In this paper, we consider the bacterial point-to-point and multiple-access molecular communications with ligand-receptors. For the point-to-point communication, we investigate common signaling methods, namely the Level Scenario (LS), which uses one type of a molecule with different concentration levels, and the Type Scenario (TS), which employs multiple types of molecules with a single concentration level. We investigate the trade-offs between the two scenarios from the capacity point of view. We derive an upper bound on the capacity using a Binomial Channel (BIC) model and the symmetrized Kullback-Leibler (KL) divergence. A lower bound is also derived when the environment noise is negligible. For the TS, we also consider the effect of blocking of a receptor by a different molecule type. Then, we consider multipleaccess communications, for which we investigate three scenarios based on molecule and receptor types, i.e., same types of molecules with Different Labeling and Same types of Receptors (DLSR), Different types of Molecules and Receptors (DMDR), and Same types of Molecules and Receptors (SMSR). We investigate the trade-offs among the three scenarios from the total capacity point of view. We derive some inner bounds on the capacity region of these scenarios when the environment noise is negligible. * This paper has been presented in part at the IEEE International Symposium on Information Theory (ISIT), Wan Chai, Hong Kong, June 2015.DRAFT arXiv:1509.05877v1 [cs.IT] 19 Sep 2015 examine the instantaneous effect of the multiple-access interference instead of its average value. In the following, we first concentrate on a point-to-point molecular communication and evaluate its capacity and the upper and lower bounds. Then we consider three multiple-access scenarios and for each, we evaluate the capacity region and some inner bounds.Our main contributions are as follows:• Point-to-Point Communication: We investigate the trade-offs between two bacterial point-to-point communication scenarios for ligand-receptors with fixed total number of molecules and receptors: (a) multi-type molecular communication with a single concentration level, and (b) single-type molecular communication with multiple concentration levels. At the first glance, scenario (a) introduces new degrees of freedom and reduces the intersymbol interference (ISI). However, since the number of molecules per type (the power per type) reduces increasing the number of types, we should examine the benefit of using different types of molecules. To make the comparison between scenario (a) and (b), we adopt the model of [8] in this work. In addition, a Markov model for the interactions between different types of molecules near the receptor is presented and the capacity for this model is computed numerically.• Upper and Lower Bounds for the BIC Capacity: Using KL divergence bound of [14], we derive an upper bound on the capacity of the point-to-point BIC model under given average and peak constraints on the channel input (Theorem 1). Based on numerical eviden...

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Chemical reactions are a prominent feature of molecular communication (MC) systems, with no direct parallels in wireless communications. While chemical reactions may be used inside the transmitter nodes, receiver nodes or the communication medium, we focus on its utility in the medium in this paper.Such chemical reactions can be used to perform computation over the medium as molecules diffuse and react with each other (physical-layer computation). We propose the use of chemical reactions for the following purposes: (i) to reduce signal-dependent observation noise of receivers by reducing the signal density, (ii) to realize molecular physical-layer network coding (molecular PNC) by performing the natural XOR operation inside the medium, and (iii) to reduce the inter-symbol interference (ISI) of other transmitters by canceling out the remaining molecules from previous transmissions. To make the ideas formal, we consider an explicit two-way relaying example with a transparent receiver (which has a signal-dependent noise). The proposed ideas are used to define a modulation scheme (which we call the PNC scheme). We compare the PNC with a previously proposed scheme for this problem where the XOR operation is performed at the relay node (using a molecular logic gate). We call the latter, the straightforward network coding (SNC). It is observed that in addition to the simplicity of the proposed PNC scheme, it outperforms the SNC scheme especially when we consider ISI. I. INTRODUCTIONWhile traditional wireless communication systems employ energy carriers (such as electromagnetic or acoustic waves) for communication, Molecular Communication (MC) utilizes physical molecules as This work was in part presented in the 2016 Iran Workshop on Communication and Information Theory (IWCIT) [1].DRAFT 2 its carriers of information. In diffusion-based MC system, the transmitter and the receiver are biological/engineered cells or electronic systems that release or receive molecules, while the channel is assumed to be a fluid medium in which molecules diffuse. Electromagnetic waves and molecular diffusion share similarities and differences. Both the electromagnetic wave equation and the Fick's second law of macroscopic diffusion are second-order linear partial differential equations. As a result, both lead to linear system models that satisfy the superposition property. However, there are also differences between electromagnetic waves and molecular diffusion. Notably, the degradation and attenuation of transmitted signals are more pronounced in molecular diffusion-based channels and seriously limit the transmission distance between the transmitter and the receiver [2]. Relaying is a solution for increasing the range of communication and has been utilized by nature in intracellular communication [3, Chapter 15]. In addition, while the measurement noise of a wireless receiver may be modeled by an additive Gaussian noise (the AWGN channel), some of the most promising molecular receptors, such as the ligand receiver and the transparent recei...

Abnormality detection and localization (ADL) have been studied widely in wireless sensor networks (WSNs) literature, where the sensors use electromagnetic waves for communication. Molecular communication (MC) has been introduced as an alternative approach for ADL in particular areas such as healthcare, being able to tackle the shortcomings of conventional WSNs, such as invasiveness, bioincompatibility, and high energy consumption. In this paper, we introduce a general framework for MCbased ADL, which consists of multiple tiers for sensing the abnormality and communication between different agents, including the sensors, the fusion center (FC), the gateway (GW), and the external node (e.g., a local cloud), and describe each tier and the agents in this framework. We classify and explain different abnormality recognition methods, the functional units of the sensors, and different sensor features. Further, we describe different types of interfaces required for converting the internal and external signals at the FC and GW. Moreover, we present a unified channel model for the sensing and communication links. We categorize the MC-based abnormality detection schemes based on the sensor mobility, cooperative detection, and cooperative sensing/activation. We also classify the localization approaches based on the sensor mobility and propulsion mechanisms and present a general framework for the externally-controllable localization systems. Finally, we present some challenges and future research directions to realize and develop MC-based systems for ADL. The important challenges in the MC-based systems lie in four main directions as implementation, system design, modeling, and methods, which need considerable attention from multidisciplinary perspectives.

The concentration of molecules in the medium can provide us very useful information about the medium. In this paper, we use this information and design a molecular flow velocity meter using a molecule releasing node and a receiver that counts these molecules. We first assume M hypotheses according to M possible medium flow velocity values and an L-sample decoder at the receiver and obtain the flow velocity detector using maximum-a-posteriori (MAP) method. To analyze the performance of the proposed flow velocity detector, we obtain the error probability, and its Gaussian approximation and Chernoff information (CI) upper bound. We obtain the optimum sampling times which minimize the error probability and the sub-optimum sampling times which minimize the Gaussian approximation and the CI upper bound. When we have binary hypothesis, we show that the sub-optimum sampling times which minimize the CI upper bound are equal. When we have M hypotheses and L → ∞, we show that the sub-optimum sampling times that minimize the CI upper bound yield to M 2 sampling times with M 2 weights. Then, we assume a randomly chosen constant flow velocity and obtain the MAP and minimum mean square error (MMSE) estimators for the L-sample receiver. We consider the mean square error (MSE) to investigate the error performance of the flow velocity estimators and obtain the Bayesian Cramer-Rao (BCR) and expected Cramer-Rao (ECR) lower bounds on the MSE of the estimators. Further, we obtain the sampling times which minimize the MSE. We show that when the flow velocity is in the direction of the connecting line between the releasing node and the receiver with uniform distribution for the magnitude of the flow velocity, and L → ∞, two different sampling times are enough for the MAP estimator.