Research Supervisor Connect

Design of Non-coherent Network Coding for Dynamically Changing Wireless Networks

Summary

Network coding schemes are expected to become one of the key radio technologies that could have a far reaching impact on the Australian economy. Subspace network coding is a very new branch of networkcoding, which now offers a novel approach to processing data in communication networks. The proposedprogram will contribute to theory, design, and development of a subspace coded system and nationwidedeployment of future wireless networks. The research outcomes are likely results in significant improvementsor breakthroughs in network throughput, reliability, network coverage, and considerable energy savings.

Supervisor

Dr Zihuai Lin.

Research location

Electrical and Computer Engineering

Program type

Masters/PHD

Synopsis

In this project we will consider multi-hop multicast data transmission in a wireless network. Themulticast model comprises multiple source nodes broadcasting data to multiple destinations across adynamically changing network. By dynamically changing, we refer to networks where the structureand topology may have time variability due to fading channels, interference and node mobility. Weare interested in non-coherent communication. By non-coherent, we mean that neither the sourcesnor the receivers have any knowledge of the network topology or the network nodes operations. Inlarge dynamically changing networks, collecting network information comes at a cost, as itconsumes bandwidth that could instead have been used for information transfer. Non-coherentcommunication allows for creating end-to-end systems completely oblivious to the network state.Our model is very general, and subsumes many specialized networks including peer-to-peer, ad-hoc,sensory and mobile networks. We will develop systematic design of joint network channel codingtechniques, capable of bringing network coding gains through data compression and channel codinggains through introducing structured redundancy.

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Opportunity ID

The opportunity ID for this research opportunity is 1837

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