This work considers a cooperative communication system in 3-D fluid medium in which the flow of molecules is supported by the drift and the diffusion phenomena. To enhance the system performance, the equal gain combining is used at the destination nanomachine (DN) where the molecular signals arriving from the direct and the cooperative paths are combined together by employing equal weights. Using the gradient descent algorithm, the optimum threshold at DN, and the optimal number of molecules transmitted from source and cooperative nanomachines are obtained. For this purpose, the convex constraints are determined using the closed-form expression for the average probability of error at DN. Finally, the accuracy of the analytical results is validated through the particle/ Monte Carlo-based simulations.

中文翻译：

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基于扩散对流的3-D分子协作通信中的梯度下降优化。

这项工作考虑了在3-D流体介质中的协作通信系统，其中的分子流动由漂移和扩散现象支持。为了增强系统性能，在目标纳米机（DN）处使用等增益合并，其中通过采用相等的权重将来自直接路径和协作路径的分子信号合并在一起。使用梯度下降算法，可以获得DN的最佳阈值以及从源和协作纳米机传输的最佳分子数。为此，使用闭合形式的表达式为DN处的平均错误概率确定凸约束。最后，通过基于粒子/蒙特卡洛的模拟验证了分析结果的准确性。