Motivated by the fact that living cells use molecular circuits (i.e., a set of chemical reactions) for information processing, this paper investigates the problem of designing molecular circuits for demodulation. In our earlier work, we use a Markovian approach to derive a demodulator for diffusion-based molecular communication. The demodulation filters take the form of an ordinary differential equation, which computes the log-posteriori probability of a transmission symbol being sent. This paper considers the realization of these demodulation filters using molecular circuits assuming the transmission symbols are rectangular pulses of the same duration but different amplitudes, i.e., concentration modulation. This paper makes a number of contributions. First, we use time-scale separation and renewal theory to analytically derive an approximation of the demodulation filter from our earlier work. Second, we present a method to turn this approximation into a molecular circuit. By using simulations, we show that the output of the derived molecular circuit is approximately equal to the log-posteriori probability calculated by the exact demodulation filter if the log-posteriori probability is positive. Third, we demonstrate that a biochemical circuit in yeast behaves similarly to the derived molecular demodulation filter and is therefore a candidate for implementing the derived filter.
There were other examples of using molecular circuits for molecular communication. The paper @cite_32 presented a biological circuit for molecular communication from a system-theoretic perspective. There was also work on using analog circuits for soft detection @cite_41 and parity check decoder @cite_11 . The key difference between these few pieces of work and ours is that they use one sample point per symbol. Lastly, there is also work on using chemical reactions to produce transmission signals for molecular communication, see @cite_42 .
@cite_41 @cite_42 @cite_32 @cite_11
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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. Advances in the field of synthetic biology have been key to demonstration of molecular computing systems in general and DNA in particular. This paper presents an overview of how continuous-time, discrete-time, and digital signal processing systems can be implemented using molecular reactions and DNA. In this paper, discrete-time systems refer to sampled signals with continuous signal amplitude. Signals that are sampled in discrete time steps with digital amplitude are referred to as digital signals. Delay elements in sampled signals are implemented using molecular reactions in the form of molecular transfer reactions. Completion of all phases of transfer reactions once corresponds to a computation cycle. These molecular systems can be implemented in a fully-synchronous, globally-synchronous locally-asynchronous or fully-asynchronous manner. The paper also presents molecular sensing systems where molecular reactions are used to implement analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). Molecular implementations of digital logic systems are presented. A complete example of the addition of two molecules using digital implementation is described where the concentrations of two molecules are converted to digital by two 3-bit ADCs, and the 4-bit output of the digital adder is converted to analog by a 4-bit DAC. This system is demonstrated using both molecular reactions and DNA. A brief comparison of molecular and electronic systems is also presented. Abstract Molecular communication enables nanomachines to exchange information with each other by emitting molecules to their surrounding environment. Molecular nanonetworks are envisioned as a number of nanomachines that are deployed in an environment to share specific molecular information such as odor, flavor, or any chemical state. In this paper, using the stochastic model of molecular reactions in biochemical systems, a realistic channel model is first introduced for molecular communication. Then, based on the realistic channel model, we introduce a deterministic capacity expression for point-to-point, broadcast, and multiple-access molecular channels. We also investigate information flow capacity in a molecular nanonetwork for the realization of efficient communication and networking techniques for frontier nanonetwork applications. The results reveal that molecular point-to-point, broadcast, and multiple-access channels are feasible with a satisfactorily high molecular communication rate, which allows molecular information flow in nanonetworks. Furthermore, the derived molecular channel model with input-dependent noise term also reveals that unlike a traditional Gaussian communication channel, achievable capacity is affected by both lower and upper bounds of the channel input in molecular communication channels. Molecular Communication (MC) is an enabling paradigm for the interconnection of future devices and networks in the biological environment, with applications ranging from bio-medicine to environmental monitoring and control. The engineering of biological circuits, which allows to manipulate the molecular information processing abilities of biological cells, is a candidate technology for the realization of MC-enabled devices. In this paper, inspired by recent studies favoring the efficiency of analog computation over digital in biological cells, an analog decoder design is proposed based on biological circuit components. In particular, this decoder computes the a-posteriori log-likelihood ratio of parity-check-encoded bits from a binary-modulated concentration of molecules. The proposed design implements the required L-value and the box-plus operations entirely in the biochemical domain by using activation and repression of gene expression, and reactions of molecular species. Each component of the circuit is designed and tuned in this paper by comparing the resulting functionality with that of the corresponding analytical expression. Despite evident differences with classical electronics, biochemical simulation data of the resulting biological circuit demonstrate very close performance in terms of Mean Squared Error (MSE) and Bit Error Rate (BER), and validate the proposed approach for the future realization of MC components.