DIGITAL COMMUNICATION

K K SHARMAAssociate Prof (ECE)1/11/2013K K S1

DATA COMMUNICATION

1UNIT-11/11/2013K K S2DIGITAL COMMUNICATIONDATA1/11/2013K K S3 (1) Distinct pieces of information, usually formatted in a special way. All software is divided into two general categories: data and programs. Programs are collections of instructions for manipulating data. Data can exist in a variety of forms -- as numbers or text on pieces of paper, as bits and bytes stored in electronic memory, or as facts stored in a person's mind. Strictly speaking, data is the plural of datum, a single piece of information. In practice, however, people use data as both the singular and plural form of the word. (2) The term data is often used to distinguish binary machine-readable information from textual human-readable information. For example, some applications make a distinction between data files (files that contain binary data) and text files (files that contain ASCII data).

UNIT 1 DIGITAL COMMUNICATION1/11/2013K K S4Introduction, digital communication, Shannon limit for information capacity, digital radio, digital amplitude modulation, frequency shift keying (FSK), phase shift keying (PSK), quadrature amplitude modulation (QAM), band width efficiency, carrier recovery, differential phase shift keying (DPSK), clock recovery, probability of error & bit error rate, trellis encoding.

Introduction to communication

1/11/2013K K S5People can communicate with other people. This is one unmistakable characteristic that points out the difference between humans and other animals (i.e. the ability to communicate). During the early days, communication among humans was limited by distance. People communicated by natural senses of hearing and sight or by written words. Actual words could be conveyed although the process was very slow. People searched for better ways of communicating faster and over long distances. Smoke signals and flag signaling were used to send messages. These were used for centuries until the nineteenth century when electrical signals came in use. In 1869, the telephone was invented. This marked a real breakthrough. At that time, it seemed like a miracle to be able to talk to someone so many miles away as easily and quickly as they were standing next to you. The arrival of wireless communication nearly three decades after the Telephone, completed the breakthrough.1/11/2013K K S6Communication is the process of conveying information at a distance or it is the basic process of exchanging information. In other words, communication is the science of transmitting, receiving and processing of information. Electrical communication is a process in which the message or information is transmitted from one point to another point or from one person to another in the form of electrical signal, through some communication link.The electronic equipments or devices which are used for the purpose of communication are known as communication equipments and integrating of different communication equipments for the purpose of communication form a communication system.Electrical communication system1/11/2013K K S7In communication, the physical information, such as sounds, pictures, words etc., is converted into an electrical message called signal and this electrical signal is being conveyed at the far place, and there, these electrical signals are reconverted into physical message.Fig-1, shows the simple block diagram of electrical communication system and it has three main basic components,TransmitterCommunication channel or transmission mediaReceiver

Simple block diagram of communication system1/11/2013K K S8

Types of Communication Systems

1/11/2013K K S9Broadly we classify the communication system in two types depending upon the type of the signal which is used in the communication system for processing, namely I. Analog communication systemII. Digital communication system

Analog Communication System

1/11/2013K K S10We have described an electrical communication system in rather broad terms based on the implicit assumption that the message signal is a continuous time-varying waveform. We refer to such continuous-time signal waveforms as analog signals and to the corresponding information sources that produce such signals as analog sources. Analog signals can be transmitted directly via carrier modulation over the communication channel and demodulated accordingly at the receiver. We call such a communication system an analog communication system.In general, an analog communication system can be represented by the functional block diagram shown in Fig.- 2. The information generated by the source may be of the form of voice (speech source), a picture (image source), or plain text.

Functional block diagram of an analog communication system1/11/2013K K S11

Digital Communication System

1/11/2013K K S12The communication system which uses the digital signals as input is known as digital communication system.An analog source output may be converted into a digital form and the message can be transmitted via digital modulation and demodulated as a digital signal at the receiver.

Typical block diagram of a digital communication system1/11/2013K K S13

1/11/2013K K S14In a digital communication system, the functional operations performed at the transmitter and receiver must be expanded to include message signal discretization at the transmitter and message signal synthesis or interpolation at the receiver. Additional functions include redundancy removal, and channel coding and decoding.

