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Related Concept Videos

Downsampling01:20

Downsampling

872
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.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
872
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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Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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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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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...
945
Bandpass Sampling01:17

Bandpass Sampling

681
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
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Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

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The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
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Related Experiment Video

Updated: May 1, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

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Terabit bandwidth-adaptive transmission using low-complexity format-transparent digital signal processing.

Qunbi Zhuge, Mohamed Morsy-Osman, Mathieu Chagnon

    Optics Express
    |March 26, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new digital signal processing (DSP) scheme using Quadrature Phase Shift Keying (QPSK) symbols for flexible and energy-efficient transceivers. This method enhances performance across various modulation formats and transmission distances.

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    Area of Science:

    • Optical Communications
    • Digital Signal Processing
    • Telecommunications Engineering

    Background:

    • Next-generation transceivers require flexible and energy-efficient digital signal processing (DSP).
    • Existing DSP schemes often lack format transparency and can be complex.
    • Optimizing bandwidth allocation is crucial for high-capacity optical networks.

    Purpose of the Study:

    • To propose a low-complexity, format-transparent DSP scheme for flexible transceivers.
    • To enable efficient initialization and tracking for various modulation formats.
    • To investigate Tb/s bandwidth-adaptive superchannel transmissions.

    Main Methods:

    • Utilizing Quadrature Phase Shift Keying (QPSK) symbols for receiver initialization and tracking.
    • Numerical and experimental evaluation in a dual-polarization (DP) 11 Gbaud 64QAM system.
    • Digital domain spectrum bandwidth allocation for adaptive superchannels.

    Main Results:

    • Demonstrated successful operation with flexible modulation formats (QPSK, 8QAM, 16QAM).
    • Achieved improved performance for higher-order QAM through digital bandwidth allocation.
    • Validated transmission over various distances (240 km to 6240 km) with colorless detection.

    Conclusions:

    • The proposed DSP scheme offers a low-complexity, format-transparent solution for flexible and energy-efficient transceivers.
    • Digital bandwidth allocation enhances the performance of higher-order QAM in superchannel transmissions.
    • The scheme supports long-haul, bandwidth-adaptive transmissions with reduced hardware complexity.