  In this work, we investigate the communication reliability for
diffusion-based molecular communication, using the indicator of bit error rate
(BER). A molecular classified model is established to divide molecules into
three parts, which are the signal, inter-symbol interference (ISI) and noise.
We expand each part separately using molecular absorbing probability, and
connect them by a traditional-like formula. Based on the classified model, we
do a theoretical analysis to prove the feasibility of improving the BER
performance. Accordingly, an adaptive threshold variation (ATV) algorithm is
designed in demodulation to implement the goal, which makes the receiver adapt
the channel condition properly through learning process. Moreover, the
complexity of ATV is calculated and its performance in various noisy channel is
discussed. An expression of Signal to Interference plus Noise Ratio (SINR) is
defined to verify the system performance. We test some important parameters of
the channel model, as well as the ATV algorithm in the simulation section. The
results have shown the performance gain of the proposal.
