Diffusive Molecular Communications Research Articles

Adaptive multi-layer reward based Q-learning for source tracing in diffusive molecular communications environment with obstacles

Benefiting by the fast development of nanotechnology, molecular communication (MC) has received great attention in recent years. In many potential applications of MC, such as drug delivery and pollution prevention, it is essential to locate or trace the target. In this paper, we consider a 3D diffusive MC environment consisting of several obstacles, a molecule-releasing source (RS) and a mobile molecule sensor (MS) which aims to find the RS within a time constraint. The problem is reformulated using Markov Decision Process (MDP) and an adaptive multi-layer reward based Q-Learning (AMR-Q Learning) approach is proposed. By exploiting information from the number of received molecules and adaptively setting multi-layer rewards, MS with AMR-Q Learning can find the RS efficiently, unlike the gradient based method which is usually trapped in locally optimal points. Numerical results demonstrate that the proposed AMR-Q Learning approach outperforms existing path-planning schemes with significantly reduced training overhead.

Interference Mitigation-Enabled Signal Detection in Diffusive Molecular Communications Systems With Molecular-Type Spreading

To accomplish complex tasks, several nano-machines may need to communicate via multiple-access channel with one access point, where information fusion is carried out. However, multiple-access Diffusive Molecular Communications (DMC) systems suffer from severe Multiple-Access Interference (MAI) and Inter-Symbol Interference (ISI), which should be effectively mitigated at receiver in order to achieve acceptable performance. Built on two fundamental single-user detection schemes, namely Threshold assisted Majority Vote Detection (TMVD) and Equal Gain Combination Detection (EGCD), we first propose three low-complexity interference cancellation schemes, which are the TMVD-assisted Iterative Interference Cancellation (TMVD-IIC), TMVD-based Minimum-Distance Decoding assisted Interference Cancellation (TMVD-MDDIC) and the EGCD-assisted N-order Iterative Interference Cancellation (EGCD-NIIC), for operation in the Molecular Type Spread assisted Molecular Shift Keying (MTS-MoSK) DMC systems. Then, following the principle of maximum likelihood detection, we propose a Simplified Approximate Maximum Likelihood (SAML) detection scheme. The error performance of the MTS-MoSK DMC systems employing respectively the considered detection schemes is comprehensively investigated and compared. Furthermore, the complexities of the detection schemes are analyzed and discussed in terms of the complexity-performance trade-off. Our studies and results show that, compared with the single-user TMVD and EGCD schemes, the proposed interference cancellation schemes are capable of mitigating efficiently the effect of MAI and enabling significant performance improvement at the slightly increased complexity.

Channel Characteristics for Diffusive Molecular Communications in a Spherical Shell

Diffusive molecular communication (DMC) is a bio-mimicking communications paradigm that exploits the Brownian motion of dedicated information carrying molecules for signal transmission. The characteristics of the communication channel in a DMC system heavily depends on the transmitter and receiver mechanisms, on the medium of propagation and its boundaries, and on the way they interact with the molecules. In this work, we investigate the DMC channel in a spherical shell, with inner and outer surfaces which may be partially or perfectly absorptive, or reflective, where either of the boundary surfaces can be considered as the DMC receiver. These geometry and boundary conditions can be used to model a variety of practically relevant scenarios, which are investigated in detail. We derive the general parametric solution of the partial differential equation for this case and provide, for the first time in the literature, expressions for the resulting channel response. We verify the results of our analysis numerically via particle based simulations.

Signal Propagation in Diffusive Molecular Communications Over a Spherical Surface

Diffusive molecular communications (DMC) relies on the Brownian motion of dedicated molecules for transmitting information. The signal propagation characteristics in a DMC channel is determined by the geometries of the environment, receiver and the transmitter and their physical and chemical properties, which impose the boundary- and initial conditions on the partial differential equation (PDE) describing the diffusion process. In this work, we investigate the directional signal propagation characteristics for a point source over (or, as a special case, on) a spherical surface, that may be reflective, perfectly absorptive or partially absorptive. We derive the general solution of the PDE for this case, and validate it via particle based simulations. Our results can be employed to determine the signal propagation characteristics in a wide range of practically relevant scenarios, for which we investigate the effect of the system parameters on the directivity of the signal propagation.

