The aim of the project is to study the fundamental principles of channel coding
(Using convolutional codes/veterbi decoding) & source coding (Using Lempel-Ziv algorithm), and sets out practical coding methods for achieving the performance improvements predicted by the theory.
The use of multiple antennas in most future wireless communication systems seems to be inevitable. Today, the main question is how to include multiple antennas and what are the appropriate methods for specific applications.
The goal of such a project is to study the space-time coding with some basic knowledge of digital communications.
The project starts with some background material on wireless communications and capacity of MIMO channels as covered in Chapters 1 and 2. A review of design criteria for space-time codes is covered in Chapter 3. A chapter 4 provides design criteria for Alamouti code. A chapter 5 provides design criteria for decoding. A chapter 6 provides the knowledge of modulation used. A chapter 7 provides the MATLAB implementation of all studied schemes for encoding and decoding.
A chapter 8 provides bibliography.
1.1 INTRODUCTION TO THE PROJECT
- Problem Statement
- Joint source coding (Lempel-Ziv) & channel coding (convolutional encoding / viterbi decoding) of digital data: simulation and implementation.
- To study different techniques of transmitting and receiving data and selecting the optimum one (convolutional coding).
- Project Description
In modern digital communication systems, source coding and channel coding is performed independently. This not only increases the complexity but also the time delay of the system. In this project channel coding and source coding are performed simultaneously which not only boost up the system but also makes data recovery more reliable. Furthermore SNR Vs BER graphs are studied.
- DIGITAL Vs ANALOG COMMUNICATION SYSTEMS
The basic difference between digital and analog communication systems depends upon the fact that how their performance is evaluated. Analog communication deals with a set of infinite waveforms so the receiver has to encounter continuous infinite number of waveforms. The performance of analog communication systems can be evaluated on the basis of,
- Percentage distortion
- Expected mean square error
between the transmitter and the receiver.
On the other hand, in digital communication system, the transmitted signals are represented using finite set of digits and the receiver, in advance, knows about the set. The performance of digital communication systems can be evaluated on the basis of,
- Probability of error
- Probability of incorrect digit detection
1.2.1 Why to Select Digital Communication?
Our inspiration for selecting the digital communication system lies on the fact that much development has been occurred in this field during the past 50 years. Now-a-days, a major portion of information is carried through digital communication media such as optical fiber, coaxial cable and microwave and satellite channels. Presently, we are bystanding a huge amount of growth in the development of personal communication systems which are based on transmitting the data in digital format such as images, video and voice. We believe that we will be shortly seeing an alternate for analog A.M., F.M. and television broadcast by transmission based on digital communication.
All these developments have encouraged us to follow the increasingly growing trend towards digital communication systems as a medium for transmitting information.
1.3 DIGITAL COMMUNICATION SYSTEM
1.3.1 Basic Elements of a Digital Communication System
Basic elements of a typical digital communication system are,
- Input signal
- Source encoder
- Channel encoder
- Channel decoder
- Source decoder
- Output signal
1.3.2 Block Diagram of a Digital Communication System
1.3.3 Overview of Digital Communication Process
In a typical digital communication system, the first step is to efficiently convert the output of, either an analog or digital source, into a sequence of binary digits by a process called source encoding.
Now, the sequence from the source encoder, in the form of digital digits, is passed to the channel encoder. Channel encoder adds some redundancy in the binary (in the form of 1's and 0's) information sequence. The purpose of adding the redundant data into the binary information sequence is to overcome the effects of noise and interference which corrupts the signal during transmission and with the help of this redundant data, it becomes easier for the receiver to overcome these effects. The addition of redundancy increases the reliability of the received data.
Now, from the channel encoder, the binary data is passed to the digital modulator. The purpose of the digital modulator is to map the binary data into signal waveforms and transmits it.
The signal is now transmitted through a channel, which serves as an interface between digital modulator and digital demodulator and is also responsible for the addition of noise in the digital data. The channels which are most commonly used are,
- Wire line channels
- Fiber optic channels
- Wireless electromagnetic channels
- Underwater acoustic channels
After passing through the channel, the signal is received and is demodulated with the help of a digital demodulator. The digital demodulator scans the corrupted transmitted waveform and reduces each waveform to a single number to represent the transmitted data symbol. With the help of redundancy, which was added in the transmitted data, the decoder corrects the signal from the points where it was corrupted.
From the digital demodulator, the sequence enters the channel decoder and from there, it enters the source decoder and from the knowledge of source encoding technique used before, it starts reconstructing the original signal. The signal at the output of the source decoder is not the original one but is an approximation of the original signal.
The purpose of writing a complete chapter on digital communication system is to explain the reader about the importance of channel coding and source coding in digital communication system.