Arash Einolghozati

Capacity of discrete molecular diffusion channels

In diffusion-based molecular communications, messages can be conveyed via the variation in the concentration of molecules in the medium. In this paper, we intend to analyze the achievable capacity in transmission of information from one node to another in a diffusion channel. We observe that because of the molecular diffusion in the medium, the channel possesses memory. We then model the memory of the channel by a two-step Markov chain and obtain the equations describing the capacity of the diffusion channel. By performing a numerical analysis, we obtain the maximum achievable rate for different levels of the transmitter power, i.e., the molecule production rate.

Capacity of diffusion-based molecular communication with ligand receptors

A diffusion-based molecular communication system has two major components: the diffusion in the medium, and the ligand-reception. Information bits, encoded in the time variations of the concentration of molecules, are conveyed to the receiver front through the molecular diffusion in the medium. The receiver, in turn, measures the concentration of the molecules in its vicinity in order to retrieve the information. This is done via ligand-reception process. In this paper, we develop models to study the constraints imposed by the concentration sensing at the receiver side and derive the maximum rate by which a ligand-receiver can receive information. Therefore, the overall capacity of the diffusion channel with the ligand receptors can be obtained by combining the results presented in this paper with our previous work on the achievable information rate of molecular communication over the diffusion channel.

Design and Analysis of Wireless Communication Systems Using Diffusion-Based Molecular Communication Among Bacteria

The design of biologically-inspired wireless communication systems using bacteria as the basic element of the system is initially motivated by a phenomenon called Quorum Sensing. Due to high randomness in the individual behavior of a bacterium, reliable communication between two bacteria is almost impossible. Therefore, we have recently proposed that a population of bacteria in a cluster is considered as a bio node in the network capable of molecular transmission and reception. This proposition enables us to form a reliable bio node out of many unreliable bacteria. In this paper, we study the communication between two nodes in such a network where information is encoded in the concentration of molecules by the transmitter. The molecules produced by the bacteria in the transmitter node propagate through the diffusion channel. Then, the concentration of molecules is sensed by the bacteria population in the receiver node which would decode the information and output light or fluorescent as a result. The uncertainty in the communication is caused by all three components of communication, i.e., transmission, propagation and reception. We study the theoretical limits of the information transfer rate in the presence of such uncertainties. Finally, we consider M-ary signaling schemes and study their achievable rates and corresponding error probabilities.

Relaying in diffusion-based molecular communication

This paper is eligible for the student paper award. Molecular communication between biological entities is a new paradigm in communications. Recently, we studied molecular communication between two nodes formed from synthetic bacteria. Due to high randomness in behavior of bacteria, we used a population of them in each node. The reliability of such communication systems depends on both the maximum concentration of molecules that a transmitter node is able to produce at the receiver node as well as the number of bacteria in each nodes. This maximum concentration of molecules falls with distance which makes the communication to the far nodes nearly impossible. In order to alleviate this problem, in this paper, we propose to use a molecular relaying node. The relay node can resend the message either by the different or the same type of molecules as the original signal from the transmitter. We study two scenarios of relaying. In the first scenario, the relay node simply senses the received concentration and forwards it to the receiver. We show that this sense and forward scenario, depending on the type of molecules used for relaying, results in either increasing the range of concentration of molecules at the receiver or increasing the effective number of bacteria in the receiver node. For both cases of sense and forward relaying, we obtain the resulting improvement in channel capacity. We conclude that multi-type molecular relaying outperforms the single-type relaying. In the second scenario, we study the decode and forward relaying for the M-ary signaling scheme. We show that this relaying strategy increases the reliability of M-ary communication significantly.

Data gathering in networks of bacteria colonies: Collective sensing and relaying using molecular communication

The prospect of new biological and industrial applications that require communication in micro-scale, encourages research on the design of bio-compatible communication networks using networking primitives already available in nature. One of the most promising candidates for constructing such networks is to adapt and engineer specific types of bacteria that are capable of sensing, actuation, and above all, communication with each other. In this paper, we describe a new architecture for networks of bacteria to form a data collecting network, as in traditional sensor networks. The key to this architecture is the fact that the node in the network itself is a bacterial colony; as an individual bacterium (biological agent) is a tiny unreliable element with limited capabilities. We describe such a network under two different scenarios. We study the data gathering (sensing and multihop communication) scenario as in sensor networks followed by the consensus problem in a multinode network. We will explain as to how the bacteria in the colony collectively orchestrate their actions as a node to perform sensing and relaying tasks that would not be possible (at least reliably) by an individual bacterium. Each single bacterium in the colony forms a belief by sensing external parameter (e.g., a molecular signal from another node) from the medium and shares its belief with other bacteria in the colony. Then, after some interactions, all the bacteria in the colony form a common belief and act as a single node. We will model the reception process of each individual bacteria and will study its impact on the overall functionality of a node. We will present results on the reliability of the multihop communication for data gathering scenario as well as the speed of convergence in the consensus scenario.

Consensus problem under diffusion-based molecular communication

We investigate the consensus problem in a network where nodes communicate via diffusion-based molecular communication (DbMC). In DbMC, messages are conveyed via the variation in the concentration of molecules in the medium. Every node acquires sensory information about the environment. Communication enables the nodes to reach the best estimate for that measurement, e.g., the average of the initial estimates by all nodes. We consider an iterative method for communication among nodes that enables information spreading and averaging in the network. We show that the consensus can be attained after a finite number of iterations and variance of estimates of nodes can be made arbitrarily small via communication.

