Research On Incoherent Signal Detection Technology Of Diffused Molecular Communication

Bio-molecular diffusion communication(MCvD)is one of the most feasible communication technologies in nano-networks.Traditional MCvD systems only focus on the concentration of a single messenger molecule at the receiving end,and ignore the dynamic co-variation of other molecules caused by the biochemical reaction mechanism occurring at any time in the organism.Moreover,in the process of molecular communication,the long tail effect of Channel Impulse Response(CIR)is the main cause of InterSymbol Interference(ISI).Reducing the serious inter-symbol interference caused by the response of long-tail diffused Channel is the main goal of molecular communication systems.In order to improve the detection performance,the existing coherent detection algorithms need to obtain the unknown Channel Status Information(CSI)of the diffused channel,which usually requires a lot of time and energy resources.Computational complexity is often overwhelming,so low-complexity detectors are a promising alternative.In addition,traditional linear processing techniques usually require a high Signal to Noise Ratio(SNR)to achieve the desired performance.The above two points are the biggest obstacles to applying existing solutions to molecular communication scenarios where noise and interference in biological environments are prevalent.Aiming at the characteristics and pain points in the above molecular communication scenarios,the research work in this paper is mainly in the following aspects:1)In order to reduce the interference of inter-symbol interference(ISI)and background noise in the process of molecular free diffusion,a nonlinear signal detector based on diversity was proposed in this paper by taking full advantage of the universal biochemical reaction characteristics of multi-molecules to realize signal detection with low complexity.Among them,nonlinear filters are inspired by stochastic resonance present in various biological systems,which can convert noise into useful signals and improve the output signal-to-noise ratio.2)The general local convexity of the observed signal is extracted,and different signals are received through the characteristics of the signals received at the receiving end,namely the dynamic transient characteristics of enzymes,compounds and residual molecules,rather than the hidden channel state information(CSI),which avoiding CSI estimation and only involving summing,thus greatly reducing the complexity of the algorithm.3)In the scenario of the proposed SIMO system with single input and multiple output,combined with the multi-matter measure,the joint decision is made through the information fusion strategy,so as to fully make use of the channel information,fully obtain the potential diversity gain of the system,and compare with the typical incoherent detection algorithm to verify the algorithm performance.The numerical results show that,compared with formal optimal linear method,the required signal-to-noise ratio can be reduced by 4 dB by using the multi-material information fusion judgment strategy based on diversity incoherent detection at the receiver,while the required signal-to-noise ratio can be reduced by 7 dB under the stochastic resonance excitation nonlinear filter.In conclusion,this method has a broad application prospect in the emerging nanoscale communication.