Molecular communication (MC) is a paradigm that employs molecules as information transmitters, hence, requiring unconventional transceivers and detection techniques for the Internet of Bio-Nano Things (IoBNT). In this study, we provide a novel MC model that incorporates a spherical transmitter and receiver with partial absorption. This model offers a more realistic representation than receiver architectures in literature, e.g. passive or entirely absorbing configurations. An optimization-based technique utilizing particle swarm optimization (PSO) is employed to accurately estimate the cumulative number of molecules received. This technique yields nearly constant correction parameters and demonstrates a significant improvement of 5 times in terms of root mean square error (RMSE). The estimated channel model provides an approximate analytical impulse response; hence, it is used for estimating channel parameters such as distance, diffusion coefficient, or a combination of both. We apply iterative maximum likelihood estimation (MLE) for the parameter estimation, which gives consistent errors compared to the estimated Cramer-Rao Lower Bound (CLRB).

翻译：分子通信（MC）是一种以分子作为信息传递介质的通信范式，因此需要采用非常规的收发器和检测技术来支撑生物纳米物联网（IoBNT）。本研究提出了一种新颖的分子通信模型，该模型包含球形发射器和具有部分吸收能力的球形接收器。与文献中常见的接收器架构（例如被动式或完全吸收式配置）相比，该模型更加贴近实际。我们采用基于粒子群优化（PSO）的优化技术，精确估计接收到的累积分子数量。该方法能生成近乎恒定的校正参数，并在均方根误差（RMSE）方面实现了5倍的显著提升。所估计的信道模型能够提供近似的解析冲激响应，进而用于估计信道参数，如距离、扩散系数或两者的组合。我们应用迭代最大似然估计（MLE）进行参数估计，其估计误差与计算得到的克拉美-罗下界（CLRB）保持一致。