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Transcript
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