الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
Abstract
Molecular communication is a novel paradigm that can be used to enable
nano-machines to communicate with each other by using molecules instead of
electromagnetic waves. It has potential applications in the medical field. The
channel modeling and the capacity of molecular communication systems are
important issues, which have been previously studied.
In this thesis, we propose an approach to maximize the receiver response
in the molecular communication systems. The proposed approach is based on
the concept of matched filter. Moreover, we develop an analytical expression
for the probability of error. The simulation results confirm that the proposed
approach is superior compared to the traditional ones (delta and pulse). The
proposed approach is important in the targeted drug delivery systems, wherein
it enables the medical personnel to compute the maximum rate of drug transmission and thus maintain the effectiveness of the drug delivery system.
Moreover, we introduce a channel model for blood flow in the cardiovascular system while the receiver is based on the ligand-receptor binding mechanism. The proposed model considers the blood flow property in the living
body. It takes into consideration the impact of flow on the channel capacity,
and observes the change of molecular channel capacity according to physical
parameters such as the distance between the transmitter and the receiver.
Additionally, it illuminates the effect of the reception process on the channel
capacity. The reactive receiver is used to model the reception of the messenger
molecules where, the messenger molecules found in the sensing area of the receiver are considered as the ligands for the receiver’s receptors. Furthermore,
we demonstrate the effect of physical parameters of the human body such as
blood pressure, blood viscosity and vessel diameter on the channel capacity.
The error performance of the proposed model is evaluated in terms of bit error probability considering the impact of inter-symbol interference (ISI) and
noise.