An optimal decoding algorithm for Molecular Communications systems with noise, memory, and pulse width

Abstract

Molecular Communications (MC) is a promising paradigm to achieve message exchange between nano-machines. Due to the specific characteristics of MC systems, the channel noise and memory significantly influence the MC system performance. Aiming to mitigate the impact of these two factors, an adaptive decoding algorithm is proposed by optimising the symbol determination threshold. In this paper, this novel decoding scheme is deployed onto a concentration-based MC system with the transmitter emission process considered. To evaluate the performance, an information theoretical approach is developed to derive the Bit Error Rate (BER) and the channel capacity. Simulations are also carried out to verify the accuracy of these formulations, to compare the performance difference against other decoding schemes, and to illustrate the performance deviation caused by different designing of relevant parameters. Furthermore, the performance of MC systems with the distance unknown is also analysed. Comparisons between distance-pre-known and distance-unknown systems are provided.

Improving adaptive receivers performance in molecular communication via diffusion

“…It should be noted that the gap between the two curves in not constant for different range of molecules. It is mainly because of the approximation we used in (11). As the molecules increased, the gap becomes more reasonable, since the Gaussian approximation will be closer to binomial.…”

“…This approach utilised the effect of ISI and perform better than fixed threshold detector under certain conditions. In [11], a decoding algorithm is proposed by optimising the threshold that has taken the influence of both previous symbols and the noise into consideration. The optimal threshold is derived by a mathematical approach to minimise the BER of the MC system.…”