Maximum A-Posteriori Decoding for Diffusion-Based Molecular Communication Using Analog Filters


Molecular communication could be a promising approach to realize the communication between nanoscale devices. In a very diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules. The transmitter uses completely different time-varying functions of concentration of signalling molecules (called emission patterns) to represent different transmission symbols. The signalling molecules diffuse freely within the medium. The receiver is assumed to contains a number of receptors, that can be in ON or OFF state. When the signalling molecules arrive at the receiver, they react with the receptors and switch them from OFF to ON state probabilistically. The receptors remain ON for a random quantity of time before reverting to the OFF state. This paper assumes that the receiver uses the continual history of receptor state to infer the transmitted image. Furthermore, it assumes that the transmitter uses 2 transmission symbols and approaches the decoding drawback from the utmost a posteriori (MAP) framework. Specifically, the decoding is realized by calculating the logarithm of the ratio of the posteriori chances of the 2 transmission symbols, or log-MAP ratio. A contribution of this paper is to point out that the computation of log-MAP ratio will be performed by an analog filter. The receiver will so use the output of this filter to come to a decision which symbol has been sent. This analog filter provides insight on what information is important for decoding. In explicit, the timing at which the receptors switch from OFF to ON state, the quantity of OFF receptors and the mean number of signalling molecules at the receiver are vital. Numerical examples are used to illustrate the property of this decoding method.

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