analog and digital communication , definition of Model of a digital communication system

By   November 12, 2019

ANALOG AND DIGITAL COMMUNICATION
Depending upon the message signal, communication may also be classified as under:
(i) Analog Communication,
(ii) Digital Communication.
1.10.1. Analog Communication
          Analog communication is that type of communication in which the message or information signal to be transmitted is analog in nature. This means that in analog communication the modulating signal (i.e., baseband signal) is an analog signal. This analog message signal may be obtained from sources such as speech, video shooting etc.
In analog communication, the analog message signal modulates some high carrier frequency inside the transmitter to produce modulated signal. This modulated signal is then transmitted with the help of a transmitting antenna to travel through the transmission channel. At the receiver, this modulated signal is received and processed to recover the original message signal. Figure 1.5 shows the block diagram of an analog communication system.
 
FIGURE 1.7 Basic Analog Communication System
Presently all the AM, FM radio transmission and TV transmission are examples of analog communication.
1.10.2. Digital Communication
          In digital communication, the message signal to be transmitted is digital in nature. This means that digital communication involves the transmission of information in digital form.
1.10.3. Model of a Digital Communication System
Figure 1.8 shows the model of a digital communication system. The overall purpose of the system is to transmit the message or sequences of symbols coming out of a source to a destination point at as high a rate and accuracy as   possible. The source and the destination point are physically separated in space and a communication channel connects the source to the destination point. The Noise communication channel accepts channel electrical (i.e., electromagnetic) signals and the output of the
channel is usually a smeared or distorted version of the input due to the non-ideal nature of the communication channel. In addition to this, the information-bearing signal is also corrupted by unpredictable electrical signals (i.e., noise) from both man-made and natural causes. Thus, the smearing and the noise introduce errors in the information being transmitted and limits the rate at which information can be communicated from the source to the destination.
The probability of incorrectly decoding a message symbol at the receiver is often used as a measure of performance of a digital communication system.
Now, let us have a detailed look at each of the functional blocks in a digital communication system.

  1. Discrete Information Source

Information source may he classified into two categories based upon the nature of their output i.e., analog information sources and discrete information sources. In case of analog communication, the information source is analog. Analog information sources, such as microphone actuated by speech, emit one or more continuous amplitude signals.
In case of digital communication, the information source produces a message singal which is not continuously varying with time. Rather the message signal is intermittent with respect to time. The output of descrete information sources such as a teletype or the numerical output of a computer consists of a sequence of discrete symbols or letters. An analog information source may be trap into a discrete information source through the process of sampling and quantizing. Discrete information sources are characterized by the following parameters:
(i) Source Alphabet: These are the letters, digits or special characters available from the information source.
(ii) Symbol Rate: It is the rate at which the information source generates source alphabets. It is generally repressented in symbols/sec unit.
(iii) Source Alphabet Probabilities: Each source alphabet from the source has independent occurrence rate in the sequence. As an example, letters A, E, I etc., occur frequently in the sequence Hence, probability of the occurrence of each source alphabet can become one of the important property which is useful in digital communication.
(iv) Probabilistic Dependence of Symbols in a Sequence: The information carrying capacity of each source alphabet is different in a particular sequence. This parameter defines average information content of the symbols. The entropy of a source describes the average information content per symbol in long messages. Entropy may be defined in terms of bits per symbol. Bit is the abbreviation for a binary digit.
This means that the source information rate is the product of symbol rate and source entropy, i.e.,
Information rate         =          Symbol rate      x      Source entropy
(Bits/sec.)                           (Symbols/sec.)           (Bits/Symbol)
 
Thus, the information rate represents minimum average data rate required to transmit information from source to the destination.

  1. Source Encoder and Decoder

The symbols produced by the information source are given to the source encoder. These symbols cannot be transmitted directly. They are first converted into digital form (i.e., binary sequence of l’s and 0’s) by the source encoder. Each binary ‘1’ and ‘0’ is known as a bit. The group of bits is called a codeword.
The source encoder assigns codewords to the symbols. For each distinct symbol, there is an unique codeword.
The codeword can be of 4, 8, 16 or 32 bits length. As the number of bits are increased in each codeword, the symbols that may be represented are also increased.
As an example, 8 bits would have 28 i.e., 256 distinct codewords. This means that 8 bits may be used to represent 256 symbols and similarly 16 bits may represent 216 = 65536 symbols and so on. Some typically source encoders are pulse code modulators, delta modulators, vector quantizers etc. Source encoders must have following important parameters:
(i)      Block Size
Block size describes the maximum number of distinct codewords which can be represented by a source encoder. This depends on the number of bits in the codeword. As an example, the block size of 8 bits source encoder will he 28 i.e., 256 codewords.
(ii)     Codeword Length
Codeword length is the number of bits used to represent each codeword. As an example, if 8 bits are assigned to each codeword, then the codeword length will be 8 bits.
(iii)    Average Data Rate
Average data rate is the output bits per second from the source encoder. In fact, the source encorder assigns multiple number of bits to each input symbol. Hence, the data rate is generally higher than the symbol rate. As an example, if we consider that the symbols are given to the source encoder and the
length of codeword is 8 hits, then the output data rate from the source encoder would be given as
Data rate = Symbol rate x Codeword length = 10 x 8
Data rate = 80 bits/seconds
Also, since the information rate is the minimum number of bits per second needed to convey information from source to destination, therefore the optimum data rate is equal to the information rate. However, due to practical limitations, designing such type of source encoder is quite difficult. Thus, the average data rate is higher than the information rate and hence symbol rate also.
(iv)    Efficiency of the Encoder
The efficiency of the encoder is the ratio of minimum source information rate to the actual output data rate of the source encoder.
In last, it may be noted that at the receiver end, some sort of decoder is used to perform the reverse operation to that of source encoder. It converts the binary output of the channel decoder into a symbol sequence. Some decoders also use memory to store codewords. The decoders and the encoders can be synchronous or asynchronous.

