An Engineered Neural Communication System Based on CDM Scheme for the Internet of Bio-Nano Things

Transmitting information in engineered neural communication systems is a promising solution to delay-sensitive applications for the Internet of bio-nano things (IoBNT). As widely used in wired and wireless communication systems, multiplexing could improve channel transmission efficiency in the neural communication system. In this paper, we model a neural communication system and propose a neural signal multiplexing scheme based on code division multiplexing (CDM) principle. The whole system including channel modeling, neural coding, multiplexing scheme, and decoding method is presented. The optimal threshold and computational complexity are analyzed. The performance of the proposed scheme is evaluated in terms of bit error rate (BER) and mutual information rate in comparison with our previous methods. The work can help researchers better understand the underlying mechanism of neural multiplexing and pave the way for the implementation of IoBNT applications.