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Encoding Techniques for Analog Sources in Digital Communication Techniques


  • 1 K.Dharshana R.Dhivya M.Sneha K.S.Lavanya M.Divya Bharathi
  • Communication System 2 A B Engineering System Genetic System Social System History and fact of communication
  • Analog and Digital Signals 3 2 4 6 8 t 1 . 5 1 . 0 0 . 5 0 . 5 1 . 0 1 . 5 f t A n a lo g 2 4 6 8 t 1 . 5 1 . 0 0 . 5 0 . 5 1 . 0 1 . 5 f t A m p lit u d e D is c r e t e
  • Encoding and Modulation 4
  • Modulation Modulation is a process of varying the one or more properties of the carrier signal with a modulating signal which typically contains information to be transmitted. The frequency of the carrier signal is chosen to be compatible with the transmission medium being used. Modulation techniques involve operation on one or more of the three parameters: amplitude, frequency, and phase According to the input source signal m(t), which is called baseband signal , the carrier signal fc(t) will be modulated into modulated signal s(t). 5
  • Components of Digital Communication Sampler Quantizer Encoder Modulator Decoder Channel Demodulator Reconstruction Filter 6 Ruggedness to channel noise & other interference Flexible implementation of digital hardware system Coding of digital signal to obtain extremely low error rate & high fidelity Security of information
  • Digital Communication System 7 Source Encoder Modulator RF-Stage Channel RF-Stage Source Decoder Demodulator Channel Encoder Channel Decoder Distortion and noise Transmitter Receiver Source input Reconstructed Signal output
  • Coding Techniques for Speech The goal of all speech coding systems is to transmit speech with the highest possible quality using the least possible channel capacity. Speech codes differ widely in their approach to achieving compression. All Speech coding techniques employ quantization. Many also employ additional properties of speech : Wave Form Coding : TEMPORAL WAVEFORM CODING SPECTRAL WAVEFORM CODING SOURCE CODING 8
  • Types Of Coding Techniques
  • Temporal Waveform Encoding A speech or an image source produces signals that vary with the time. Designed to represent the time domain characteristics of the signal. For high bit rates (16-64 kbps) it is sufficient to just sample and quantize the time domain waveform. We need to digitize some time varying parameter of the time-wave form representing the source. this process is called as temporal waveform encoding There are different types of modulation in temporal waveform encoding. Let us see about it. MOST COMMON METHODS ARE : Pulse Code Modulation (PCM) Differential Pulse Code Modulation (DPCM) Delta Modulation (DM) 10
  • PCM was invented by the British engineer Ales Reeves in 1937 in France. It was not until about the middle of 1943 that the Bell Labs people became aware of the use of PCM binary coding as already proposed by Alec Reeves. At first the pulse amplitude will be modulated with the carrier by using the pulse amplitude modulation. After that the Pulse amplitude modulation is quantized this signal pulse is coded and modulated to the signal it is known as pulse coded modulation. The sampling rate must be greater than, twice the highest frequency in the analog signal, fs > 2fA(max) PCM can be used as a storage device & for baseband transmission. 11 Pulse Code Modulation (PCM)
  • PCM Block Diagram 12
  • 13 Advantages of PCM 1. Robustness to noise and interference 2. Efficient regeneration 3. Efficient SNR and bandwidth trade-off 4. Uniform format 5. Ease add and drop 6. Secure Modifications of PCM 1.VLSI chips are made commercially available for PCM system 2. Increased bandwidth is provided by OFC optical fibre cable 3 Using data compression techniques ,redundancy and transmitted data bit rate is reduced 4. Instead of PCM, Delta modulation also preffered Virtues and Modifications of PCM
  • Differential Pulse Code Modulation (DPCM) Speech is very strongly correlated from one instant to next. In DPCM, the difference between successive samples are encoded rather than the samples themselves. Since the difference between samples are expected to be smaller than the samples themselves, fewer bits are required to represent the difference. Usually PCM has the sampling rate higher than the Nyquist rate. The encode signal contains redundant information. DPCM can efficiently remove this redundancy. 32 Kbps for PCM Quality. In DPCM, the error at the output of a prediction filter is quantized, rather than the voice signal itself. It is assumed that the error of the prediction filter is much smaller than the actual signal itself. DPCM quantizes the difference between one sample and the predicted value of the next sample (this is usually much less than the absolute value of the samples) 14
  • Power spectrum for speech signal 15
  • DPCM Receiver 16
  • 17 The exploitation of signal correlation in DPCM suggest that oversampling a signal will increase the correlation between samples. Delta modulation is a special case of DPCM where there are only two quantization levels It is extreme case of DPCM in which signal is oversampled and R=1 bit/sample. Delta modulation can be implemented with an extremely simple 1 bit quantizer. Adaptive Delta Modulation at 16 Kbits/sec can produce reasonable quality speech Delta Modulation (DM)Delta Modulation (DM)
  • 18 DM TransmitterDM Transmitter DM ReceiverDM Receiver
  • 19 Delta ModulationDelta Modulation The high sample to sample correlation of speech type signal is exploited to the maximum in the delta modulation. If we oversample a signal, the correlation between adjacent samples increases and as a result, the prediction error decreases. DM is basically a 1-bit DPCM where no extra encoding effort is needed there by simplifying the circuitry. It predictor is generally 1st order , so a signal needs time delay. The performance of is limited by two types of distortion. Slope Overload Distortion Step Size is too small Granular Noise Step size is too large
  • 20 Delta ModulationDelta Modulation Alternative solution is variable step size : Step size is increased when the waveform has steep slope and decreased when the waveform has relatively small slope. One of the method is Continuous Variable Slope Delta Modulation (CVSD). DM WaveformDM Waveform
  • Spectral Waveform EncodingSpectral Waveform Encoding PCM, APCM, DPCM, ADPCM, DM and ADM are all encoding technique that attempt to faithfully represents the time variations of the input signal waveform. Attempt to represent spectral characteristics of speech waveform. The source output signal is filtered into a number of frequency sub band and separately encoded in each sub band. Each sub band can be encoded in time-domain waveform or Each sub band can be encoded in frequency-domain waveform. There are two types of coding in spectral wave form encoding they are 1)sub band coding (SBC) 2)Adaptive Transform coding(ATC)
  • 22 Subband Coding :Subband Coding : Source signal is divided into number of subbands . More bits for the LFB signal and fewer band for HFB. Filter design is important in achieving good performance Quadrature-mirror filters (QMFs) used most used in practice. Example :Example : Lets assume that speech signal BW=3200HzLets assume that speech signal BW=3200Hz Each of QMFs divides the spectrum into 2 Low : 0-1600Hz, & High : 1600-3200Hz. Low: 0-800Hz, & High : 800-1600Hz. Low : 0-400Hz, & High : 400-800Hz.
  • Adaptive Transform CodingAdaptive Transform Coding The source signal is sampled and subdivided into frames of Nf samples. Then data is transformed into the spectral domain . signal is converted and synthesized from the time domain samples. Bit assigned of spectral coefficients . For transform, DFT or DCT can be used.
  • 24 Model-Based encoding (Source coding)Model-Based encoding (Source coding) For low bit rate voice encoding it is necessary to mathematically model the voice and transmit the parameters associated with the model. This type of coding attempts to replicate a model of the process by which speech was constructed Estimate the input waveform by minimizing the difference between the signal Characterize various parameters and encoded it. The source is modeled as a linear system. The parameters of the linear system are transmitted with an appropriate excitation table. If the parameters are sufficient small, provides large compression.


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