Adaptive Multi-Layer Reward Based Q-Learning for Source Tracing in Diffusive Molecular Communications Environment with Obstacles

Adaptive Multi-Layer Reward Based Q-Learning for Source Tracing in Diffusive Molecular Communications Environment with Obstacles

Towards high data-rate diffusive molecular communications: A review on performance enhancement strategies

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Studies on fundamental information theoretic limits of DiMC channel are reviewed. Classical and novel transceiver designs are discussed with an emphasis on methods for ISI mitigation and performance-complexity tradeoffs. Key parameter estimation strategies such as synchronization and channel estimation are considered in conjunction with asynchronous and timing error robust receiver methods. Finally, source and channel coding in the context of DiMC is presented.

Sequential Decision Fusion for Abnormality Detection via Diffusive Molecular Communications

This letter considers the task of abnormality detection in a fluid medium, employing a molecular communications (MC) based network of nanoscale sensors. This task entails sensing, detection and reporting of abnormal changes in the environment that may characterize a disorder or an abnormal event. Such distributed detection (DD) problems are of paramount interest, especially in applications such as health monitoring, disease diagnosis, targeted drug delivery, environmental sensing and monitoring, contaminant detection and removal, and environmental remediation. This letter proposes, for the first time in the literature, to employ a sequential probability ratio test based approach to the decision fusion in diffusive MC based DD. The proposed approach leads to considerable gains in the average number of samples required for the decision compared to its fixed-sample size counterparts, resulting in a significant improvement in the average decision delay. In the investigated DD scenarios, we observe savings of up to 50% in the number of samples required for decision fusion.

Simulation Study and Analysis of Diffusive Molecular Communications With an Apertured Plane.

Molecular communication via diffusion (MCvD) is a method of achieving nano- and micro-scale connectivity by utilizing the free diffusion mechanism of information molecules. The randomness in diffusive propagation is the main cause of inter-symbol interfe-rence (ISI) and the limiting factor of high data rate MCvD applications. In this paper, an apertured plane is considered between the transmitter and the receiver of an MCvD link. Either after being artificially placed or occurring naturally, surfaces or volumes that resemble an apertured plane only allow a fraction of the molecules to pass. Contrary to intuition, it is observed that such topology may improve communication performance, given the molecules that can pass through the aperture are the ones that take more directed paths towards the receiver. Furthermore, through both computer simulations and a theoretical signal evaluation metric named signal-to-interference and noise amplitude ratio (SINAR), it is found that the size of the aperture imposes a trade-off between the received signal power and the ISI combating capability of an MCvD system, hinting to an optimal aperture size that minimizes the bit error rate (BER). It is observed that the trend of BER is accurately mirrored by SINAR, suggesting the proposed metric's applicability to optimization tasks in MCvD systems, including finding the optimal aperture size of an apertured plane. In addition, computer simulations and SINAR show that said optimal aperture size is affected by the location of the aperture and the bit rate. Lastly, the paper analyzes the effects of radial and angular offsets in the placement of the apertured plane, and finds that a reduction in BER is still in effect up to certain offset values. Overall, our results imply that apertured plane-like surfaces may actually help communication efficiency, even though they reduce the received signal power.

Diffusive MIMO Molecular Communications: Channel Estimation, Equalization, and Detection

In diffusion-based communication, for molecular systems, the achievable data rate depends on the stochastic nature of diffusion, which exhibits a severe inter-symbol-interference (ISI). Multiple-input multiple-output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). The numerical validations in terms of MSE are compared with Cramer–Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE, and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. D-MIMO time interleaving is exploited as an additional countermeasure to mitigate the ILI with remarkable performance improvements. The configuration of nano-transceivers is not static but affected by a Brownian motion. A block-type communication is proposed for D-MIMO channel estimation and equalization, and the corresponding time-varying D-MIMO MC system is numerically evaluated.

