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      Receivers for Diffusion-Based Molecular Communication: Exploiting Memory and Sampling Rate

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          A physical end-to-end model for molecular communication in nanonetworks

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            Molecular communication and networking: opportunities and challenges.

            The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.
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              Diffusion-Based Noise Analysis for Molecular Communication in Nanonetworks

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                Author and article information

                Journal
                IEEE Journal on Selected Areas in Communications
                IEEE J. Select. Areas Commun.
                Institute of Electrical and Electronics Engineers (IEEE)
                0733-8716
                December 2014
                December 2014
                : 32
                : 12
                : 2368-2380
                Article
                10.1109/JSAC.2014.2367732
                db2aaa1e-1666-4e3c-843a-7e1caa840df9
                © 2014
                History

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