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Probabilistic shaping-based delta sigma modulation.

Li Zhao, Sicong Xu, Mingxu Wang

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    This summary is machine-generated.

    This study introduces a novel probabilistic shaping delta-sigma modulation technique. This method enhances anti-noise capabilities for digital communication signals, improving data transmission reliability.

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    Area of Science:

    • Electrical Engineering
    • Signal Processing
    • Information Theory

    Background:

    • Delta-sigma modulation is a widely used technique in digital signal processing.
    • Probability shaping can improve the performance of communication systems.
    • Optimizing modulation techniques is crucial for reliable data transmission.

    Purpose of the Study:

    • To propose and evaluate a probabilistic shaping delta-sigma modulation technique.
    • To enhance the anti-noise capability of delta-sigma modulation signals.
    • To compare the bit error rate performance against existing methods.

    Main Methods:

    • Performing delta-sigma modulation on a probability shaping signal at the transmitter.
    • Analyzing signal performance under identical transmit power and net bit rate conditions.
    • Comparing bit error rate (BER) performance for PS-based 131072QAM signals against ordinary 65536QAM signals.

    Main Results:

    • The proposed probabilistic shaping delta-sigma modulation demonstrates superior anti-noise capability compared to standard delta-sigma modulation.
    • Under equivalent information entropy, the PS-based 131072QAM signal shows better BER performance than the ordinary 65536QAM signal.
    • The achieved BER performance is lower than that of soft decision-forward error correction (4 × 10-2).

    Conclusions:

    • Probabilistic shaping delta-sigma modulation offers enhanced anti-noise performance.
    • This technique improves BER performance in high-order modulation schemes.
    • The proposed method presents a viable approach for more robust digital communication systems.