Student research opportunities
Theoretical Analysis and Transmission Design of Molecular Communications
Project Code: CECS_1077
This project is available at the following levels:
Engn4200, Masters
Keywords:
Molecular communications, nano-scale networks, communication theory, information theory, channel model.
Supervisor:
Dr Nan YangOutline:
Biological nanomachines are nanoscale to microscale devices that either exist in the biological world or are artificially created from biological materials and that perform simple functions such as sensing, logic, and actuation. Molecular communication is a new paradigm for communication between nanomachines over a short (nanoscale or microscale) range, in which information is encoded to and decoded from molecules, rather than electrons or electromagnetic waves. Since nanomachines are too small and simple to communicate using electrons or electromagnetic waves, molecular communication provides a novel mechanism for nanomachines to communicate by propagating molecules carrying information. The aim of this project is to exploit the theoretical fundamentals of molecular communication channel and to design robust molecular communication schemes.
NB: This project may be temporarily unavailable in some semesters.
Goals of this project
1. Exploit the channel limits based on information theory and propose accurate mathematical models to establish the theoretical fundamentals of molecular communication channels.
2. Design robust transmission schemes based on the properties of molecules and propagation environment.
Requirements/Prerequisites
A high self-motivation, a solid background in communication and electronic engineering, a strong grounding in mathematical skills, and a good level of programming in Matlab.
Student Gain
A thorough understanding on molecular communication theory.
Background Literature
[1] S. Hiyama et al., "Molecular communication," in Proc. 2005 Nano Sci. and Technol. Institute Conf., 2005, pp. 391–394.
[2] A. W. Eckford, "Molecular communication: Physically realistic models and achievable information rates," arXiv:0812.1554v1, 8 December 2008.
