XXVII. Work in two groups. Group 1 should list all the advantages of using the Internet. Group 2 is to list all the disadvantages. Then together consider how disadvantages could be minimized.

Advantages of the Internet	Disadvantages of the Internet
Ability to do research from your home versus research libraries	There is a lot of wrong information on the Internet

XXVIII. Using the list you compiled in previous task, describe in written form the advantages and disadvantages of the Internet. Use linking words from Appendix 1.

UNIT 7

COMMUNICATIONS SYSTEMS

I. a) Communications systems enable users to send and receive data and information. In groups of 3 make a list of communications systems. Compare with the class.

b) Here are examples of communications systems. How often do you use these technologies? For which purposes? Discuss with the class.

e-mail voice mail smart phone teleconferencing

videoconferencing e-commerce bulletin board system GPS

FAX the Internet the Web instant messaging

II. Work in pairs. Discuss advantages and disadvantages of one of the items of communications systems stated above. Share your ideas with the class.

III. The figure below shows the model of the framework in which communication systems function. Could you explain how it works?

IV. Read and translate the text. What are the Communication and Information theories based on?

Communication theory

The basis of Information Technology and Communications (IT&C) is the processing and transmission of information. Information theory places well-defined limits on what is possible in terms of our everyday use of information, while communication theory defines principles upon which practical communication systems are designed. Information theory tells us how well we can theoretically do and communication theory tells us how we can practically do it.

Communication and information theory are the theories of modern digital communication systems, where "digital" means that we are transmitting information as symbols from a finite alphabet. Although physical signals are continuous waveforms in time, the principles of communication theory, allows us to consider the continuous waveforms we are transmitting and receiving over a noisy and interfering communication channel as a digital system, randomly perturbing the information that we are transmitting.

The translation of physically transmitted and received electrical signals into an equivalent digital system, transmitting and receiving digital numbers represents the very heart of communication theory. This, in turn, allows for advanced signal processing techniques to be applied in transmitters and receivers, leading to the design of increasingly more efficient digital communication systems, closer and closer to fundamental limits.

It is remarkable that the earliest form of electrical communication, namely telegraphy developed by Samuel Morse in 1837, was a digital communication system. Although Morse was responsible for the development of the first electrical digital communication system, the beginnings of what we now regard as modern digital communications stem from the work of Nyquist in 1924.

The current paradigm for digital communications networks is to separate the various functions of the network. However information theory indicates that a more coordinated system design may be more efficient. This means that joint design of multiple functionalities across multiple layers in the communication protocol stack, with corresponding joint receiver processing may lead to more efficient communications networks. The problem is that joint processing in many cases leads to a prohibiting level of processing complexity. A key challenge is to find processing strategies that approach optimal performance, but has an implementable level of complexity. The iterative paradigm applied in turbo coding may be a way forward.

Another key challenge is introduced by the development of turbo coding. Now it is possible to communicate close to fundamental limits, leading to very power-efficient communication. In popular terms, we can now in principle build decoders that can communicate at signal levels which are virtually below the inherent noise level in the receiver electronics. Communicating at such low signal-to-noise levels makes it a very difficult challenge to synchronize and estimate channel parameters necessary for the signal processing required prior to decoding.