This paper considers a diffusion-based molecular communication system, where the transmitter uses reaction shift keying (RSK) as the modulation scheme. We focus on the demodulation of RSK signal at the receiver. The receiver consists of a front-end molecular circuit and a back-end demodulator. The front-end molecular circuit is a set of chemical reactions consisting of multiple chemical species. The optimal demodulator computes the posteriori probability of the transmitted symbols given the history of the observation. The derivation of the optimal demodulator requires the solution to a specific Bayesian filtering problem. The solution to this Bayesian filtering problem had been derived for a few specific molecular circuits and specific choice(s) of observed chemical species. The derivation of such solution is also lengthy. The key contribution of this paper is to present a general solution to this Bayesian filtering problem, which can be applied to any molecular circuit and any choice of observed species.
For the receiver side, different receiver designs have been proposed in literature for molecular communication systems, e.g. @cite_13 @cite_9 @cite_35 @cite_43 @cite_25 . Similarly different demodulation schemes for molecular communication systems are presented in @cite_9 @cite_43 . A common idea in these papers is that discrete-time samples of the number of output molecules are used to compute the likelihood of the transmitted symbol. However, the demodulation of RSK uses continuous-time signals @cite_20 @cite_23 where the processing of such continuous-time signals requires an analog filter. We further shown in our earlier work @cite_20 @cite_36 that information processing using the uniformly sampled version of the signals generally will result in information loss. Similar conclusion was also arrived in @cite_11 from an information theoretic analysis on capacity.
@cite_35 @cite_36 @cite_9 @cite_43 @cite_23 @cite_13 @cite_25 @cite_20 @cite_11
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This paper considers a diffusion-based molecular communication system, where the transmitter uses reaction shift keying (RSK) as the modulation scheme. We focus on the demodulation of RSK signal at the receiver. The receiver consists of a front-end molecular circuit and a back-end demodulator. The front-end molecular circuit is a set of chemical reactions consisting of multiple chemical species. The optimal demodulator computes the posteriori probability of the transmitted symbols given the history of the observation. The derivation of the optimal demodulator requires the solution to a specific Bayesian filtering problem. The solution to this Bayesian filtering problem had been derived for a few specific molecular circuits and specific choice(s) of observed chemical species. The derivation of such solution is also lengthy. The key contribution of this paper is to present a general solution to this Bayesian filtering problem, which can be applied to any molecular circuit and any choice of observed species. Abstract Simulation-based and information theoretic models for a diffusion-based short-range molecular communication channel between a nano-transmitter and a nano-receiver are constructed to analyze information rates between channel inputs and outputs when the inputs are independent and identically distributed (i.i.d.). The total number of molecules available for information transfer is assumed to be limited. It is also assumed that there is a maximum tolerable delay bound for the overall information transfer. Information rates are computed via simulation-based methods for different time slot lengths and transmitter–receiver distances. The rates obtained from simulations are then compared to those computed using information theoretic channel models which provide upper bounds for information rates. The results indicate that a 4-input–2-output discrete channel model provides a very good approximation to the nano-communication channel, particularly when the time slot lengths are large and the distance between the transmitter and the receiver is small. It is shown through an extensive set of simulations that the information theoretic channel capacity with i.i.d. inputs can be achieved when an encoder adjusts the relative frequency of binary zeros to be higher (between 50 and 70 for the scenarios considered) than binary ones, where a ‘zero’ corresponds to not releasing and a ‘one’ corresponds to releasing a molecule from the transmitter. Molecular communication is a promising approach to realize the communication between nanoscale devices. In a diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules. The transmitter uses different time-varying functions of concentration of signalling molecules (called emission patterns) to represent different transmission symbols. The signalling molecules diffuse freely in the medium. The receiver is assumed to consist of a number of receptors, which 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 amount of time before reverting to the OFF state. This paper assumes that the receiver uses the continuous history of receptor state to infer the transmitted symbol. Furthermore, it assumes that the transmitter uses two transmission symbols and approaches the decoding problem from the maximum a posteriori (MAP) framework. Specifically, the decoding is realized by calculating the logarithm of the ratio of the posteriori probabilities of the two transmission symbols, or log-MAP ratio. A contribution of this paper is to show that the computation of log-MAP ratio can be performed by an analog filter. The receiver can therefore use the output of this filter to decide which symbol has been sent. This analog filter provides insight on what information is important for decoding. In particular, the timing at which the receptors switch from OFF to ON state, the number of OFF receptors and the mean number of signalling molecules at the receiver are important. Numerical examples are used to illustrate the property of this decoding method. Abstract In this paper, a strength-based optimum signal detection scheme for binary concentration-encoded molecular communication (CEMC) system has been presented. In CEMC, a single type of information molecule is assumed to carry the information from the transmitting nanomachine (TN), through the propagation medium, to the receiving nanomachine (RN) in the form of received concentration of information molecules at the location of the RN. We consider a pair of nanomachines communicating by means of on–off keying (OOK) transmission protocol in a three-dimensional ideal (i.e. free) diffusion-based unbounded propagation environment. First, based on stochastic chemical kinetics of the reaction events between ligand molecules and receptors, we develop a mathematical receiver model of strength-based detection scheme for OOK CEMC system. Using an analytical approach, we explain the receiver operating characteristic (ROC) curves of the receiver thus developed. Finally, we propose a variable threshold -based detection scheme and explain its communication range and rate dependent characteristics. We show that it provides an improvement in the communication ranges compared to fixed threshold -based detection scheme. (Part of this paper has been peer-reviewed and published in BWCCA-2012 conference in Victoria, BC, 12–14 November, 2012 [20] .)