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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In the Molecular Communication (MC), molecules are utilized to encode, transmit, and receive information. Transmission of the information is achieved by means of diffusion of molecules and the information is recovered based on the molecule concentration variations at the receiver location. The MC is very prone to intersymbol interference (ISI) due to residual molecules emitted previously. Furthermore, the stochastic nature of the molecule movements adds noise to the MC. For the first time, we propose four methods for a receiver in the MC to recover the transmitted information distorted by both ISI and noise. We introduce sequence detection methods based on maximum a posteriori (MAP) and maximum likelihood (ML) criterions, a linear equalizer based on minimum mean-square error (MMSE) criterion, and a decision-feedback equalizer (DFE) which is a nonlinear equalizer. We present a channel estimator to estimate time varying MC channel at the receiver. The performances of the proposed methods based on bit error rates are evaluated. The sequence detection methods reveal the best performance at the expense of computational complexity. However, the MMSE equalizer has the lowest performance with the lowest computational complexity. The results show that using these methods significantly increases the information transmission rate in the MC. 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. In this paper, we perform receiver design for a diffusive molecular communication environment. Our model includes flow in any direction, sources of information molecules in addition to the transmitter, and enzymes in the propagation environment to mitigate intersymbol interference. We characterize the mutual information between receiver observations to show how often independent observations can be made. We derive the maximum likelihood sequence detector to provide a lower bound on the bit error probability. We propose the family of weighted sum detectors for more practical implementation and derive their expected bit error probability. Under certain conditions, the performance of the optimal weighted sum detector is shown to be equivalent to a matched filter. Receiver simulation results show the tradeoff in detector complexity versus achievable bit error probability, and that a slow flow in any direction can improve the performance of a weighted sum detector. 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] .) Reaction shift keying (RSK) is a recently proposed modulation scheme for diffusion-based molecular communication networks. For RSK, the transmitter uses different chemical reactions to generate different emission patterns to represent different symbols. The receiver front end consists of a molecular circuit and the back end uses a bank of demodulation filter for detection. The aim of this paper is to study the impact of the choice of molecular circuits on communication performance. We consider two circuits: (1) ligand-receptor binding with feedback regulation; (2) ligand-receptor with multiple binding sites. For each circuit, we derive the maximum a posteriori demodulation filter by solving a Bayesian filtering problem. We show that appropriate amount of feedback can reduce symbol error rate. We also show how the choice of measurements in the multiple multiple binding site case can affect communication performance. This paper studies the mitigation of intersymbol interference in a diffusive molecular communication system using enzymes that freely diffuse in the propagation environment. The enzymes form reaction intermediates with information molecules and then degrade them so that they cannot interfere with future transmissions. A lower bound expression on the expected number of molecules measured at the receiver is derived. A simple binary receiver detection scheme is proposed where the number of observed molecules is sampled at the time when the maximum number of molecules is expected. Insight is also provided into the selection of an appropriate bit interval. The expected bit error probability is derived as a function of the current and all previously transmitted bits. Simulation results show the accuracy of the bit error probability expression and the improvement in communication performance by having active enzymes present. Diffusion-based communication refers to the transfer of information using molecules as message carriers whos ep rop- agation is governed by the laws of molecular diffusion. It has been identified that diffusion-based communication is one of the most promising solutions for end-to-end communication between nanoscale devices. In this paper, the design of a diffusion-based communication system considering stochastic signaling, arbitrary orders of channel memory, and noisy receptio ni s proposed. The diffusion in the cases of one, two, and three dimensions are all considered. Three signal processing techniques for the molecular concentration with low computational complexity are proposed. For the detector design, both a low-complexity one-shot optimal detector for mutual information maximization and a near Max- imum Likelihood (ML) sequence detector are proposed. To the best of our knowledge, our paper is thefirst that gives an analytical treatment of the signal processing, estimation, and detection prob- lems for diffusion-based communication in the presence of ISI and reception noise. Numerical results indicate that the proposed signal processing technique followed by the one-shot detector achieves near-optimal throughput without the need of ap riori information in both short-range and long-range diffusion-based communication scenarios, whic hs uggests an ML sequence de- tector is not necessary. Furthermore, the proposed receiver design guarantees diffusion-based communication to operate without failure even in the case of infinite channel memory. A channel capacity of 1 bit per channel utilization can be ultimately achieved by extending the duration of the signaling interval. In a diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules (or ligands) in a fluid medium. This paper assumes that the transmitter uses different chemical reactions to generate different emission patterns of signalling molecules to represent different transmission symbols, and the receiver consists of receptors. When the signalling molecules arrive at the receiver, they may react with the receptors to form ligand-receptor complexes. Our goal is to study the demodulation in this setup assuming that the transmitter and receiver are synchronised. We derive an optimal demodulator using the continuous history of the number of complexes at the receiver as the input to the demodulator. We do that by first deriving a communication model which includes the chemical reactions in the transmitter, diffusion in the transmission medium and the ligand-receptor process in the receiver. This model, which takes the form of a continuous-time Markov process, captures the noise in the receiver signal due to the stochastic nature of chemical reactions and diffusion. We then adopt a maximum a posteriori framework and use Bayesian filtering to derive the optimal demodulator. We use numerical examples to illustrate the properties of this optimal demodulator. We consider a channel model based on the diffusion of particles in the medium which is motivated by the natural communication mechanisms between biological cells based on exchange of molecules. In this model, the transmitter secretes particles into the medium via a particle dissemination rate. The concentration of particles at any point in the medium is a function of its distance from the transmitter and the particle dissemination rate. The reception process is a doubly stochastic Poisson process whose rate is a function of the concentration of the particles in the vicinity of the receiver. We derive a closed-form for the mutual information between the input and output processes in this communication scenario and establish useful properties about the mutual information. We also provide a signaling strategy using which we derive a lower bound on the capacity of the diffusion channel with Poisson reception process under average and peak power constraints. Furthermore, it is shown that the capacity of discretized diffusion channel can be a negligible factor of the capacity of continuous time diffusion channel. Finally, the application of the considered model to the molecular communication systems is discussed.