CDM in Neural Communication Based on Oscillatory Characteristics of Membrane Potential

With the advancement of the Internet of Nanothings (IoNT), information networks within organisms are becoming increasingly sophisticated, making the transmission of data from IoNT to the external environment a key research focus. Neural communication, as a promising solution, utilizes action potentials (APs) to carry information. However, enhancing the efficiency of data transmission for multiple IoNT nodes in a complex biological environment presents significant challenges. To address these challenges, this paper proposes an adaptive code division multiplexing (CDM) schemes in neural communication based on the oscillatory characteristics of membrane potential, enabling parallel information transmission for multiple IoNT nodes. This scheme assigns each signal an orthogonal code sequence and superimposes them onto a shared channel. To accommodate the oscillatory properties described by the resonate-and-fire (RF) neuron model, our approach further encodes the superimposed signals in CDM schemes, converting both symbolic and numerical bits into binary data for transmission. Simulation results demonstrate that the proposed scheme significantly enhances interference resistance while enabling multiple signals to share a single neuron channel. This paper paves the way for the implementation of IoNT applications.