AI 中文总结
本文针对配体受体扩散分子通信，推导出每比特分子释放数量的闭式最优规则，使受体解离常数等于两比特条件浓度几何平均值，精确最小化比特错误概率，并经仿真验证。
AI 中文摘要
每比特释放的分子数量是基于扩散的分子通信（MC）的基本设计变量，而配体-受体接收方式打破了“越多越好”的直觉。释放分子过少会使结合受体的观测结果淹没在结合噪声中，而释放过多则会放大累积的符号间干扰并使有限的受体群体饱和，同样使观测结果难以区分。因此，可靠性在某个内部工作区域达到峰值，而该区域的位置似乎需要对信道动态进行穷举搜索。在本文中，我们证明对于一种生物学上合理的接收机，该搜索可以避免，该接收机无需信道状态信息或决策阈值即可比较连续的结合受体计数。我们推导出一个闭式传输规则，该规则设置每比特释放的分子数量，使得受体解离常数等于两个比特条件下接收浓度水平的几何平均值，并证明该规则精确地最小化无记忆二项式受体模型的比特错误概率，并通过欧拉-麦克劳林对干扰的评估将其表示为物理信道参数。对信道和受体参数进行时域蒙特卡洛扫描，并通过基于粒子的模拟进行佐证，结果表明经验最优的释放数量与预测一致，或略高于预测（相差一个小因子）。
英文摘要
The number of molecules released per bit is a fundamental design variable of diffusion-based molecular communication (MC), and ligand-receptor reception breaks the more-is-better intuition. Too few molecules leave the bound-receptor observations buried in binding noise, while too many amplify the accumulated intersymbol interference and saturate the finite receptor population, again making the observations indistinguishable. Reliability therefore peaks in an interior operating region whose location seems to require an exhaustive search over the channel dynamics. In this paper, we show that this search can be obviated for a biologically plausible receiver that compares consecutive bound-receptor counts without channel state information or a decision threshold. We derive a closed-form transmission rule, which sets the number of molecules released per bit such that the receptor dissociation constant equals the geometric mean of the two bit-conditioned received concentration levels, prove that it exactly minimizes the bit error probability of a memoryless binomial receptor model, and express it in the physical channel parameters through an Euler--Maclaurin evaluation of the interference. Time-domain Monte Carlo sweeps of the channel and receptor parameters, corroborated by particle-based simulations, show that the empirically optimal release count coincides with the prediction or lies above it by a small factor.
