Performance Analysis of a Biologically Inspired Collective Gradient Detection Method for a Bio-Nanomachine Cluster

In molecular communication, information can be encoded on the concentration gradient of signal molecules, making gradient detection an important issue. This letter considers a biologically inspired method for a cluster of bio-nanomachines to perform collective gradient detection. It develops a mathematical model of the collective gradient detection method, and uses the model to analyze its performance. One of the major findings reported in this letter is the existence of an optimal cluster size that can maximize the gradient detection performance. The contributions of this letter include exploring a new research direction in molecular communication, where a cluster of bio-nanomachines is used as a unit of molecular communication systems.