Adaptive Signal Detection Method Using Distance Estimation for Diffusion-Based Nanosensor Communication Systems

This article proposes an adaptive signal detection method for diffusion-based nanosensor communication (DNC). A major challenge for the performance improvement of DNC systems is signal decoding accuracy. High-accuracy decoding performance in DNC systems requires distance estimation between two nanosensors and the effective adaptation of system parameters. In this article, two concentration-based distance estimation methods are proposed. Based on the estimated distance, a protocol to determine the system parameters is designed such that the nanosensor adapts the concentration threshold automatically for the signal decoding and the sampling time for signal detection. The superiority of the proposed method is confirmed via simulation in MATLAB. The results demonstrate that the proposed method improves decoding accuracy compared with existing methods by mitigating the distance-decay effect of the molecular signal.