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IEEE Trans Nanobioscience ; 16(4): 287-298, 2017 06.
Article in English | MEDLINE | ID: mdl-28541217

ABSTRACT

The progress of molecular communication (MC) is tightly connected to the progress of nanomachine design. State-of-the-art states that nanomachines can be built either from novel nanomaterials by the help of nanotechnology or they can be built from living cells which are modified to function as intended by synthetic biology. With the growing need of the biomedical applications of MC, we focus on developing bio-compatible communication systems by engineering the cells to become MC nanomachines. Since this approach relies on modifying cellular functions, the improvements in the performance can only be achieved by integrating new biological properties. A previously proposed model for molecular communication is using bacteria as information carriers between transmitters and receivers, also known as bacterial nanonetworks. This approach has suggested encoding information into the plasmids inserted into the bacteria which leads to extra overhead for the receivers to decode and analyze the plasmids to obtain the encoded information. Another scheme, which is proposed in this paper, is to determine the digital information transmitted based on the quantity of bacteria emitted. While this scheme has its simplicity, the major drawback is the low-data rate resulting from the long propagation of the bacteria. To improve the performance, this paper proposes a distributed modulation scheme utilizing three bacterial properties, namely, engineering of plasmids, conjugation, and bacterial motility. In particular, genetic engineering allows us to engineer the different combinations of genes representing the different series of bits. When compared with binary density modulation and the M-ary density modulation, it is shown that the distributed modulation scheme outperforms the other two approaches in terms of bit error probability as well as the achievable rate for varying quantity of bacteria transmitted, distances, as well as time slot length.


Subject(s)
Bacteria/genetics , Computers, Molecular , Nanotechnology/methods , Genetic Engineering , Synthetic Biology
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