades At
The Same Time.
 By Selecting The Antenna With The Strongest Signal, A
Technique Known As Selection Combining,
 We Obtain A Much Better Signal Than If We Had Just
One Antenna.
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 Diversity techniques that mitigate the effect of multipath
fading are called Micro-diversity,
 Diversity to mitigate the effects of shadowing from
buildings and objects is called Macro-diversity.
 Macro-diversity is generally implemented by combining
signals received by several BTSs or RAPs,
 Which requires coordination among these different
stations or points.
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 Such coordination is implemented.
 As Part Of The Networking Protocols In
Infrastructure-based Wireless Networks.
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Realization of Independent Fading Paths
 There Are Many Ways Of Achieving Independent
Fading Paths In A Wireless System.
One Method Is To Use Multiple Transmit Or Receive
Antennas, Also Called An Antenna Array,
Where The Elements Of The Array Are Separated In
Distance.
This Type Of Diversity Is Referred To As Space Diversity.
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 The maximum diversity gain for either Tx’r
or Rx’r space diversity typically requires that,
 The separation b/n antennas be such that the fading
amplitudes corresponding to each antenna are
approximately independent.
 A second method of achieving diversity is by using either two
Tx’t antennas or two Rx’e antennas with different
polarization
E.g., vertically and horizontally polarized waves
The two transmitted waves follow the same path.
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 A second method of achieving diversity is by using either
two Tx’t antennas or two Rx’e antennas with different
polarization
E.g., vertically and horizontally polarized waves
The two transmitted waves follow the same path.
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 Freq Diversity
 It is achieved by Tx’g the same narrowband signal at
different carrier freqs, where the carriers are separated by
the coherence bandwidth of the channel.
 This technique requires additional transmit power to send
the signal over multiple freq bands.
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Typical Freq Diversity Diagram
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 Time Diversity
 This Is Achieved By:
 Tx’g The Same Signal At Different Times,
 Where The Time Difference Is Greater Than The
Channel Coherence Time (The Inverse Of The Channel
Doppler Spread).
 It Does Not Require Increased Ptx,
 But It Lowers Data Rates, Since Data Is Repeated In The Diversity
Time Slots Rather Than Sending New Data In Those Time Slots.
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Typical Time Diversity Diagram
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Receiver Diversity
 In receiver diversity,
 The independent fading paths associated with multiple
receive antennas are combined to obtain a signal that is
then passed thro’ a standard demodulator.
 The combination vary in complexity & overall
performance.
 Most combining techniques are linear:
 The O/p of the combiner is just a weighted sum of the
different fading paths as shown below for M-branch
diversity
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 Combining more than one branch signal
requires co-phasing,
 where the phase θi of the ith branch is removed
through multiplication by αi = ai e−jθi for some
real-valued ai.
 This phase removal requires coherent detection of
each branch to determine its phase θi.
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 Linear combiner
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 Without Co-phasing,
The Branch Signals Would Not Add Up
Coherently In The Combiner,
Hence,
The Resulting Output Could Still Exhibit Significant
Fading Due To Constructive And Destructive
Addition Of The Signals In All The Branches.
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 Transmitter Diversity
 Here, There Are Multiple Transmit Antennas, & The Pt Is
Divided Among These Antennas.
 Transmit Diversity Is Desirable In Systems Where,
More Space, Power, & Processing Capability Are
Available On The Transmit Side Than On The Receive
Side, As In Cellular Systems.
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 Transmit diversity design depends on whether or not the
complex channel gain is known to the transmitter.
When this gain is known, the system is quite similar to
receiver diversity.
 Without this channel knowledge,
 Transmit diversity gain requires a combination of space
& time diversity via a novel technique called the
Alamouti scheme and its extensions.
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 Typical Transmit diversity Diagram
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END OF CHAPTER FOUR
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CHAPTER 4 updated.ppt. Wireless communication

  • 1.
    15/05/2008 18:10:18 Academicexcellence in ICT Education 1 GTUC MASTERS IN TELECOM ENGINEERING (MTE) COURSE: WIRELESS COMMUNICATIONS DATE: 21st OCT 2016 COURSE CODE: MTE 507 CREDIT HOURS: 3 LECTURER:Dr. D. M. O. Adjin OFFICE HOURS: 08:00 – 16:00 GMT ROOM: HOD / Telecom Eng. PHONE: 020 – 269 -8175 TIME: 08:00 – 16:00 GMT E-MAIL: dadjin@gtuc.edu.gh
  • 2.