  1. Channel Encoder and Decoder

          After converting the message or information signal in the form of binary sequence by the source encoder, the signal is transmitted through the channel. The communication channel adds noise and interference to the signal being transmitted. Hence, errors are introduced in the binary sequence received at the receiver end.
Therefore, the errors are also introduced in the symbols generated from these binary codewords. Thus channel coding is done to avoid these types of
errors. In fact, the channel encoder adds some redundant binary bits to the input sequence. Also, these redundant bits are always added with some properly defined logic. As an example, let us consider that the codeword from the source encoder to make it 4-bits long. This fourth bit is added (i.e., 1 or 0) in such a manner that the number of 1’s in the encoded word remain even (also known as even parity). Table 1.2 gives the output of a source encoder, the fourth bit depending on the parity and the output of channel encoder.
NOTE:       It may be observed from the table that each codeword at the output of channel encoder contains “even” number of 1’s. Now, at the receiver end, if odd number of 1’s are detected, then the receiver comes to know that there is an error in the received signal. The channel decoder at the receiver is thus able to reconstruct error free accurate bit sequence and reduce the effects of channel noise and distortion.

Output of
source encoder
Bit to be added by the channel encoder for an even parity Output of a channel encoder
b3      b2      b1
1        0        0
0        1        0
0        0        0
1        1        1
:
:
b0
1
1
:
:
b3      b2      b1           b0
1        1        0        0
0        1        0        1
0        0        0        0
1        1        1        1
:
:

 
This means that the channel encoder and decoder serve to increase the reliability of a received signal. However the extra bits which are added by the channel encoders carry no information. rather, they are used by the channel decoder to detect and correct errors if any. The coding and decoding operation
at the encoder and decoder needs the memory and processing of binary data However in the modern time, due to use of microcontrollers and computers, the complexity of the, encoders and decoders has been significantly reduced.
A channel encoder must have the following important parameters:
(i) The coding rate that depends upon the redundant bits added by the channel encoder.
(ii) The coding method used.
(iii) Coding efficiency which is the ratio of data rate at the input to the data rate at the output of the encoder.
(iv) Error control capabilities.
(v) Feasibility of the encoder and decoder.

  1. Digital Modulators and Demodulators
DO YOU KNOW?
Well-known forms of electronic communication, such as the telephone, radio and television, have increased our ability to share information. Today, they are a major part of our lives.

In article 1.8, we discussed why modulation is needed in communication system. Now, if the modulating signal is digital (i.e. binary codewords), then digital modulation techniques are used. The carrier signal used by digital modulators is always continuous sinusoidal wave of high frequency. In fact, the digital modulators map the input binary sequence of 1’s and 0’s to the analog signal waveforms. For example, if one bit at a time is transmitted, then digital modulator signal is s1(t) to transmit binary ‘0’ and s2(t) to transmit binary ‘1’ as shown in figure 1.9.
Here the signal s1(t) has low frequency compared to signal s2(t). Hence, here, even though the modulated signal seems to be continuous, the modulation is discrete (i.e., in steps). This means that a signal carrier is converted into two waveforms s1(t) and s2(t) because of digital modulation.
Now, if the codeword consits of two bits and they are to be transmitted at a time, then there would be 22 i.e.. 4 distinct symbols i.e., codewords. Thus, these codewords will require four distinct waveforms for transmission purpose. Such types of modulators are known as M-ary modulators. Amplitude shift keying (ASK), phase shift keying (PSK), frequency shift keying (FSK), differential phase shift keying (DPSK) and minimum shift keying (MSK) are the examples of various digital modulators.
 
 
 
FIGURE 1.9 The output of a digital modulator.
However, since these modulators use a continuous, carrier wave, therefore they are also known as digital CW modulators. At the receiver end, the digit al demodulator converts the input moodulated signal into the sequence of binary bits.
A digital modulation method must have, following important parameters:
(i) Bandwidth needed to transmit the signal,
(ii) Probability of symbol or bit error,
(iii) Synchronous or asynchronous method of detection,
(iv) Complexity of implementation.

  1. Communications Channel

As discussed earlier, the connection between transmitter and receiver is established through a communication channel. The communication can take place through wirelines, wireless or fiber optic channels. The other media such as optical disks, magnetic tapes and disks etc. may also be called as a communication channel since they can also carry data through them. However, it may be noted that each and every communication channel has some inherent problems. These are:
(i)      Signal Attenuation: The signal attenuation in channel occurs due to the internal resistance of the channel and fading of the signal.
(ii)     Amplitude and Phase Distortion: The transmitted signal is distorted in amplitude and phase due to the non-linear characteristics of the communication channel.
(iii)    Additive Noise Interference: Additive noise interference is produced due to internal solid state devices and resistors etc., used to implement a communication system.
(iv)    Multipath Distortion: The multipath distortion occurs mostly in wireless communication channels.
In fact, the signals coming from different paths tend to interfere with each other.

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