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Molecular
communication is a rising communication model for biological nano-machines. It
permits biological nano-machines to communicate to the external environment by
exchanging information among the molecules. Due to the biological nature of
biological nanomachines, molecular communication finds application to
measure the conditioning of the human body, the formation of tissues, etc. The
communication is performed by using mainly three units (i) transmitter (ii)
channel and (iii) receiver. At the transmitter side, the information is encoded,
in this research work, we are using the OFDM technique to encode the information
signal and then the encoded signal is passed to the external environment.
Initially, a molecular communication network is designed by using n number of
nano-machines. The network area of communication is defined by using 1000×1000
meter square height and width. The coverage area of each nano-machine is
defined using the area of the network which is 20 percent of the total area. The source
molecule and destination molecules are defined within the network. After this, the route is formed from source to destination. The collision may occur in the
communication path if there are more than one user transmitting data within the
same route. In such a case, a packet is dropped and the throughput of the network
decreases. To overcome this problem, we are using OFDM (Orthogonal frequency
division multiplexing). This technique helps to allow several molecules to
transmit information in a specified band, by dividing the offered bandwidth
into different narrow bandwidth carriers. Every molecule is allocated with
defined carries to transmit their information and the carriers are orthogonal to
each other. This results in decreasing interference as well as the collision
and hence increases the spectral efficiency. Also, ANN (artificial neural
network) is used to classify the best possible route within the molecular
communication network with the help of OFDM. To determine the efficiency of the
proposed work, the parameter such as BER (Bit error rate) and MSE (mean square
error) are measured in MATLAB.
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