Download 1.2 Peak Detection System

This project presents an investigation to a simple peak detection channel used in different
computer storage systems. Two major activities are described, the first being the simulation
of a peak detection channel and the second being the hardware design for the channel.
The peak-detection channel simulation was carried out in simulation software package known
as electronic workbench (EWB) where the channel electronic circuits are tested and the
results are presented.
The simulated peak–detection channel is designed in the electronic lab using real electronic
components and the results are also presented.
The simulation results and experimental measurements then compared where a good
agreement is obtained. This is done to prove the practicality of the simulated channel
electronics.
NO
NO. Of P.
Abstract
Chapter1 :- Review on Signal
Manipulation
1.1
introduction
15
1.2
Peak system detection
17
1.3
Detection window
19
1.4
Signal to noise ratio and error rate of
the threshold detector
Error rate of the zero crossing
21
Project layout
25
1.5
23
Chapter2 (channel simulation)
2.1
Input sequence
28
2.2
Response pulse
32
2.3
Simulation of peak detection channel
34
Chapter3 (channel implementation)
3.1
Introduction
40
3.2
Requirements
40
3.3
Specifications
40
3.4
Design stage
41
Chapter4(conclusion and future work)
4.1
Conclusion
44
4.2
Future work
44
Reference
No. of page
15
Title
Number of
figure
Signal processing through a specified
system
(1.1.1)
Block diagram of communication system
17
(1.1.2)
Block diagram of storage system
17
Peak detection system
18
Typical
The processing of finding zero crossing
19
20
Detection window for peak detection
system
(1.1.3)
(1.2.1)
(1.2.2)
(1.3.1)
with (1,7)code.
21
Error of threshold detector.
(1.4.1)
Gaussian distribution function.
22
(1.4.2)
Influence of noise on zero- crossing
23
24
(1.5.1)
Influence of both ISI and noise on zero
29
30
33
34
crossing detector
(2.5.2)
Feed back shift register corresponding to
x^4+x+1
(2.1.1)
Simulated pseudo-random sequence
generator of length 4095 and part from
the generated binary data.
(2.1.2)
The response signal computed by timeconvolutions approach
(2.2.1)
Relationship between input output wave
forms for signal recoding system
Block diagram of peak detection
(2.2.2)
(2.3.1)
36
Signal after the threshold
(2.3.3)
36
Output digital signal
(2.3.4)
37
In put (sine wave)and output(square)
(2.3.5)
41
Channel Circuit diagram of Simple Of
(3.4.1)
Peak Detection
42
43
Input analog signal
Channel output response
(3.4.2)
)3.4.3)
No. of. page
16
32
Title
Number of table
Comparison between communication
and storage channel
Table (1)
Feedback polynomials to generate
PRBS
Table (2)
Chapter 1:- Introduction
Chapter2:- Channel simulation
Chapter3:- Channel Implementation
Chapter4:- Conclusion and future work
* Fundamentals of magnetic recoding.
* Peak detection system
* Detection window.
* Signal to noise ratio and error rate of the threshold detector.
* Error rate of the zero- crossing detector.
* Project layout.
Chapter 1:- Review on Signal Manipulation
1.1- Introduction
Systems are designed to perform some tasks or to process signals that express information in
continuous or discrete form as illustrated in Fig. (1.1.1). Information comes neatly packaged
in analog or digital forms. Speech for example, is clearly an analog signal and computer files
consist of sequence bytes, a form of discrete time signal. Continuous and discrete signal
processing through different systems can be done with respect to time where storage systems
are obtained or with respect to position where communication systems are obtained.
The main objective of a communication system is to transmit information bearing signals
from a source, located at one point, to a user destination, located at another point some
distance away (here and there). When the message produced by the source is not electrical in
nature, which is often the case, an input transducer is used to convert it into a time varying
electrical signal called the message signal. Where as the storage systems aim to transmit
information over time (now and then).
Fig (1.1.1) Signal Processing through a specified system
Many features are common between both systems and several design techniques can be
implemented to both systems successfully. Table (1.1.1) presents a comparison between
storage and communication systems. In addition to stability, storage and communication
systems must meet other requirements, such as to track desired signals and to suppress noise,
to
be
really
useful
in
practice.
In this project, an attempt has been done to design simple peak detection channel used in
conventional storage systems. In order to a achieve the desired design, theoretical and
simulation procedures are reviewed and investigated. This piece of work presents an
implementation to the electronic circuit's knowledge gained through out the course of study.
Electronic circuit form the
basis to achieve the required signals manipulation and some
basic principles used in magnetic Performance of the recoding channel is also addressed.
Communication system
St orage system
Communication
links
transmit Information transmitted from now to then
information from here and there.
Aiming to maximizing number of Aiming to maximizing number of stored
transmitted bits per second.
bits per inch.
Involves communication media such
Involves storage media such as hard discs
as, air, optical fibers, and wires…etc.
magnetic tapes and optical discs.
Their
electronics
start
with Start with record electronics and end with
transmitters and end with receivers
They
involve
modulation
demodulation schemes
re play electronics
and No
modulation
and
demodulation
schemes are involved.
Table (1.1.1) Comparison between communication and storage systems
Fig. (1.1.2) shows the block diagram of communication system and fig. (1.1.3) shows the
block diagram of storage system.
Information
Source
Source
Transducer
Channel
Encoder
Noise,
Interferences and
Distortion
Information
Sink
Communication
Media
Channel
Decoder
User
Transducer
Fig (1.1.2) Block diagram of a communication system
Record signal processing
Input data
(bi)
Error-correction
encoder
Channel
encoder
I
(ai)
Record head
driver
t
Record current
Record/Replay
Process
Decoded
data
Error-correction
decoder
(b’i)
Channel
decoder
x’(t)
Channel
equalisation &
detection
Playback signal processing
r(t)
e
t
Analogue playback
signal
Fig. (1.1.3) Block diagram of storage system
1.2 Peak Detection System:Computer memories are divided into or working memories including RAM's,ROM's and
