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. In popular terms, 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 (or numbers) from a finite alphabet (or limited set of numbers). 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 (a telephone cable or the radio waves propagation of a mobile phone antenna) 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.

A Historical Perspective of Digital Communications

The telegraph
The telegraph

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. His studies led him to conclude that for binary data transmission (transmitting one of two numbers, 0 or 1) over a noiseless channel of bandwidth W Hertz, the maximum pulse rate is 2W pulses per second.

N. Wiener
N. Wiener

Hartley extended this work in 1928 to non-binary data transmission, while Kolmogorov and Wiener independently in 1939 and 1942, respectively, solved the problem of optimally estimating a signal in the presence of additive noise. In 1948 Claude Shannon established the mathematical foundation for information transmission and derived fundamental limits for digital communication systems. His work can arguably be considered as the true beginning of the information age.

V. Kotelnikov
V. Kotelnikov

Another important contribution to the field of digital communication is the work of Kotelnikov in 1947, who provided a coherent analysis and consequently a principle for optimal design of such systems. His work was later extended by Wozencraft and Jacobs in 1965, leading to the principles used to design the communication systems of today.

The work of Hamming in 1950 on error control coding to combat detrimental effects of channel noise completes the classic contributions to modern digital communication systems.

C. Berrou
C. Berrou
A. Viterbi
A. Viterbi

Of more modern contributions, the Viterbi decoding algorithm for trellis codes, proposed by Andrew Viterbi in 1967 is now found in almost all wireless communication systems. Efficient error control decoding makes mobile communication systems what they are today. The latest significant leap forward for improvements of communications systems was in 1993 with the discovery of the "turbo principle" by Berrou and Glavieux. The special turbo codes developed based on these principles can be efficiently decoded using a very powerful iterative signal processing approach. The resulting coding system performs very close to fundamental limits for a range of different channels. In practical terms, this leads to the most efficient use of bandwidth and power, which is very important for portable wireless devices.

Modern Digital Communication Systems

A modern communication system is traditionally modelled as shown in the figure below. As illustrated in the figure, the current paradigm for digital communications systems is to separate the various functions of the system. For example, source coding and channel coding is done separately where source coding removes inherent source redundancy, while channel coding adds control redundancy to combat interference introduced over the channel. Based on this design paradigm, the signal processing required for different functionalities in the system are designed separately and applied sequentially in a concatenated fashion.

The figure below shows a typical system diagram of a modern digital communications system. You can click on the various components to learn about their function.

Digital Communications System Diagram

Digital Communications System. Click on the block to find out more.

Some Key Research Challenges

As mentioned, 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.

Specific projects may include:

  • Joint cross-layer communication protocol design;
  • Efficient communication protocols for ad-hoc networks;
  • Efficient system design for high speed data transmission over highly mobile channels;
  • Synchronization and channel estimation at very low signal-to-noise ratio;
  • Optimal receiver structures for unknown channels;
  • Efficient system design for wireless packet data transmission systems with random multiple access.

More Information

Australian Communications Theory Researchers

Researcher
Abbosh, Amin M
Abhayapala, Thushara D
Alexander, Paul D
Armstrong, Jean
Bhaskaran Pillai, Sibi Raj
Chan, Terence Ho Leung
Chen, Zhuo
Collings, Iain B
Cowley, William G
Daniels, Graham Ross
Davis, Linda M
Develi, Ibrahim
Dogancay, Kutluyil
Elkashlan, Maged
Evans, Jamie Scott
Grant, Alex J
Hanlen, Leif Whyte
Ho, Mark S C
Ho, Tsun Yue
Jayalath, Dhammika
Johnson, Sarah J
Karmakar, Nemai
Kennedy, Rodney Andrew
Kind, Adriel P.
Krongold, Brian
Krusevac, Snezana M
Lamahewa, Tharaka Anuradha
Land, Ingmar R
Lee, Wee Sit
Letzepis, Nicholas Alexander
Li, Yonghui
Lin, Zihuai
Maennel, Olaf Manuel
Manton, Jonathan H
Naguleswaran, Sanjeev
Ngo, Nghia Hieu
Nicol, Chris J
Ning, Jun
Ninness, Brett M
Nirmalathas, Thas A
Papandriopoulos, John
Perreau, Sylvie L
Pollock, Tony S
Ramamurthy, Balachander
Rasmussen, Lars K
Reed, Mark C
Reid, Aaron Barry
Rezaeian, Mohammad J
Rice, Mark
Rueffer, Bjoern S
Sadeghi, Parastoo
Schreier, Peter J.
Seberry, Jennifer
Shi, Zhenning
Sithamparanathan, Kandeepan
Smith, David Burton
Suraweera, Himal
Thanabalasingham, Thayaparan
Trajkovic, Vladimir
Tran, Le Chung
Vucetic, Branka S
Weller, Steven R
White, Langford B
Xiang, Wei
Yu, Limin
Yuan, Jinhong
Yuce, Mehmet Rasit
Zhang, Jian Andrew
Zhang, Wei
Zhou, Zhendong
Zhu, Weiping

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