This document discusses carrier synchronization techniques in digital communication systems. It begins with an introduction to the need for carrier recovery and symbol synchronization at the receiver. It then covers maximum likelihood estimation of signal parameters including carrier phase. Next, it describes carrier phase estimation using a phase-locked loop and decision-directed loops. It explains how the phase-locked loop works to continuously track and update the carrier phase estimate. Finally, it provides an example of decision-directed carrier phase estimation for a double-sideband suppressed carrier pulse amplitude modulation signal.
In communication system, intersymbol interference (ISI) is a form of distortion of a signal in which one symbol interferes with subsequent symbols. This is an unwanted phenomenon as the previous symbols have similar effect as noise, thus making the communication less reliable.
In communication system, the Nyquist ISI criterion describes the conditions which when satisfied by a communication channel (including responses of transmit and receive filters), result in no intersymbol interference(ISI). It provides a method for constructing band-limited functions to overcome the effects of intersymbol interference.
Base band transmission
*Wave form representation of binary digits
*PCM, DPCM, DM, ADM systems
*Detection of signals in Gaussian noise
*Matched filter - Application of matched filter
*Error probability performance of binary signaling
*Multilevel base band transmission
*Inter symbol interference
*Eye pattern
*Companding
*A law and μ law
*Correlation receiver
In communication system, intersymbol interference (ISI) is a form of distortion of a signal in which one symbol interferes with subsequent symbols. This is an unwanted phenomenon as the previous symbols have similar effect as noise, thus making the communication less reliable.
In communication system, the Nyquist ISI criterion describes the conditions which when satisfied by a communication channel (including responses of transmit and receive filters), result in no intersymbol interference(ISI). It provides a method for constructing band-limited functions to overcome the effects of intersymbol interference.
Base band transmission
*Wave form representation of binary digits
*PCM, DPCM, DM, ADM systems
*Detection of signals in Gaussian noise
*Matched filter - Application of matched filter
*Error probability performance of binary signaling
*Multilevel base band transmission
*Inter symbol interference
*Eye pattern
*Companding
*A law and μ law
*Correlation receiver
Hello everyone. This is a short presentation on path loss and shadowing. I have not covered all the topics but a brief idea is given on path loss and wireless channel propagation models.
Hope you find it useful.
Thanks
the presentation consists of a brief description about ADAPTIVE LINEAR EQUALIZER , its classification and the associated attributes of ZERO FORCING EQUALIZER and MMSE EQUALIZER
This presentation covers:
Some basic definitions & concepts of digital communication
What is Phase Shift Keying(PSK) ?
Binary Phase Shift Keying – BPSK
BPSK transmitter & receiver
Advantages & Disadvantages of BPSK
Pi/4 – QPSK
Pi/4 – QPSK transmitter & receiver
Advantages of Pi/4- QPSK
Hello everyone. This is a short presentation on path loss and shadowing. I have not covered all the topics but a brief idea is given on path loss and wireless channel propagation models.
Hope you find it useful.
Thanks
the presentation consists of a brief description about ADAPTIVE LINEAR EQUALIZER , its classification and the associated attributes of ZERO FORCING EQUALIZER and MMSE EQUALIZER
This presentation covers:
Some basic definitions & concepts of digital communication
What is Phase Shift Keying(PSK) ?
Binary Phase Shift Keying – BPSK
BPSK transmitter & receiver
Advantages & Disadvantages of BPSK
Pi/4 – QPSK
Pi/4 – QPSK transmitter & receiver
Advantages of Pi/4- QPSK
This is the third part of the mini-series of synchronization in the Topics in Digital Communication Presentations.
Timing synchronization is another key component in modem design and implementation. However, this subject, especially its practical aspects, were not covered in details in text books. The materials covered in this presentation are not really new, but discussed in the literature published over past forty years. I hope that putting them in a single slide deck can help people who want to learn more on this subject.
Fuyun Ling
Includes a briefing on medium and high speed modems.Information about training sequence,scrambler and descrambler circuits.Also includes an introduction to modem control.
