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Non-Linear Signal Detection for Molecular Communications

Molecular communications convey information via diffusion propagation. The inherent long-tail channel response causes severe inter-symbol interference, which may seriously degrade signal detection performances. Traditional linear signal detection techniques, unfortunately, require both high complexity and a high signal-to-noise (SNR) ratio to operate. In this paper, we proposed a new non-linear signal processing paradigm inspired by the biological systems that achieves low-complexity signal detection even in low SNR regimes. First, we introduce a stochastic resonance inspired non-linear filtering scheme for molecular communications, and show that it significantly improves the output SNR by transforming the noise energy into useful signals. Second, we design a novel non-coherent detector by exploiting the transient features of molecular signaling, which are independent of channel response and involves only lowcomplexity linear summation operations. Numerical simulations show that this new scheme can improve the detection performance remarkably (approx. 7dB gain), even when compared against linearly optimal coherent methods. This is one of the first attempts to demodulate molecular signals from an entirely biological point of view, and the designed non-linear noncoherent paradigm will provide significant potential to the design and future implementation of nano-systems in noisy biological environments.