In this paper, we study diffusive multi-hop mobile molecular communication (MMC) with drift in one-dimensional channel by adopting amplify-and-forward (AF) relay strategy. Multiple and single molecules type are used in each hop to transmit information, respectively. Under these two cases, the mathematical expressions of average bit error probability (BEP) of this system based on AF scheme are derived. We implement joint optimization problem whose objective is to minimize the average BEP with (Q+2)(Q + 2) optimization variables including (Q+1)(Q + 1) -hop distance ratios and decision threshold. Q{Q} is the number of relay nodes. Furthermore, considering that more optimization variables result in higher computation complexity, we use efficient algorithm which is adaptive genetic algorithm (AGA) to solve the optimization problems to search the location of each relay node and the decision threshold at destination node simultaneously. Finally, the numerical results reveal that AGA has a faster convergence speed and it is more efficient with fewer iterations compared with Bisection algorithm. The performances of average BEP with optimal distance ratio of each hop and decision threshold are evaluated. These results can be used to design multi-hop MMC system with optimal optimization variables and lower average BEP.

中文翻译：

---

带漂移的多跳扩散移动分子通信的中继位置和决策阈值联合优化


在本文中，我们通过采用放大转发（AF）中继策略来研究在一维信道中具有漂移的扩散多跳移动分子通信（MMC）。每跳分别使用多分子类型和单分子类型来传输信息。在这两种情况下，推导了该基于AF方案的系统的平均误码概率(BEP)的数学表达式。我们实现联合优化问题，其目标是使用 (Q+2)(Q + 2) 优化变量（包括 (Q+1)(Q + 1) 跳距离比和决策阈值）最小化平均 BEP。 Q{Q}是中继节点的数量。此外，考虑到更多的优化变量导致更高的计算复杂度，我们使用高效的算法——自适应遗传算法（AGA）来解决优化问题，同时搜索每个中继节点的位置和目的节点的决策阈值。最后，数值结果表明，与 Bisection 算法相比，AGA 具有更快的收敛速度，并且迭代次数更少，效率更高。评估了每跳最佳距离比和决策阈值下的平均 BEP 性能。这些结果可用于设计具有最佳优化变量和较低平均 BEP 的多跳 MMC 系统。