    CHAPTER 4 –PERFORMANCE OF DIGITAL MODULATION OVER WIRELESS CHANNELS  AWGN Channels  Fading  Doppler Spread  Inter-Symbol-Interference  Diversity
  • 3.
    AWGN CHANNELS  Thissection discusses the SNR and its relation to energy per bit (Eb) & energy per symbol (Es).  Error probability on AWGN channels is also examined for different modulation techniques as parameterized by these energy metrics. 15/05/2008 18:10:18 Academic excellence in ICT Education 3
  • 4.
     Signal-to-Noise PowerRatio & Bit/Symbol Energy  In an AWGN channel the modulated signal s(t) = Re{u(t)ej2πfc t } has noise n(t) added to it prior to reception.  The noise n(t) is a white Gaussian random process with mean zero & power spectral density (PSD) N0 / B.  The received signal is thus r(t) = s(t) + n(t ). 15/05/2008 18:10:18 Academic excellence in ICT Education 4
  • 5.
     We definethe received SNR as the ratio of the Rx’d signal power Pr to the power of the noise within the bandwidth of the Tx’d signal s(t).  The Rx’d power Pr is determined by the Tx’d power & the path loss, shadowing, & multipath fading.  The noise power is determined by the bandwidth of the Tx’d signal & the spectral properties of n(t ).  If the bandwidth of the complex envelope u(t) of s(t) is B,  Then the bandwidth of the transmitted signal s(t) is 2B. 15/05/2008 18:10:18 Academic excellence in ICT Education 5
  • 6.
     Since thenoise n(t) has uniform PSD N0/B,  The total noise power within the bandwidth 2B is N = N0/B · 2B = N0B. Hence the received SNR is given by: SNR = Pr / N0B  In systems with interference, we often use the Rx’d signal- to-interference-plus-noise power ratio (SINR) in place of SNR for calculating error probability. 15/05/2008 18:10:18 Academic excellence in ICT Education 6
  • 7.
     This isa reasonable approximation if the interference statistics approximate those of Gaussian noise.  The received SINR is given by: SINR = Pr / (N0B + Pi ),  Where Pi is the average power of the interference. 15/05/2008 18:10:18 Academic excellence in ICT Education 7
  • 8.
     The SNRis often expressed in terms of the signal energy per bit Eb (or per symbol, Es) as: SNR = Pr /N0B = Es/N0BTs = Eb / N0BTb  Where:  Ts is the symbol time  Tb is the bit time (for binary modulation Ts = Tb and Es = Eb). 15/05/2008 18:10:18 Academic excellence in ICT Education 8
  • 9.
     For pulseshaping with Ts =1/B (e.g., raised cosine pulses with β =1),  We have SNR = Es/N0 for multilevel signaling and SNR = Eb/N0 for binary signaling.  For general pulses, Ts = k/B for some constant k, in which case k · SNR = Es/N0.  The quantities γs = Es/N0 and γb = Eb/N0 are sometimes called the SNR per symbol & the SNR per bit, respectively. 15/05/2008 18:10:18 Academic excellence in ICT Education 9
  • 10.
     For performancespecification, we are interested in the bit error probability Pb as a function of γb.  With M-ary signalling (e.g., MPAM & MPSK) the Pb depends on both the symbol error probability & the mapping of bits to symbols.  Thus, we typically compute the symbol error probability Ps as a function of γs based on the signal space concepts  Then obtain Pb as a function of γb using an exact or approximate conversion. 15/05/2008 18:10:18 Academic excellence in ICT Education 10
  • 11.
     The approximateconversion typically assumes that,  The symbol energy is divided equally among all bits  Gray encoding is used, so that (at reasonable SNRs) one symbol error corresponds to exactly one bit error.  These assumptions for M-ary signaling lead to the approximations 15/05/2008 18:10:18 Academic excellence in ICT Education 11
  • 12.