Software PLL for PLI synchronization, design, modeling and simulation , sozopoldpdobrev
Power-line interference is a common disturbing
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An Analytical Expression for Service Curves of Fading ChannelsGiacomo Verticale
In this paper, we develop a method for analyzing time-varying wireless channels in the context of the modern theory of the stochastic network calculus. In particular, our technique is applicable to channels that can be modeled as Markov chains, which is the case of channels subject to Rayleigh fading. Our approach relies on theoretical results on the convergence time of reversible Markov processes and is applicable to chains with an arbitrary number of states. We provide two expressions for the delay tail distribution of traffic transmitted over a fading channel fed by a Markov source. The first expression is tighter and only requires a simple numerical minimization, the second expression is looser, but is in closed form.
There are many types of wireless channel impairments such as noise, path loss, shadowing, and fading and impairment Mitigation techniques should be adopted according to system requirements and channel environments.
Joint Timing and Frequency Synchronization in OFDMidescitation
With the advent of OFDM for WLAN
communications, as exemplified by IEEE 802.11a, it has become
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frequency synchronization techniques.
This three day course is intended for practicing systems engineers who want to learn how to apply model-driven systems Successful systems engineering requires a broad understanding of the important principles of modern spacecraft communications. This three-day course covers both theory and practice, with emphasis on the important system engineering principles, tradeoffs, and rules of thumb. The latest technologies are covered. <p>
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The following resources come from the 2009/10 BEng (Hons) in Digital Communications & Electronics (course number 2ELE0064) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.
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CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
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It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
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Data file handling has been effectively used in the program.
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3. Table of Contents
1 Signal Parameter Estimation
1.1 The Likelihood Function
1.2 Carrier Recovery and Symbol Synchronization in
Signal Demodulation
2 Carrier Phase Estimation
2.1 Maximum-Likelihood Carrier Phase Estimation
2.2 The Phase-Locked Loop
2.3 Decision-Directed Loops
4. Introduction
In a digital communication system, the output of the demodulator
must be sampled periodically, once per symbol interval, in order
to recover the transmitted information.
Since the propagation delay from the transmitter to the receiver is
generally unknown at the receiver, symbol timing must be
derived from the received signal in order to synchronously
sample the output of the demodulator.
The propagation delay in the transmitted signal also results in a
carrier offset, which must be estimated at the receiver if the
detector is phase-coherent.
Symbol synchronization is required in every digital
communication system which transmits information
synchronously.
Carrier recovery is required if the signal is detected coherently.
5. 1. Signal Parameter Estimation
We assume that the channel delays the signals transmitted
through it and corrupts them by the addition of Gaussian noise.
The received signal may be expressed as
where
τ : propagation delay
sl(t): the equivalent low-pass signal
The received signal may be expressed as:
where the carrier phase φ, due to the propagation delay τ, is φ
= -2πfcτ.
6. It may appear that there is only one signal parameter to be
estimated, the propagation delay, since one can determine φ from
knowledge of fc and τ. However, the received carrier phase is
not only dependent on the time delayτbecause:
The oscillator that generates the carrier signal for demodulation at the
receiver is generally not synchronous in phase with that at the transmitter.
The two oscillators may be drifting slowly with time.
The precision to which one must synchronize in time for the
purpose of demodulating the received signal depends on the
symbol interval T. Usually, the estimation error in estimating
τmust be a relatively small fraction of T.
±1 percent of T is adequate for practical applications. However, this level
of precision is generally inadequate for estimating the carrier phase since
fc is generally large.
7. In effect, we must estimate both parameters τand φ in order to
demodulate and coherently detect the received signal.
Hence, we may express the received signal as
where φ and τrepresent the signal parameters to be estimated.
To simplify the notation, we let ψ denote the parameter vector
{φ, τ}, so that s(t; φ, τ) is simply denoted by s(t; ψ).
There are two criteria that are widely applied to signal
parameter estimation: the maximum-likelihood (ML) criterion
and the maximum a posteriori probability (MAP) criterion.
In the MAP criterion, ψ is modeled as random and characterized by an a
priori probability density function p(ψ).
In the ML criterion, ψ is treated as deterministic but unknown.
8. By performing an orthonormal expansion of r(t) using N
orthonormal functions {fn(t)}, we may represent r(t) by the
vector of coefficients [r1 r2 ¸¸¸ rN] ≡ r.
The joint PDF of the random variables [r1 r2 ¸¸¸ rN] in the
expansion can be expressed as p(r| ψ).
The ML estimate of ψ is the value that maximizes p(r| ψ).
The MAP estimate is the value of ψ that maximizes the a posteriori
probability density function
If there is no prior knowledge of the parameter vector ψ, we
may assume that p(ψ) is uniform (constant) over the range of
values of the parameters.
