Recent advances in nanotechnology enables the miniaturization of devices and communication networks. Molecular communication is a new communication paradigm where molecules are used to transfer information. Diffusion-based molecular communication is a promising approach for nanocommunication. However, according to the random nature of the diffusion of a molecule, the estimation of a molecule's arriving time at the receiver is difficult and a late arrival of a molecule causes interference between different symbols in detection. The inter-symbol interference (ISI) lowers the system's performance significantly, which inhibits communication at high data rates. Before addressing these problems, a pre-determined threshold for the received signal must be calculated to make a decision. In this research, an analytical technique is proposed to determine the optimum threshold, whereas other thresholds are calculated empirically in the literature. In addition to the requirement of a large sample set of received molecule counts to represent the system characteristics in empirical calculation, a slight change in the system model parameters such as temperature, requires all calculations to be repeated. The main objective of this thesis is to mitigate the ISI effect of diffusion-based molecular communication employing binary Concentration shift keying modulation scheme. We consider two worst case conditions in which the probability of correct detections are the least ones. We approximate these conditions using Gaussian distribution and calculate a new decision threshold based on the ISI effect of the communication channel Numerical results show that the proposed decision threshold method mitigates the ISI significantly and allows reliable transmissions inside nanocommunications. Key Words : Molecular Communications, Diffusion, Inter-Symbol Interference (ISI), ISI Cancellation, Brownian Motion, Decision Threshold.