    Error Probability forBPSK & QPSK  We first consider BPSK modulation with coherent detection & perfect recovery of the carrier freq & phase.  With binary modulation each symbol corresponds to one bit, so the symbol & bit error rates are the same.  The Tx’d signal is s1(t) = Ag(t ) cos(2πfc t) to send a 0-bit and s2(t) = −Ag(t ) cos(2πfc t) to send a 1-bit for A > 0.  Thus, Pb = Q(√dmin / 2N0) 15/05/2008 18:10:18 Academic excellence in ICT Education 12
  • 13.
     dmin =s1 − s0 = A − (−A) = 2A.  Let us now relate A to the energy per bit.  We have:  Thus, the signal constellation for BPSK in terms of energy per bit is given by s0 = √Eb and s1 = − √Eb.  This yields the minimum distance dmin = 2A = 2√Eb.  By Substitution yields: 15/05/2008 18:10:18 Academic excellence in ICT Education 13
  • 14.
     QPSK modulationconsists of BPSK modulation on both the in-phase & quadrature components of the signal.  With perfect phase & carrier recovery, the received signal components corresponding to each of these branches are orthogonal.  Therefore, the bit error probability on each branch is the same as for BPSK: Pb = Q(√2γb)  The symbol error probability equals the probability that either branch has a bit error: 15/05/2008 18:10:18 Academic excellence in ICT Education 14
  • 15.
    FADING  In AWGNthe probability of symbol error depends on the received SNR or, equivalently, on γs .  In a fading environment,  The Prx varies randomly over distance or time as a result of shadowing and/or multipath fading.  Thus, in fading, γs is a random variable with distribution pγs(γ ) , thus, Ps(γs) is also random.  The performance metric when γs is random depends on the rate of change of the fading. 15/05/2008 18:10:18 Academic excellence in ICT Education 15
  • 16.
     There arethree different performance criteria that can be used to characterize the random variable Ps :  The outage probability, Pout, defined as the probability that γs falls below a given value corresponding to the maximum allowable Ps ;  The average error probability, Ps - , averaged over the distribution of γs;  Combined average error probability & outage,  Defined as the average error probability that can be achieved some percentage of time or spatial locations. 15/05/2008 18:10:18 Academic excellence in ICT Education 16
  • 17.
     The AverageProbability Of Symbol Error Applies When The Fading Coherence Time Is On The Order Of A Symbol Time (Ts ≈ Tc),  Thus, The Signal Fade Level Is Roughly Constant Over A Symbol Period.  The Average Error Probability Is A Reasonably Good Figure Of Merit For The Channel Quality Under These Conditions. 15/05/2008 18:10:18 Academic excellence in ICT Education 17
  • 18.
     If TheSignal Fading Is Changing Slowly (Ts << Tc) Then A Deep Fade Will Affect Many Simultaneous Symbols.  Thus, Fading May Lead To Large Error Bursts,  Which Cannot Be Corrected For With Coding Of Reasonable Complexity.  Hence, These Error Bursts Can Seriously Degrade End-to- end Performance. 15/05/2008 18:10:18 Academic excellence in ICT Education 18
  • 19.
     Outage &Average Error Probability Are Often Combined,  When The Channel Is Modeled As A Combination Of Fast & Slow Fading E.g., Log-normal Shadowing With Fast Rayleigh Fading.  Note That,  If Tc << Ts, Then The Fading Will Be Averaged Out By The Matched Filter In The Demodulator.  Thus, For Very Fast Fading, Performance Is The Same As In AWGN. 15/05/2008 18:10:18 Academic excellence in ICT Education 19
  • 20.
    Outage Probability  Theoutage probability relative to γ0 is defined as: Where γ0 typically specifies the minimum SNR required for acceptable performance. 15/05/2008 18:10:18 Academic excellence in ICT Education 20
  • 21.
     For example,if we consider digitized voice, Pb = 10−3 is an acceptable error rate  It Can’t Be Detected By The Human Ear.  Thus, for a BPSK signal in Rayleigh fading, γb < 7 dB would be declared an outage; hence we obtain γ0 = 7 dB. 15/05/2008 18:10:18 Academic excellence in ICT Education 21
  • 22.