Decode and forward relaying in diffusion-based molecular communication between two populations of biological agents

Molecular communication allows bio nodes to communicate and cooperate in an aqueous environment. We recently proposed an m-ary modulation scheme in which the information is encoded into the concentration of molecules emitted by the bio nodes. The performance of such scheme, among other factors, is limited by the maximum concentration of molecules that can be induced by the transmitter at the receiver. This paper investigates relaying to improve the reliability of such molecular communication. We consider the case that nodes consist of a population of biological agents and study the scenario in which the relay node decodes the incoming information symbol and forwards it to the destination using the same or a different type of molecules as the transmitter. We show how the use of relaying in molecular communication can increase the effective range of molecular concentration induced at the receiver and also can help with achieving diversity at the receiver. We use a generalized form of Maximum Ratio Combining (MRC) and show as to how the probability of error is improved using the optimal relaying. We also compare this scenario with the case that the relay node uses the same type of the molecule.

Collective sensing-capacity of bacteria populations

The design of biological networks using bacteria as the basic elements of the network is initially motivated by a phenomenon called quorum sensing. Through quorum sensing, each bacterium performs sensing the medium and communicating it to others via molecular communication. As a result, bacteria can orchestrate and act collectively and perform tasks impossible otherwise. In this paper, we consider a population of bacteria as a single node in a network. In our version of biological communication networks, such a node would communicate with one another via molecular signals. As a first step toward such networks, this paper focuses on the study of the transfer of information to the population (i.e., the node) by stimulating it with a concentration of special type of a molecules signal. These molecules trigger a chain of processes inside each bacteria that results in a final output in the form of light or fluorescence. Each stage in the process adds noise to the signal carried to the next stage. Our objective is to measure (compute) the maximum amount of information that we can transfer to the node. This can be viewed as the collective sensing capacity of the node. The molecular concentration, which carries the information, is the input to the node, which should be estimated by observing the produced light as the output of the node (i.e., the entire population of bacteria forming the node. The molecules are trapped in the bacteria receptors forming complexes inside the bacteria which affect the genes responsible for producing the light. We focus on the noise caused by the random process of trapping molecules at the receptors as well as the variation of outputs of different bacteria in the node. The optimal input distribution to maximize the mutual information between the output of the node, e.g., light, and the applied molecule concentration is derived. Further, the capacity variation with the number of bacteria in the node and the number of receptors per bacteria is obtained. Finally, we investigated the collective sensing capability of the node when a specific form of molecular signaling concentration (which resembles M-ary modulation) is used. The achievable sensing capacity and the corresponding error probabilities were obtained for such practical signaling techniques.

BPRS: Belief Propagation based iterative recommender system

In this paper we introduce the first application of the Belief Propagation (BP) algorithm in the design of recommender systems. We formulate the recommendation problem as an inference problem and aim to compute the marginal probability distributions of the variables which represent the ratings to be predicted. However, computing these marginal probability functions is computationally prohibitive for large-scale systems. Therefore, we utilize the BP algorithm to efficiently compute these functions. Recommendations for each active user are then iteratively computed by probabilistic message passing. As opposed to the previous recommender algorithms, BPRS does not require solving the recommendation problem for all the users if it wishes to update the recommendations for only a single active. Further, BPRS computes the recommendations for each user with linear complexity and without requiring a training period. Via computer simulations (using the 100K MovieLens dataset), we verify that BPRS iteratively reduces the error in the predicted ratings of the users until it converges. Finally, we confirm that BPRS is comparable to the state of art methods such as Correlation-based neighborhood model (CorNgbr) and Singular Value Decomposition (SVD) in terms of rating and precision accuracy. Therefore, we believe that the BP-based recommendation algorithm is a new promising approach which offers a significant advantage on scalability while providing competitive accuracy for the recommender systems.

Molecular communication between two populations of bacteria

Molecular communication is an expanding body of research. Recent advances in biology have encouraged using genetically engineered bacteria as the main component in the molecular communication. This has stimulated a new line of research that attempts to study molecular communication among bacteria from an information-theoretic point of view. Due to high randomness in the individual behavior of the bacterium, reliable communication between two bacteria is almost impossible. Therefore, we recently proposed that a population of bacteria in a cluster is considered as a node capable of molecular transmission and reception. This proposition enables us to form a reliable node out of many unreliable bacteria. The bacteria inside a node sense the environment and respond accordingly. In this paper, we study the communication between two nodes, one acting as the transmitter and the other as the receiver. We consider the case in which the information is encoded in the concentration of molecules by the transmitter. The molecules produced by the bacteria in the transmitter node propagate in the environment via the diffusion process. Then, their concentration sensed by the bacteria in the receiver node would decode the information. The randomness in the communication is caused by both the error in the molecular production at the transmitter and the reception of molecules at the receiver. We study the theoretical limits of the information transfer rate in such a setup versus the number of bacteria per node. Finally, we consider M-ary modulation schemes and study the achievable rates and their error probabilities.