other semiconductor devices which are directly addressable by the CPU, and mass storage
devices. Mass storage memories generally are not directly addressable by the CPU, have as
lower access method, are non-volatile and often removable off-line and have a much lower
cost per bit. Mass storage devices may be classified into magnetic hard disks and floppy
disks, several types of magnetic type drives, and various kinds of optical disk drives. In
additional, there are the many varieties of card storage devices like magnetic card, smart
cards, RAM and flash memory cards. Except for the CD-ROM in which data is represented
by physical indentations or pits, practically all other write-able mass storage devices make
use of the magnetic or magneto-optical (M-O) characteristics of the recording media to store
the required information.
In conventional storage devices when recording density is relatively low, intersymbol
interference (ISI) is small enough, each transition results in a relatively sharp peak of voltage.
To detect such transitions, a peak detection scheme was developed. Peak detection scheme
was the main detection principle of most of the current disk drives until other advanced
channels were introduced some time ago specially for very poor chararctized environments.
A block diagram of a typical peak detector system is shown in Figure (1.2.1).
Fig (1.2.1) typical peak detection system
Referring to fig (1.2.1), in typical peak detection system, the input analog signal is passing
through
two different paths. One path qualifies a peak of voltage by simple threshold
detection. It means that when a voltage level exceeds some threshold level, a comparator is
turned on and a rectangular pulse appears on the output of threshold detector. A second path
locates the peaks of voltage by differentiating the signal and looking at the zero crossing of
the signal derivative. Once a zero crossing is detected and it is located within the region and
signal amplitude exceeds a specific threshold value, the transition signal is considered to be
detected and the qualified pulse appears on Peak detector output. This process is
schematically shown in figure (1.2.2).
Fig. (1.2.2)The process of finding zero crossing
To achieve a precise output response of the output of the system two paths are used in the
peak detection systems because for example, when only the threshold detector is used to
detect peaks of voltage, the exact location of the transitions will not be determined precisely.
As seen from Figure (1.2.2), the threshold detector provides on its output a relatively wide
pulse of voltage. On the other hand, if only a differentiating process and zero-crossing
detector is used, a lot of extra–crossings caused by noise are to be expected in the channel.
The combination of a threshold detector and a zero–crossing detector provides additional
robustness to the system and allow relatively accurate determination of the peak position.
1.3 Detection window: To distinguish between adjacent transitions and to track instabilities of the rotational speed,
each pulse of voltage is detected inside the appropriate detection window. To provide this
detection window, a special Phase- Locked Loop (PLL) system is used. PLL updates its
frequency based on detected pulses. Each incoming transition and the correspondingly pulse
of voltage is searched inside its detection interval. Since peak detection systems are mostly
using (1,7) encoding scheme, this timing interval corresponds to 50% of the timing distance
between the two closest transitions which could be written on the magnetic medium. The
principle of setting the detection window is illustrated in Figure (1.3.1). By this way, each
pulse should be detected after the previous channel bit and before the next channel bit,
therefore the timing window, or bit cell equals exactly channel bit rate, or one half of channel
flux rate. Performance of the peak detection system depends on a number of parameters.
Most importantly, its error rate is determined by two factors.
Fig. (1.3.1) Detection Window for Peak Detection System with (1.7) code
The error rate of the threshold part of the peak detection system is determined by the
probability of drop-outs when the pulse amplitude falls below the specified threshold or the
probability of strong noise outbursts when total media and electronic noise exceeds the
specified signal level. The error rate of differentiating part is determined by random shifts of
zero-crossing position from the correct peak location. Random noise mixed with the signal
causes position of the zero-crossing position in the differentiated read-back signal. Error
occurs when this zero-crossing position falls beyond the detection window, when zerocrossing is being detected earlier or later than the current bit-cell. Now we will consider error
rates of the threshold part and the zero-crossing part of the peak detection system in more
detail.
1.4 Signal to noise ratio and error rate of the threshold detector
An error in the threshold detector will occur when the noise outburst exceeds the threshold
(extra bit detected) or when the noise masks the existing transition (missing bit error) as
illustrated in Figure (1.4.1)
Fig. (1.4.1) Error of Threshold Detector
The theoretical estimate of the error rate of the threshold detector may be calculated from the
Knowledge of channel signal to noise ratio (SNR). We will use the following definition of
SNR:
SNR = [(peak- signal- power(s))/ (Root- Mean- Square (RMS) – Noise power (N))]
SNR = [(zero-to- peak-signal –voltage/-noise-voltage)]
Let us denote zero to peak signal voltage as VO and RM S of noise as VN. Signal –to-Noise
ratio
in
decibels
is
defined
as:
To estimate the approximate error rate of the threshold detector in the Peak Detection
channel, we will consider that the noise in the recording channel is approximately. Gaussians
with zero mean value. This means that the noise distribution is given by the following
expression:
F (n)  (1 2 *  * )) * exp{(n2 / 2 * 2 }..............................(1.2)
Were σ is the noise standard deviation: Figure (1.4.2) depicts the Gaussian noise distribution
function.
=3σ
Fig. (1.4.2) Gaussian distribution Function
Now we will consider probabilities of errors in the threshold detector. If there is no peak of
voltage in the channel, we may detect transition if the noise outburst exceeds one half of
zero-to-peak signal voltage. The probability of this event is given by the following integral of
the Gaussian distribution function:
vo / 2
Po / i 
 {(1
2 *  *  ) * exp( (n 2 / 2 *  3 )) dn}.........................................................................(1.3)

