Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Molecular communication networks can be used to realise communication beten nanoscale devices. In a molecular communication network, transmitters and receivers communicate by using signalling molecules. At the receivers, the signalling molecules react, via a chain of chemical reactions, to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The output signal is noisy due to the stochastic nature of diffusion and chemical reactions.  aims to characterise the properties of the output signal.  do this by modelling the transmission medium, transmitter and receiver. In order to simplify the analysis,  model the transmitter as a sequence which specifies the number of molecules emitted by the transmitter over time.  considers two receiver reaction mechanisms, reversible conversion and linear catalytic, which can be used to approximate, respectively, ligand-receptor binding and enzymatic reactions. These two mechanisms are chosen because, if  consider them on their own (i.e. without the transmitter and diffusion), the ordinary differential equations describing the mean behaviour of these two reaction mechanisms have the same form; hover, if  consider the end-to-end behaviour from the transmitter signal to the mean/variance of the number of output molecules, then these two receiver reaction mechanisms have very  different  behaviours.  show this by deriving analytical expressions for the mean, variance and frequency properties of the number of output molecules of these two receiver reaction mechanisms. In addition, for reversible conversion,  are able to derive the exact probability distribution of the number of output molecules. Our model allows us to study the impact of design parameters on the communication performance. For example,  assume that our receiver is enclosed by a membrane and  study the impact of the diffusibility of molecules across this membrane on the communication performance.
['Chun Tung Chou']
I am writing a research paper on a idea Impact of Receiver Reaction Mechanisms on the Performance of Molecular Communication Networks
[{"from": "human", "value": "I am writing a research paper on a idea Impact of Receiver Reaction Mechanisms on the Performance of Molecular Communication Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Molecular communication networks can be used to realise communication beten nanoscale devices. In a molecular communication network, transmitters and receivers communicate by using signalling molecules. At the receivers, the signalling molecules react, via a chain of chemical reactions, to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The output signal is noisy due to the stochastic nature of diffusion and chemical reactions.  aims to characterise the properties of the output signal.  do this by modelling the transmission medium, transmitter and receiver. In order to simplify the analysis,  model the transmitter as a sequence which specifies the number of molecules emitted by the transmitter over time.  considers two receiver reaction mechanisms, reversible conversion and linear catalytic, which can be used to approximate, respectively, ligand-receptor binding and enzymatic reactions. These two mechanisms are chosen because, if  consider them on their own (i.e. without the transmitter and diffusion), the ordinary differential equations describing the mean behaviour of these two reaction mechanisms have the same form; hover, if  consider the end-to-end behaviour from the transmitter signal to the mean/variance of the number of output molecules, then these two receiver reaction mechanisms have very  different  behaviours.  show this by deriving analytical expressions for the mean, variance and frequency properties of the number of output molecules of these two receiver reaction mechanisms. In addition, for reversible conversion,  are able to derive the exact probability distribution of the number of output molecules. Our model allows us to study the impact of design parameters on the communication performance. For example,  assume that our receiver is enclosed by a membrane and  study the impact of the diffusibility of molecules across this membrane on the communication performance."}]