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Related Concept Videos

Communication01:03

Communication

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Communication between two animals occurs when one animal transmits an information signal that causes a change in the animal that receives the information. Organisms communicate with one another in a host of different ways. Signals can be auditory, chemical, visual, tactile, or a combination of these. Communication is a critical behavioral adaptation that promotes survival, growth, and reproduction.
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Communication01:28

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Sharing information, concepts, and emotions to foster mutual understanding is communication. The sender, recipient, and transaction must be considered in this manner. The sender is the person who shares the message, the recipient is the person who receives and understands the message, and the transaction is the method used to deliver the message and the variables that affect the communication's context and surroundings. The nurse-client connection is built on therapeutic communication.
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Glutamine Flux Imaging Using Genetically Encoded Sensors
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High performance demodulation method with less complexity for image-sensor communication.

Yuki Ohira, Tomohiro Yendo, Shintaro Arai

    Optics Express
    |September 13, 2019
    PubMed
    Summary

    This study introduces a new, less complex signal demodulation method for visible light communication (VLC) systems using image sensors. It improves performance by selectively applying advanced decoding only to challenging signals, approaching maximum-likelihood decoding (MLD) efficiency.

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    Area of Science:

    • Optical Engineering
    • Wireless Communication
    • Signal Processing

    Background:

    • Visible Light Communication (VLC) systems utilize light-emitting diodes (LEDs) as transmitters and image sensors as receivers.
    • Signal demodulation is critical but challenging due to image degradation from distance and noise.
    • Existing methods like Maximum-Likelihood Decoding (MLD) offer high performance but are computationally complex.

    Purpose of the Study:

    • To propose a novel, computationally efficient signal demodulation method for image-sensor-based VLC systems.
    • To achieve performance comparable to MLD while significantly reducing complexity.
    • To address the challenges of signal demodulation in noisy and distance-affected VLC environments.

    Main Methods:

    • A hybrid demodulation approach combining Minimum Mean Square Error (MMSE) and MLD.
    • Categorizing LEDs into reliable and unreliable groups based on MMSE performance.
    • Directly demodulating reliable LEDs and applying MLD exclusively to unreliable LEDs.

    Main Results:

    • The proposed method demonstrates performance approaching that of MLD.
    • Achieved significant reduction in computational complexity compared to standard MLD.
    • Validated through numerical simulations and laboratory experiments.

    Conclusions:

    • The novel hybrid demodulation method offers an effective solution for VLC systems.
    • It balances high performance with practical computational efficiency.
    • This approach enhances the feasibility of image-sensor-based VLC systems.