9. In such a case, the value of ψ that maximizes p(r| ψ) also
maximizes p(ψ|r). Therefore, the MAP and ML estimates are
identical.
In our treatment of parameter estimation given below, we view
the parameters φ and τ as unknown, but deterministic. Hence, we
adopt the ML criterion for estimating them.
In the ML estimation of signal parameters, we require that the
receiver extract the estimate by observing the received signal over
a time interval T0 ≥ T, which is called the observation interval.
Estimates obtained from a single observation interval are
sometimes called one-shot estimates.
In practice, the estimation is performed on a continuous basis by
using tracking loops (either analog or digital) that continuously
update the estimates.
10. 1.1 The Likelihood Function
Since the additive noise n(t) is white and zero-mean Gaussian,
the joint PDF p(r|ψ) may be expressed as
where T0 represents the integration interval in the expansion of
r(t) and s(t; ψ).
By substituting from Equation (B) into Equation (A):
11. Now, the maximization of p(r|ψ) with respect to the signal
parameters ψ is equivalent to the maximization of the likelihood
function.
Below, we shall consider signal parameter estimation from the
viewpoint of maximizing Λ(ψ).
12. 1.2 Carrier Recovery and Symbol
Synchronization in Signal Demodulation
Binary PSK signal demodulator and detector:
The carrier phase estimate is used in generating the
∧
reference signal g(t)cos(2πfct+φ) for the correlator.
The symbol synchronizer controls the sampler and the
output of the signal pulse generator.
If the signal pulse is rectangular, then the signal generator
can be eliminated.
14. QAM signal demodulator and detector:
An AGC is required to maintain a constant average power
signal at the input to the demodulator.
The demodulator is similar to a PSK demodulator, in that both
generate in-phase and quadrature signal samples (X, Y) for the
detector.
The detector computes the Euclidean distance between the
received noise-corrupted signal point and the M possible
transmitted points, and selects the signal closest to the
received point.
15. 2. Carrier Phase Estimation
Two basic approaches for dealing with carrier
synchronization at the receiver:
One is to multiplex, usually in frequency, a special signal,
called a pilot signal, that allows the receiver to extract and to
synchronize its local oscillator to the carrier frequency and
phase of the received signal.
When an unmodulated carrier component is transmitted
along with the information-bearing signal, the receiver
employs a phase-locked loop (PLL) to acquire and track
the carrier component.
The PLL is designed to have a narrow bandwidth so that it
is not significantly affected by the presence of frequency
components from the information-bearing signal.
16. The second approach, which appears to be more prevalent in
practice, is to derive the carrier phase estimate directly from
the modulated signal.
This approach has the distinct advantage that the total
transmitter power is allocated to the transmission of the
information-bearing signal.
In our treatment of carrier recovery, we confine our
attention to the second approach; hence, we assume that the
signal is transmitted via suppressed carrier.
17. Consider the effect of a carrier phase error on the demodulation
of a double-sideband, suppressed carrier (DSB/SC) signal:
Suppose we have an amplitude-modulated signal:
Demodulate the signal by multiplying s(t) with the carrier
reference:
we obtain
Passing the product signal c(t)s(t) though a low-pass filter:
18. ∧
The effect of the phase error φ -φ is to reduce the signal level ∧
in voltage by a factor cos(φ -φ) and in power by a factor
∧
cos2(φ -φ).
Hence, a phase error of 10± results in a signal power loss of
0.13 dB, and a phase error of 30± results in a signal power
loss of 1.25 dB in an amplitude-modulated signal.
The effect of carrier phase errors in QAM and multiphase PSK is
much more severe.
The QAM and M-PSK signals may be represented as:
S(t) = A (t)cos (2π fct+φ )−B (t)sin (2π fct+φ )
Demodulated by the two quadrature carriers:
c (t)= c cos(2πf ct+φ ) c (t)=−sin s (2πf ct+φ )
19. Multiplication of s(t) with cc(t) and cs(t) followed by low-pass
filtering yield the in-phase and quadrature component:
y (t)= I
1
2
1
A(t)cos (φ −φ)− 1
2
1
B (t)sin (φ −φ)
y (t)= Q 2 B (t)cos (φ −φ)+ 2 A (t)sin (φ −φ)
The phase error in the demodulation of QAM and M-PSK
signals has a much more severe effect than in the demodulation
of a PAM signal:
There is a reduction in the power of the desired signal component by a
∧
factor of cos2(φ -φ).
