54 research outputs found

    Adaptive detection and ISI mitigation for mobile molecular communication

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    Current studies on modulation and detection schemes in molecular communication mainly focus on the scenarios with static transmitters and receivers. However, mobile molecular communication is needed in many envisioned applications, such as target tracking and drug delivery. Until now, investigations about mobile molecular communication have been limited. In this paper, a static transmitter and a mobile bacterium-based receiver performing random walk are considered. In this mobile scenario, the channel impulse response changes due to the dynamic change of the distance between the transmitter and the receiver. Detection schemes based on fixed distance fail in signal detection in such a scenario. Furthermore, the intersymbol interference (ISI) effect becomes more complex due to the dynamic character of the signal which makes the estimation and mitigation of the ISI even more difficult. In this paper, an adaptive ISI mitigation method and two adaptive detection schemes are proposed for this mobile scenario. In the proposed scheme, adaptive ISI mitigation, estimation of dynamic distance and the corresponding impulse response reconstruction are performed in each symbol interval. Based on the dynamic channel impulse response in each interval, two adaptive detection schemes, concentration-based adaptive threshold detection (CATD) and peak-time-based adaptive detection (PAD), are proposed for signal detection. Simulations demonstrate that, the ISI effect is significantly reduced and the adaptive detection schemes are reliable and robust for mobile molecular communication

    Diffusive MIMO Molecular Communications: Channel Estimation, Equalization and Detection

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    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.Comment: Accepted paper at IEEE transaction on Communicatio

    Bacterial relay for energy efficient molecular communications

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    In multi-cellular organisms, molecular signaling spans multiple distance scales and is essential to tissue structure and functionality. Molecular communications is increasingly researched and developed as a key subsystem in the Internet-of-Nano-Things paradigm. While short range microscopic diffusion communications is well understood, longer range channels can be inefficient and unreliable. Static and mobile relays have been proposed in both conventional wireless systems and molecular communication contexts. In this paper, our main contribution is to analyze the information delivery energy efficiency of bacteria mobile relays. We discover that these mobile relays offer superior energy efficiency compared with pure diffusion information transfer over long diffusion distances. This paper has widespread implications ranging from understanding biological processes to designing new efficient synthetic biology communication systems
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