     In Rayleighfading the outage probability becomes:  Inverting this formula shows that, for a given outage probability, the required average SNR  γ- s is: 15/05/2008 18:10:18 Academic excellence in ICT Education 22
  • 23.
     In decibelsthis means that, 10 log γs must exceed the target 10 log γ0 by Fd = −10 log[−ln(1− Pout )], In order to maintain acceptable performance more than 100(1− Pout ) percent of the time.  The quantity Fd is known as the dB Fade Margin. 15/05/2008 18:10:18 Academic excellence in ICT Education 23
  • 24.
    Average Probability ofError  The average probability of error is used as a performance metric when Ts ≈ Tc.  Thus, assume that γs is constant over a symbol time.  Then the average probability of error is computed by integrating the error probability in AWGN over the fading distribution: 15/05/2008 18:10:18 Academic excellence in ICT Education 24
  • 25.
     Where Ps(γ) is the probability of symbol error inAWGN with SNR γ,  For a given distribution of the fading amplitude r E.g., In Rayleigh, Rician & log-normal, we compute pγs(γ ) by making the change of variable: 15/05/2008 18:10:18 Academic excellence in ICT Education 25
  • 26.
     Combined Outageand Average Error Probability  When The Fading Environment Is A Superposition Of Both Fast And Slow Fading (E.g., Log-normal Shadowing & Rayleigh Fading), A Common Performance Metric Is, “Combined Outage & Average Error Probability”, Where Outage Occurs When The Slow Fading Falls Below Some Target Value And The Average Performance In Non- outage Is Obtained By Averaging Over The Fast Fading. 15/05/2008 18:10:18 Academic excellence in ICT Education 26
  • 27.
     We UseThe Following Notation: 15/05/2008 18:10:18 Academic excellence in ICT Education 27
  • 28.
     We canspecify an average error probability P- s with some probability 1 − Pout.  An outage is declared,  When the received SNR per symbol due to shadowing & path loss alone, γ- s , falls below a given target value γ- s0 . 15/05/2008 18:10:18 Academic excellence in ICT Education 28
  • 29.
     When notin outage (γ- s ≥ γ- s0 ), The average probability of error is obtained by averaging over the distribution of the fast fading conditioned on the mean SNR: 15/05/2008 18:10:18 Academic excellence in ICT Education 29
  • 30.
     The criterionused to determine the outage target γ- s0 is typically based on a given maximum acceptable average probability of error P -s0 .  The threshold γ- s0 must then satisfy the average probability model below: 15/05/2008 18:10:18 Academic excellence in ICT Education 30
  • 31.
    DOPPLER SPREAD (DS) DS Is The Range Of Freqs Over Which The Rx’ved Spectrum Is Essentially Non-zero.  It Is The Measure Of Spectral Broadening Caused By The Time Rate Of Change Of Mobile Radio Channel.  One Consequence Of DS Is An Irreducible Error Floor For Modulation Techniques,  Using Differential Detection.  Since In Differential Modulation The Signal Phase Associated With One Symbol Is Used As A Phase Reference For The Next Symbol. 15/05/2008 18:10:18 Academic excellence in ICT Education 31
  • 32.
     If TheChannel Phase Decorrelates Over A Symbol,  Then The Phase Reference Becomes Extremely Noisy,  Leading To A High Symbol Error Rate That Is Independent Of Prx.  The Phase Correlation B/n Symbols & Consequent Degradation In Performance Are Functions Of The Doppler Frequency fD = v/λ & the symbol time Ts . 15/05/2008 18:10:18 Academic excellence in ICT Education 32
  • 33.
     The channelcorrelation AC(τ ) over time τ equals the inverse Fourier Transform of the Doppler power spectrum SC(f ) As a function of Doppler frequency f.  The correlation coefficient is thus ρC = AC(T )/AC(0) evaluated at T = Ts for DQPSK or at T = Tb for DPSK. 15/05/2008 18:10:18 Academic excellence in ICT Education 33
  • 34.
    INTER-SYMBOL-INTERFERENCE (ISI)  Inter-symbolInterference Frequency-selective fading gives rise to ISI,  Where the received symbol over a given symbol period experiences interference from other symbols that have been delayed by multipath.  Since increasing signal power also increases the power of the ISI,  This interference gives rise to an irreducible error floor that is independent of signal power. 15/05/2008 18:10:18 Academic excellence in ICT Education 34
  • 35.
