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Updated: Dec 3, 2025

Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking FLLIT
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LiFi grid: a machine learning approach to user-centric design.

Mohamadreza Pashazanoosi, S Alireza Nezamalhosseini, Jawad A Salehi

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    |October 26, 2020
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    Summary
    This summary is machine-generated.

    A new machine learning algorithm, LiFi Grid, optimizes wireless networks by clustering access points for better user signal quality. This user-centric approach enhances performance over traditional designs.

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    Area of Science:

    • Computer Science
    • Electrical Engineering
    • Telecommunications

    Background:

    • Designing efficient wireless networks requires optimal placement of access points (APs).
    • Traditional cell-centric designs often struggle with dynamic user distribution and signal quality maximization.
    • Optical Wireless Networks (OWNs) offer high bandwidth but need advanced resource allocation strategies.

    Purpose of the Study:

    • To introduce a novel machine learning clustering algorithm, light-fidelity (LiFi) Grid, for user-centric (UC) network design in LiFi systems.
    • To maximize the minimum signal-to-interference-plus-noise ratio (SINR) for improved user experience.
    • To enable dynamic resource allocation in Optical Wireless Networks (OWNs).

    Main Methods:

    • The LiFi Grid algorithm uses a two-phase approach.
    • Phase 1: Mean-shift (MS) clustering identifies user density clusters without predefining the number of clusters.
    • Phase 2: A novel clustering method groups APs based on user positions for UC design.

    Main Results:

    • LiFi Grid demonstrates superior performance in maximizing the minimum SINR compared to fixed-shape, cell-centric designs.
    • The algorithm effectively handles dynamic resource allocation in OWNs.
    • LiFi Grid is fully compatible with the IEEE 802.15.7 standard.

    Conclusions:

    • The proposed LiFi Grid algorithm offers an effective user-centric approach to designing amorphous LiFi cells.
    • This method enhances network performance by optimizing AP grouping and resource allocation.
    • LiFi Grid provides a scalable and compatible solution for next-generation wireless networks.