漂移扩散分子通信的到达模型及误差分析
Arrival Modeling and Error Analysis for Molecular Communication via Diffusion with Drift
摘要：
分子扩散通讯（MCvD）中分子的到达是一个计数过程，本质上呈二项分布。即使二项式过程很好地描述了分子的到达，当考虑连续发送的符号时，该过程也难以与二项式累积分布函数（CDF）一起工作。因此，在文献中，使用二项分布的泊松和高斯近似。在本文中，我们分析了这两个近似的二项式模型的到达过程中的MCvD漂移。考虑到距离，漂移速度，和发射的分子的数量，我们调查的区域中，无论是泊松或高斯模型是更好的根均方误差（RMSE）的CDF，我们通过数值模拟确认该区域的边界。此外，我们推导出连续通信的错误概率，并分析哪种模型更准确地近似它。
英文摘要：
The arrival of molecules in molecular communication via diffusion (MCvD) is a counting process, exhibiting by its nature binomial distribution. Even if the binomial process describes well the arrival of molecules, when considering consecutively sent symbols, the process struggles to work with the binomial cumulative distribution function (CDF). Therefore, in the literature, Poisson and Gaussian approximations of the binomial distribution are used. In this paper, we analyze these two approximations of the binomial model of the arrival process in MCvD with drift. Considering the distance, drift velocity, and the number of emitted molecules, we investigate the regions in which either Poisson or Gaussian model is better in terms of root mean squared error (RMSE) of the CDFs; we confirm the boundaries of the region via numerical simulations. Moreover, we derive the error probabilities for continuous communication and analyze which model approximates it more accurately.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