There is also crosstalk interference from the in-phase and quadrature
components. Since the average power levels of A(t) and B(t) are similar,
a small phase error causes a large degradation in performance.
Hence, the phase accuracy requirements for QAM and multiphase
coherent PSK are much higher than for DSB/SC PAM.
20. 2.1 Maximum-Likelihood Carrier
Phase Estimation
We derive the maximum-likelihood carrier phase estimate.
Assuming that the delay τ is known, and, we set τ = 0.
The function to be maximized is the likelihood function :
T
0
With φ substituted for ψ, the function becomes
21. Only the second term of the exponential factor involves the cross
correlation of the received signal r(t) with s(t; φ), depends on the
choose of φ.
Therefore, the likelihood function Λ(φ) may be expressed as
where C is a constant independent of φ.
∧
The ML estimateφ MLis the value of φ that maximizes Λ(φ).
Equivalently, it also maximizes the logarithm of Λ(φ), i.e., the
log-likelihood function:
22. 2.2 The Phase-Locked Loop
The PLL basically consists of a multiplier, a loop filter, and a
voltage-controlled oscillator (VCO):
Assuming that the input to the PLL is the sinusoid xc(t)= ∧
Accos(2πfct+φ) and the output of the VCO is e0(t)= -Avsin(2πfct+φ),
∧
where φ represents the estimate of φ, the product of two signals is:
23. The loop filter is a low-pass filter that responds only to the low- ∧
frequency component 0.5AcAvsin(φ -φ) and removes the
component at 2fc.
The output of the loop filter provides the control voltage ev(t)
for the VCO.
The VCO is a sinusoidal signal generator with an instantaneous
phase given by
where Kv is a gain constant in rad/s/V.
24. By neglecting the double-frequency term resulting from the
multiplication of the input signal with the output of the VCO, the
phase detector output is:
ˆ
e (ψ)=K sinψ d d
where ψ =φ−φ is the phase error and Kd is a proportionality
constant.
In normal operation, when the loop is tracking the phase of the
∧
incoming carrier, the phase error φ −φis small. As a result,
With the assumption that | ψ |<<1, the PLL becomes linear.
25. In practice, the selection of the bandwidth of the PLL involves
a trade-off between speed of response and noise in the phase
estimate.
On the one hand, it is desirable to select the bandwidth of the
loop to be sufficiently wide to track any time variations in the
phase of the received carrier.
On the other hand, a wideband PLL allows more noise to pass
into the loop, which corrupts the phase estimate.
26. 2.3 Decision-Directed Loops
Up to this point, we consider carrier phase estimation when the
carrier signal is unmodulated.
We consider carrier phase recovery when the signal carries
information {In}. In this case, we can adopt one of two
approaches: either we assume that {In} is known or we treat {In}
as a random sequence and average over its statistics.
In decision-directed parameter estimation, we assume that the
information sequence over the observation interval has been
estimated.
Consider the decision-directed phase estimate for the class of
linear modulation techniques for which the received equivalent
low-pass signal may be expressed as:
27. The likelihood function and corresponding log-likelihood
function for the equivalent low-pass signal are :
If we substitute for sl(t) and assume that the observation interval
T0=KT, where K is a positive integer, we obtain:
28. Differentiating the log-likelihood function with respect to φ and
setting the derivative equal to zero:
φˆ MLis the decision-directed (or decision-feedback) carrier phase
estimate.
It can be shown that the mean value of φˆML is φ. -- unbias.
30. The received double-sideband PAM is given by
A(t)cos(2͘fct+φ), where A(t)=Amg(t) and g(t) is assumed to be
a rectangular pulse of duration T.
The received signal is multiplied by the quadrature carriers cc(t)
and cs(t). The product signal:
is used to recover the information carried by A(t).
The detector makes a decision on the symbol that is received
every T seconds.
In the absence of decision errors, it reconstructs A(t) free of
any noise.
31. The reconstructed signal is used to multiply the product of the
second quadrature multiplier, which has been delayed by T
seconds to allow the demodulator to reach a decision.
The input to the loop filter in the absence of decision errors is
the error signal:
The loop filter rejects the double-frequency term.
The desired component is A2(t)sinΔφ, which contains the phase
error for driving the loop.