Asynchronous Neuro-Spike Array - Based Communication

Keyvan Aghababaiyan, V. Shah-Mansouri, B. Maham
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引用次数: 9

Abstract

Nano-networks employ novel nano-scale communication techniques. A new example of nano-networks is the artificial neural system where nano-machines are linked to neurons to treat the neurodegenerative diseases. Many of the nano-scale communication techniques are inspired by biological systems. Neuro-spike communication is one example of this communication paradigm which is exploited to transfer vital information through the nervous system by neurons or nano-machines. Neurons and nano-machines exploit spike rate and the temporal coding to transmit information by action potentials. However, the efficiency of these encoding methods decreases when the transmitter and receiver are asynchronous. Synchronization is beyond the capabilities of nano-machines. In this paper, first we propose a mathematical model for the jitter of the neuro-spike communication channel. Next, we propose an asynchronous neuro-spike array-based communication scheme in which the transmission order of the generated spikes by different elements of the nano-machines array is used to convey information. Thus, in this scheme, there is no need for time synchronization between the transmitter and receiver nano-machines. Finally, we evaluate our proposed scheme via numerical results. It can be observed that our scheme improves the communication rate in comparison to other schemes about 50%.
基于异步神经脉冲阵列的通信
纳米网络采用新颖的纳米级通信技术。纳米网络的一个新例子是人工神经系统,其中纳米机器与神经元连接以治疗神经退行性疾病。许多纳米级通信技术都受到生物系统的启发。神经脉冲通信是这种通信范式的一个例子,它被用来通过神经元或纳米机器在神经系统中传递重要信息。神经元和纳米机器利用脉冲速率和时间编码通过动作电位传递信息。然而,当发送端和接收端是异步时,这些编码方法的效率会降低。同步超越了纳米机器的能力。在本文中,我们首先提出了神经脉冲通信信道抖动的数学模型。接下来,我们提出了一种基于异步神经尖峰阵列的通信方案,该方案利用纳米机器阵列中不同元素产生的尖峰的传输顺序来传递信息。因此,在该方案中,不需要发送和接收纳米机之间的时间同步。最后,通过数值结果对所提出的方案进行了评价。可以观察到,与其他方案相比,我们的方案提高了约50%的通信速率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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