Information source

1/11/2013K K S15The source output may be either an analog signal, such as audio or video signal, or a digital signal, such as the output of a computer which is discrete in time and has a finite number of output characters. The analog information is converted to an equivalent digital signal by sampling and quantization that process is known as Analog to Digital conversion (ADC). The A/D produces analog-to-digital conversion (for analog source) including sampling and quantizing.

1/11/2013K K S16 Sampling: Pulse amplitude modulation (PAM)Converting the continuous input to discrete sequence.Quantization: Pulse code modulation (PCM)Encoding each quantized sample into a digital word including Uniform and Nonuniform QuantizationThe discrete information sources are characterized by source alphabet, symbol rate, source alphabet probabilities and probabilistic dependence of symbols in a sequence. The source alphabet will have letters, digits, and special characters available from the information source.The symbol rate is the rate at which the information sources the symbols / characters and its unit is symbol / sec.Source Encoding1/11/2013K K S17The process of efficiently converting the output of either an analog or a digital source into a sequence of binary digits is called source encoding or data compression, such as Huffman coding, JPEG (for picture), MPEG (for video).There are few important parameters used for source encoder as follows:Block size: Block size gives the number of distinct code-words that the encoder can represent and depends upon the number of bits in the codeword. As an example, the block size of 25 i.e., 32 code-words.Code-word length: It is number of bits used to represent the codeword. As example, if 5 bits are assigned to each code-word, then code-word length will be 5 bits.Average data rate: It is the output bits per second from the source encoder.

Channel Encoder1/11/2013K K S18The purpose of the channel encoder is to introduce, in a controlled manner, some redundancy in the binary information sequence which can be used at the receiver to overcome the effects of noise and interference encountered in the transmission of the signal through the channel. The channel encoder provides a different type of communication security than that provided by the encryptor. By adding some known redundancy to the message. Error control is achieved by adding extra bits to the output of the source encoded data. The extra redundancy bits added do not convey any information but provides detection and correction of errors in the message bits at the receiver. The coding and decoding process at the encoder and decoder needs the memory for processing of binary data. Typical channel codes: block codes, convolutional codes.

Digital Modulation1/11/2013K K S19Analog modulation methods are employed in analog communication system such as amplitude, frequency and phase modulation. A bit sequence cannot be transmitted from channel (fiber, cable, atmosphere and other transmission medium) directly. We must use the bit sequence to generate appropriate digital waveform, which is suitable to transmission medium. For example Pulse waveform (baseband signal) can directly transmitted through cable. For wireless, the baseband signals must be shift to a frequency band (RF signal), which is suitable to transmit through atmosphere. In digital communication system, digital modulation techniques are used such as amplitude shift keying (ASK), frequency shift keying (FSK), phase shift keying (PSK) and minimum shift keying (MSK).

1/11/2013K K S20The output of channel encoder is a digital signal composed of symbols. These digital symbols can be transmitted directly on a physical channel after passing through a line coding system (such as NRZ, RZ, Manchester, Differential Manchester). This type of transmission is referred to as base band modulation because the base band signal has been coded and transmitted at the base band frequency only. However, for wireless communication this digital signal is carrier modulated using sinusoidal as carrier signal. Carrier modulation enables efficient transmission of the signal by minimizing the effect of channel noise.

Communication Channel

1/11/2013K K S21The communications channel is the physical medium that is used to send the signal from the transmitter to the receiver. There are two types of channels, namely Point to point channel and broadcast channels. In point to point channel usually employ a variety of physical media, including wire lines, optical fiber cables, and wireless (microwave radio) such as telephone channels. On the other hand, in broadcast channels provide a capability where many receiving stations can be reached simultaneously from a single transmitter. In wireless transmission, the channel is usually the atmosphere (free space). Examples of broadcast channels are satellite communications, television broadcasting, radio broadcasting etc.