Directional Receivers for Diffusion-Based Molecular Communications

The particle motion in diffusion-based molecular communication systems is typically modeled by using Brownian processes. In particular, this model is used to characterize the propagation of signal molecules after their release from the transmitter. This motion cannot include directionality in the propagating signal and translates into omnidirectional broadcast communications. In order to make such molecular communications system suitable for supporting communications protocols at the molecular scales, we propose to improve the receiver capabilities by introducing a form of directionality while receiving biological signals. Inspired by the directionality introduced in electromagnetic communications by means of directional antennas, we designed a nanomachine receiver having directionality properties. Our aim is to increase the average concentration of signal molecules, also referred to as carriers, in the area around the receiver surface. In this way, it is possible to increase the signal strength at the receiver. For this purpose, we propose to use a purely reflecting shell to be placed at a configurable distance from the receiver surface. The shape of the shell can be modeled as either a spherical cap or a cylinder with an empty basis. The presence of this surface causes a number of signal molecules to remain trapped in a region close to the receiver surface for a sufficiently long time. In this way, the probability of assimilating additional carriers by the compliant receptors present on the receiver surface increases. By means of an extensive simulation campaign, we identified the most suitable configuration able to provide a significant advantage with respect to those not adopting the proposed solution. The resulting approach can be regarded as an enabler of protocols for diffusive molecular communications taking advantage of directionality properties at the receiver site. It can result in an increased communication range or in improved capabilities of discriminating signals of coexisting molecular communication systems.

Diffusive Molecular Communications With Reactive Molecules: Channel Modeling and Signal Design

This paper focuses on molecular communication (MC) systems using two types of signaling molecules which may participate in a reversible bimolecular reaction in the channel. The motivation for studying these MC systems is that they can realize the concept of constructive and destructive signal superposition, which leads to favorable properties, such as inter-symbol interference (ISI) reduction and avoiding environmental contamination due to continuous release of signaling molecules into the channel. This paper first presents a general formulation for binary modulation schemes that employ two types of signaling molecules and proposes several modulation schemes as special cases. Moreover, two types of receivers are considered: 1) a receiver that is able to observe both types of signaling molecules (2TM) and 2) a simpler receiver that can observe only one type of signaling molecules (1TM). For both of these receivers, the maximum likelihood (ML) detector for general binary modulation is derived under the assumption that the detector has perfect knowledge of the ISI-causing sequence. The performance of this genie-aided ML detector yields an upper bound on the performance of any practical detector. In addition, two suboptimal detectors of different complexity are proposed, namely, an ML-based detector that employs an estimate of the ISI-causing sequence and a detector that neglects the effect of ISI. The proposed detectors, except for the detector that neglects ISI for the 2TM receiver, require knowledge of the channel response (CR) of the considered MC system. Moreover, the CR is needed for performance evaluation of all proposed detectors. However, deriving the CR of MC systems with reactive signaling molecules is challenging since the underlying partial differential equations that describe the reaction–diffusion mechanism are coupled and non-linear. Therefore, we develop an algorithm for efficient computation of the CR and validate its accuracy via particle-based simulation. Simulation results obtained using this CR computation algorithm confirm the effectiveness of the proposed modulation and detection schemes. Moreover, these results show that MC systems with reactive signaling have superior performance relative to those with non-reactive signaling due to the reduction of ISI enabled by the chemical reactions.

Cooperative Abnormality Detection via Diffusive Molecular Communications.

In this paper, we consider abnormality detection via diffusive molecular communications (MCs) for a network consisting of several sensors and a fusion center (FC). If a sensor detects an abnormality, it injects a number of molecules into the medium which is proportional to its sensing output. Two transmission schemes for releasing molecules into the medium are considered. In the first scheme, each sensor releases a different type of molecule (DTM), whereas in the second scheme, all sensors release the same type of molecule (STM). The molecules released by the sensors propagate through the MC channel and some may reach the FC where the final decision regarding whether or not an abnormality has occurred is made. We derive the optimal decision rules for both DTM and STM. However, the optimal detectors entail high computational complexity as log-likelihood ratios (LLRs) have to be computed. To overcome this issue, we show that the optimal decision rule for STM can be transformed into an equivalent low-complexity decision rule. Since a similar transformation is not possible for DTM, we propose simple low-complexity sub-optimal detectors based on different approximations of the LLR. The proposed low-complexity detectors are more suitable for practical MC systems than the original complex optimal decision rule, particularly when the FC is a nano-machine with limited computational capabilities. Furthermore, we analyze the performance of the proposed detectors in terms of their false alarm and missed detection probabilities. Simulation results verify our analytical derivations and reveal interesting insights regarding the tradeoff between complexity and performance of the proposed detectors and the considered DTM and STM schemes.