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Register a new userSimulation Study and Analysis of Diffusive Molecular Communications with an Apertured Plane
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Added by
Mustafa Can Gursoy
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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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 interference (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 metrics 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.
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For nano-scale communications, there must be cooperation and simultaneous communication between nano devices. To this end, in this paper we investigate two-way (a.k.a. bi-directional) molecular communications between nano devices. If different types of molecules are used for the communication links, the two-way system eliminates the need to consider self-interference. However, in many systems, it is not feasible to use a different type of molecule for each communication link. Thus, we propose a two-way molecular communication system that uses a single type of molecule. We develop a channel model for this system and use it to analyze the proposed systems bit error rate, throughput, and self-interference. Moreover, we propose analog- and digital- self-interference cancellation techniques. The enhancement of link-level performance using these techniques is confirmed with both numerical and analytical results.
In this work, spatial diversity techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are proposed and analyzed. At the receiver-side, selection diversity, equal-gain combining, and maximum-ratio combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical $2times 2$ MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that it is possible to achieve a diversity gain in molecular communications. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.
In diffusion-based communication, as for molecular systems, the achievable data rate is low due to 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). 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. Since D-MIMO systems are severely affected by the ILI because of short transmitters inter-distance, D-MIMO time interleaving is exploited as countermeasure to mitigate the ILI with remarkable performance improvements. The feasibility of a block-type communication including training and data equalization is explored for D-MIMO, and system-level performances are numerically derived.
In molecular communication via diffusion (MCvD), the inter-symbol interference (ISI) is a well known severe problem that deteriorates both data rates and link reliability. ISI mainly occurs due to the slow and highly random propagation of the messenger molecules, which causes the emitted molecules from the previous symbols to interfere with molecules from the current symbol. An effective way to mitigate the ISI is using enzymes to degrade undesired molecules. Prior work on ISI mitigation by enzymes has assumed an infinite amount of enzymes randomly distributed around the molecular channel. Taking a different approach, this paper assumes an MCvD channel with a limited amount of enzymes. The main question this paper addresses is how to deploy these enzymes in an effective structure so that ISI mitigation is maximized. To find an effective MCvD channel environment, this study considers optimization of the shape of the transmitter node, the deployment location and structure, the size of the enzyme deployed area, and the half-lives of the enzymes. It also analyzes the dependence of the optimum size of the enzyme area on the distance and half-life.
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