     An approximationto symbol error probability with ISI can be obtained by,  Treating the ISI as uncorrelated white Gaussian noise.  Then the SNR becomes:  Where; Pr is the received power associated with the LOS signal component, I is the received power associated with the ISI. 15/05/2008 18:10:18 Academic excellence in ICT Education 35
  • 36.
     In astatic channel,  The resulting probability of symbol error will be Ps(γˆs), where Ps is the probability of symbol error in AWGN.  If both the LOS signal component & the ISI experience flat fading,  Then γˆs will be a random variable with distribution p(γˆs), The average symbol error probability is then;  P-s = Ps(γˆs)p(γˆs) dγs . 15/05/2008 18:10:18 Academic excellence in ICT Education 36
  • 37.
     Note that, γˆs is the ratio of two random variables – the LOS received power Pr & the ISI received power I, The resulting distribution p(γˆs) may be hard to obtain  Irreducible error floors due to ISI are often obtained by simulation, which can easily  incorporate different channel models, modulation formats, and symbol sequence characteristics 15/05/2008 18:10:18 Academic excellence in ICT Education 37
  • 38.
     Irreducible errorfloors due to ISI are often obtained by simulation,  Which Can Easily Incorporate Different Channel Models, Modulation Formats & Symbol Sequence Characteristics  BPSK, DPSK, QPSK, OQPSK & MSK modulations are simulated for:  Different Pulse Shapes  Channels With Different Power Delay Profiles, Including A Gaussian, Exponential, Equal-amplitude Two-ray,  Empirical Power Delay Profile. 15/05/2008 18:10:18 Academic excellence in ICT Education 38
  • 39.
     The Simulationresults indicate that; The irreducible error floor is more sensitive to the rms delay spread of the channel than to the shape of its power delay profile. Pulse shaping can significantly impact the error floor: 15/05/2008 18:10:18 Academic excellence in ICT Education 39
  • 40.
    DIVERSITY  We ObservedFrom The Fading Section That,  Both Rayleigh Fading & Log-normal Shadowing Exact A Large Power Penalty On The Performance Of Modulation Over Wireless Channels.  One Of The Best Techniques To Mitigate The Effects Of Fading Is Diversity Combination Of Independently Fading Signal Paths. Diversity Combination Exploits The Fact That: Independent Signal Paths Have A Low Probability Of Experiencing Deep Fades Simultaneously. 15/05/2008 18:10:18 Academic excellence in ICT Education 40
  • 41.
     Thus, The IdeaBehind Diversity Is To Send The Same Data Over Independent Fading Paths. These Independent Paths Are Combined In Such A Way That The Fading Of The Resultant Signal Is Reduced.  Hence,  The Main Purpose Of Diversity Is To:  Coherently Combine Independent Fading Paths To Alleviate The Effects Of Fading In Wireless Channels. 15/05/2008 18:10:18 Academic excellence in ICT Education 41
  • 42.
     E.g., AssumeA System With Two Antennas At Either The Tx’r Or Rx’r That Experience Independent Fading. If The Antennas Are Spaced Sufficiently Far Apart, It Is Unlikely That They Both Experience Deep Fades At The Same Time.  By Selecting The Antenna With The Strongest Signal, A Technique Known As Selection Combining,  We Obtain A Much Better Signal Than If We Had Just One Antenna. 15/05/2008 18:10:18 Academic excellence in ICT Education 42
  • 43.
     Diversity techniquesthat mitigate the effect of multipath fading are called Micro-diversity,  Diversity to mitigate the effects of shadowing from buildings and objects is called Macro-diversity.  Macro-diversity is generally implemented by combining signals received by several BTSs or RAPs,  Which requires coordination among these different stations or points. 15/05/2008 18:10:18 Academic excellence in ICT Education 43
  • 44.
     Such coordinationis implemented.  As Part Of The Networking Protocols In Infrastructure-based Wireless Networks. 15/05/2008 18:10:18 Academic excellence in ICT Education 44
  • 45.