The following integral of the Gaussian distribution is called a complementary error function
and is tabulated:

erft{x)   (2 /  ) *  exp{ y 2 }dn............................................................................................(1.4)
x
From here we can easily obtain (this requires substituting the integration limits):
po / i  (1/ 2) * erfc[(vo / 2 (2 * )]  (1/ 2)erfc SNR / 2 2].......................................................(1.5)
Similar to the above example, a zero signal will be detected instead of voltage, if a negative
noise outburst occurs so that noise exceeds a value of –Vo/2:
 vo / 2
po / i 

[1 / (2 *  * )) * exp{ n 2 / 2 *  3 )}dn]  (1 / 2)erfc[ SNR / 2 2...................................(1.6)

The above calculation has rather theoretical significance. If the signal amplitude is stable and
the channel noise is Gaussian, for a value of SNR = 20dB the expected error rate of the
threshold detector will be better than 10 7 . For a typical SNR of about 25dB the threshold
detector error rate will be about 10 15 .However, instability of the amplitude, modulation and
medium defects may cause threshold much in excess of the above calculation.
1.5 Error Rate of the Zero-Crossing Detector
Zero-crossing detector locates the transition by looking at the signal derivative. When signal s
(t) is mixed with noise n (t), both of them are differentiated and the output signal of the
differentiator is equal to s'(t) +n'(t). As a result the location of zero-crossing in the signal is
shifted from the location of transition as shown in Figure (1.5.1). These errors are also called
peak-shift or bit-shift errors.
Fig (1.5.1) Influence of noise on zero crossing detector
An error on the output of the zero-crossing detector will occur when the resulting shift
exceeds the detection window edges. Theoretical calculation of this error rate is complicated,
since the actual timing shifts induced by noise depend on the exact values of the pulse
derivative s'(t) and the noise derivative n'(t). For a Lorenzian pulse model and Gaussian noise
with standard deviation σ, the following threshold estimate has been obtained to predict bitshift error rate:
Pbit  shift  (1 / 2)erfc[ SNR / 4]...................................................................................................(1.7)
Comparing this expression with the error rate threshold detector which was obtained in the
previous section, it is easy to see that effective SNR for bit-shift errors is √2 times or 3dB
below of threshold errors. Therefore, it can be expected that bit-shift errors will dominate the
error rate of peak detection system, at least if the read-back amplitude is stable. Bit-Shift
errors are important also due to the linear Inter Symbol Interference (ISI). In the Figure,
(1.5.2) the distance between the edges of the detection window and the zero-crossing
becomes smaller as illustrated. Therefore the probability of errors will increase.
Fig. (1.5.2)Influence of both ISI and noise on zero crossing detector
Chapter 1:
Presents the required background and theoretical information to carry out the project.
Chapter2:
Presents the required simulation using the electronic work bench (EWB) and the simulated
results are presented
Chapter 3:
Presents the design of the peak detection channel which is done in the electronic lab using
different channel components and the experiment al results are also presented
Chapter4:
This chapter presents the over all conclusion and opens a further area to be investigated