Advantages of digital communication1/11/2013K K S22Reduction of noise is possible in digital communication system.Reduction of distortion and other impairments is possible in digital communication system.Error detection and correction is possible in digital communication system that will reduce the probabilities of error by employing channel encoder.Regeneration of signal is easier than analog communication system.Signal processing and storage is easier due to use of digital signal processing techniques and digital computer.Security of data is possible due to encryption and decryption and spread spectrum coding provides antijamming facility.Data compression and image processing is possible in digital communication system.Large amount of noise interference may be tolerated.

1/11/2013K K S23Use of VLSI technology may be possible.Handling of multimedia information such as integration of voice, video and data is easier. There are many signal processing algorithms can be used to increase transmission rate and reliability of digital communication system. Digital circuits are more reliable and can be produced at lower cost than analog circuits, such as DSP, FPGA and ASIC. Digital signal is less subject to distortion and interference than analog signal. The digital signal is more easer to reborn or regenerated, compared to analog signals because:Digital signal has only two states (0 or 1)On the contrary, analog signal are not two-state signal. It can take an infinite variety of amplitude.

Disadvantages of Digital communication1/11/2013K K S24Digital communication requires more bandwidth than analog communication.It needs synchronizationLimitations of Communication System1/11/2013K K S25The primary limitations of information transmission by electrical means are bandwidth and noise.Bandwidth LimitationNoise Limitation

In this TEXT, we use the term bandwidth to refer to the property of a medium or the width of a single spectrum.

Note:1/11/2013K K S26Figure 3.13 Bandwidth

1/11/2013K K S27Example 3If a periodic signal is decomposed into five sine waves with frequencies of 100, 300, 500, 700, and 900 Hz, what is the bandwidth? Draw the spectrum, assuming all components have a maximum amplitude of 10 V.SolutionB = fh -fl = 900 - 100 = 800 HzThe spectrum has only five spikes, at 100, 300, 500, 700, and 900 (see Figure 13.4 )1/11/2013K K S28Figure 3.14 Example 3

1/11/2013K K S29Example 4A signal has a bandwidth of 20 Hz. The highest frequency is 60 Hz. What is the lowest frequency? Draw the spectrum if the signal contains all integral frequencies of the same amplitude.SolutionB = fh - fl20 = 60 - flfl = 60 - 20 = 40 Hz1/11/2013K K S30Figure 3.15 Example 4

1/11/2013K K S31Example 5A signal has a spectrum with frequencies between 1000 and 2000 Hz (bandwidth of 1000 Hz). A medium can pass frequencies from 3000 to 4000 Hz (a bandwidth of 1000 Hz). Can this signal faithfully pass through this medium? SolutionThe answer is definitely no. Although the signal can have the same bandwidth (1000 Hz), the range does not overlap. The medium can only pass the frequencies between 3000 and 4000 Hz; the signal is totally lost.1/11/2013K K S323.3 Digital SignalsBit Interval and Bit RateAs a Composite Analog SignalThrough Wide-Bandwidth MediumThrough Band-Limited MediumVersus Analog BandwidthHigher Bit Rate1/11/2013K K S33A digital signal

1/11/2013K K S34Example 6A digital signal has a bit rate of 2000 bps. What is the duration of each bit (bit interval)SolutionThe bit interval is the inverse of the bit rate.Bit interval = 1/ 2000 s = 0.000500 s = 0.000500 x 106 ms = 500 ms1/11/2013K K S35

Bit rate and bit interval

1/11/2013K K S36Figure Digital versus analog

1/11/2013K K S37A digital signal is a composite signal with an infinite bandwidth.

Note:1/11/2013K K S38The bit rate and the bandwidth are proportional to each other.