    Realization of IndependentFading Paths  There Are Many Ways Of Achieving Independent Fading Paths In A Wireless System. One Method Is To Use Multiple Transmit Or Receive Antennas, Also Called An Antenna Array, Where The Elements Of The Array Are Separated In Distance. This Type Of Diversity Is Referred To As Space Diversity. 15/05/2008 18:10:18 Academic excellence in ICT Education 45
  • 46.
     The maximumdiversity gain for either Tx’r or Rx’r space diversity typically requires that,  The separation b/n antennas be such that the fading amplitudes corresponding to each antenna are approximately independent.  A second method of achieving diversity is by using either two Tx’t antennas or two Rx’e antennas with different polarization E.g., vertically and horizontally polarized waves The two transmitted waves follow the same path. 15/05/2008 18:10:18 Academic excellence in ICT Education 46
  • 47.
     A secondmethod of achieving diversity is by using either two Tx’t antennas or two Rx’e antennas with different polarization E.g., vertically and horizontally polarized waves The two transmitted waves follow the same path. 15/05/2008 18:10:18 Academic excellence in ICT Education 47
  • 48.
     Freq Diversity It is achieved by Tx’g the same narrowband signal at different carrier freqs, where the carriers are separated by the coherence bandwidth of the channel.  This technique requires additional transmit power to send the signal over multiple freq bands. 15/05/2008 18:10:18 Academic excellence in ICT Education 48
  • 49.
    Typical Freq DiversityDiagram 15/05/2008 18:10:18 Academic excellence in ICT Education 49
  • 50.
     Time Diversity This Is Achieved By:  Tx’g The Same Signal At Different Times,  Where The Time Difference Is Greater Than The Channel Coherence Time (The Inverse Of The Channel Doppler Spread).  It Does Not Require Increased Ptx,  But It Lowers Data Rates, Since Data Is Repeated In The Diversity Time Slots Rather Than Sending New Data In Those Time Slots. 15/05/2008 18:10:18 Academic excellence in ICT Education 50
  • 51.
    Typical Time DiversityDiagram 15/05/2008 18:10:18 Academic excellence in ICT Education 51
  • 52.
    Receiver Diversity  Inreceiver diversity,  The independent fading paths associated with multiple receive antennas are combined to obtain a signal that is then passed thro’ a standard demodulator.  The combination vary in complexity & overall performance.  Most combining techniques are linear:  The O/p of the combiner is just a weighted sum of the different fading paths as shown below for M-branch diversity 15/05/2008 18:10:18 Academic excellence in ICT Education 52
  • 53.
     Combining morethan one branch signal requires co-phasing,  where the phase θi of the ith branch is removed through multiplication by αi = ai e−jθi for some real-valued ai.  This phase removal requires coherent detection of each branch to determine its phase θi. 15/05/2008 18:10:18 Academic excellence in ICT Education 53
  • 54.
     Linear combiner 15/05/200818:10:18 Academic excellence in ICT Education 54
  • 55.
     Without Co-phasing, TheBranch Signals Would Not Add Up Coherently In The Combiner, Hence, The Resulting Output Could Still Exhibit Significant Fading Due To Constructive And Destructive Addition Of The Signals In All The Branches. 15/05/2008 18:10:18 Academic excellence in ICT Education 55
  • 56.
     Transmitter Diversity Here, There Are Multiple Transmit Antennas, & The Pt Is Divided Among These Antennas.  Transmit Diversity Is Desirable In Systems Where, More Space, Power, & Processing Capability Are Available On The Transmit Side Than On The Receive Side, As In Cellular Systems. 15/05/2008 18:10:18 Academic excellence in ICT Education 56
  • 57.
     Transmit diversitydesign depends on whether or not the complex channel gain is known to the transmitter. When this gain is known, the system is quite similar to receiver diversity.  Without this channel knowledge,  Transmit diversity gain requires a combination of space & time diversity via a novel technique called the Alamouti scheme and its extensions. 15/05/2008 18:10:18 Academic excellence in ICT Education 57
  • 58.
     Typical Transmitdiversity Diagram 15/05/2008 18:10:18 Academic excellence in ICT Education 58
  • 59.
    END OF CHAPTERFOUR 15/05/2008 18:10:18 Academic excellence in ICT Education 59