🤖 AI Summary
本文提出了一种基于分子脉冲阵列的神经尖峰通信方案，通过特定排列而非精确时间同步来编码信息，以解决纳米机器资源受限下的同步难题。
📝 Abstract
In this paper, we investigate a neuro-spike communication system designed to bridge severed connections between damaged neurons using auxiliary nano-machines. Natural neuro-spike communication typically relies on instantaneous spike rates and temporal intervals to convey information. However, these temporal encoding schemes require exact time synchronization between the transmitter and receiver, a requirement that poses a significant challenge for resource-constrained nano-machines. To address this issue, it is imperative for future intra-body nano-networks to develop communication schemes that operate under reduced-order synchronization (e.g., symbol-synchronized). In this paper, we propose a novel neuro-spike array-based communication scheme where information is encoded through the specific arrangement of distinct molecular pulses emitted by nano-machines. By distinguishing symbols based on the sequence of these emissions rather than their exact timing, the need for stringent time synchronization is eliminated. We theoretically analyze the performance of the proposed scheme by deriving expressions for the probability of inter-symbol interference (ISI), error probability, and the achievable communication rate. Analytical and numerical results demonstrate that our array-based scheme significantly outperforms previously proposed symbol-synchronized models, providing a 75% - 150% enhancement in the communication rate across various diffusion coefficients.