Note:1/11/2013K K S39Data Rate LimitNoiseless Channel: Nyquist Bit Rate

Noisy Channel: Shannon Capacity

Using Both Limits1/11/2013K K S40Noiseless Channel: Nyquist Bit Rate

1/11/2013K K S41In 1924, Henry Nyquist, has realized that even a perfect channel (i.e. noiseless channel) has a finite transmission capacity. He derived as expression for the maximum data rate for a finite bandwidth noiseless channel. Nyquist proved that any arbitrary signal has been passed through a low pass filter of bandwidth B, the filtered signal can be reconstructed completely by making only 2B (exact) sample per second. Sampling the line faster than 2B times per second is of no use because the higher frequency components such sampling could recover have already been filtered out.According to Nyquists theorem, if the signal consists of V discrete levels, the maximum data rate can be given as Maximum data rate = 2B log2 V bits/secExampleConsider a noiseless channel with a bandwidth of 3000 Hz transmitting a signal with two signal levels. The maximum bit rate can be calculated asBit Rate = 2 3000 log2 2 = 6000 bps1/11/2013K K S42Example 8Consider the same noiseless channel, transmitting a signal with four signal levels (for each level, we send two bits). The maximum bit rate can be calculated as: Bit Rate = 2 x 3000 x log2 4 = 12,000 bps1/11/2013K K S43Noisy Channel: Shannon Capacity

1/11/2013K K S44 In 1948, Claude Shannon carried Nyquists work further and extended it to the practical care of a channel subject to random noise. All practical channels are noisy channels and random noise deteriorates the situation rapidly. It is always that random or thermal noise present due to the motion of the molecules in the system. The amount of thermal noise present is determined by the ratio of the signal power to the noise power. This ratio is called signal to noise ratio.1/11/2013K K S45Now according to Shannons theorem, that the maximum data rate of a noisy channel where bandwidth is B Hz, and has SNR is S/N, is given by.Maximum number of bits/sec = B log2 (1+S/N)Example 9Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero. In other words, the noise is so strong that the signal is faint. For this channel the capacity is calculated asC = B log2 (1 + SNR) = B log2 (1 + 0) = B log2 (1) = B 0 = 01/11/2013K K S46Example 10We can calculate the theoretical highest bit rate of a regular telephone line. A telephone line normally has a bandwidth of 3000 Hz (300 Hz to 3300 Hz). The signal-to-noise ratio is usually 3162. For this channel the capacity is calculated asC = B log2 (1 + SNR) = 3000 log2 (1 + 3162) = 3000 log2 (3163)C = 3000 11.62 = 34,860 bps1/11/2013K K S47Example 11We have a channel with a 1 MHz bandwidth. The SNR for this channel is 63; what is the appropriate bit rate and signal level?SolutionC = B log2 (1 + SNR) = 106 log2 (1 + 63) = 106 log2 (64) = 6 MbpsThen we use the Nyquist formula to find the number of signal levels. 4 Mbps = 2 1 MHz log2 L L = 4First, we use the Shannon formula to find our upper limit.1/11/2013K K S48

SHANNON-LIMIT for information Capacity1/11/2013K K S49This theorem is concerned with the rate of transmission of information over a transmission media or communication channel. The term communication channel includes all the features and components parts of the transmission system which introduce noise, or limit the bandwidth.Shannons theorem defines that it is possible, in principle, to device a means whereby a communication system will transmit information with an arbitrarily small probability of error provided that the information rate R is less than or equal to a C the channel capacity. RC. (1)Where R= information rate C= channel capacityIt is commonly known as Shannon-Hartley capacity theorem. According to this the system capacity(c) is a function of the average received signal power s, the average noise power N, and bandwidth B. They are related as: C= Blog2 (1+S/N) (2)1/11/2013K K S50If bandwidth (B) is in hertz (Hz) and base is 2 of logarithmic then unit of channel capacity, is bits/sec.Theoretically as we have discussed in eqn-(1), it is possible to transmit information over such a communication channel at any rate R, where RC, with an arbitrarily small error.The important feature of the theorem is that it indicates that for RC, error free transmission is possible in the presence of noise.There is another statement associated with this theorem, that is given a source of M equally likely messages, with M>>1, which is generating information at a rate R and given a channel with a channel capacity C. if, now R>C, the probability of error is close to unity for every possible set of M transmitter signals. If the information rate R exceeds a specific value of channel capacity C, the error probability approaches unity, as M increases.The channel capacity C decides the maximum permissible rate at which an error free transmission of information is possible through it.