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Related Concept Videos

Upsampling01:22

Upsampling

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Aliasing01:18

Aliasing

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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
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Downsampling01:20

Downsampling

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When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
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Scaling01:26

Scaling

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In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
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¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Reconstruction of Signal using Interpolation01:10

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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ASE noise mitigation with digital frequency offset loading for discrete spectrum nonlinear frequency division

Yanfeng Bi, Hengying Xu, Yining Zhang

    Optics Letters
    |November 1, 2023
    PubMed
    Summary

    We introduce digital frequency offset loading (DFO-loading) to reduce amplified spontaneous emission (ASE) noise in discrete spectrum nonlinear frequency division multiplexing (DS-NFDM) systems. This method significantly improves system performance and lowers complexity compared to existing schemes.

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    Area of Science:

    • Optical Communications
    • Signal Processing

    Background:

    • Amplified spontaneous emission (ASE) noise is a major limiting factor in discrete spectrum nonlinear frequency division multiplexing (DS-NFDM) systems.
    • Traditional methods for mitigating ASE noise and recovering signals can be complex and computationally intensive.

    Purpose of the Study:

    • To propose and evaluate a novel ASE noise mitigation scheme for DS-NFDM systems.
    • To reduce system complexity while maintaining or improving signal quality.

    Main Methods:

    • Digital frequency offset loading (DFO-loading) at the transmitter to encode 4-bit information onto 16 distinct frequency offsets.
    • Sliding window-assisted eigenvalue position (SWA-EP) decoding to replace conventional channel equalization and carrier phase recovery.

    Main Results:

    • Achieved Q-factor gains of 2.1 dB (at 15 dB OSNR) and 1.8 dB (after 800 km fiber transmission) compared to the b-coefficient 16-QAM scheme.
    • Demonstrated a significant reduction in computational complexity, requiring only 0.6% of that of the b-coefficient scheme.

    Conclusions:

    • The proposed DFO-loading scheme effectively mitigates ASE noise in DS-NFDM systems.
    • This approach offers a low-complexity and high-performance solution for optical communication systems.