Feedback-Controlled Adaptive Signal Detection Scheme for Diffusion-Based Molecular Communication Systems

This paper proposes a feedback-controlled adaptive method for detecting signals in diffusion-based molecular communication (MC) systems. Signal detection via a receiver nanomachine is a critical challenge for the exchange of information in MC systems. Incorrect estimations or small errors in signal detection can lead to high data detection errors. Existing methods for improving detection performance require high time costs or computational complexity. This paper proposes a simple and practical method that enables receiver nanomachines to automatically estimate signal detection times according to the measured molecular concentrations and weighted feedback errors. The proposed method adjusts the detection time even when the initial parameter values of the system are unknown to the receiver nanomachines. Simulations were performed to evaluate the bit error rate performance of the proposed and existing methods in terms of different data rates, transmission distances, and estimation error lengths under different initial conditions. The simulation results reveal that the implementation of the proposed method is simpler and demonstrates superior performance compared with that of existing methods.