Corpus ID: 204907096

Spectral Power Parameter Estimation of Random Sources with Binary Sampled Signals

@article{Stein2019SpectralPP,
  title={Spectral Power Parameter Estimation of Random Sources with Binary Sampled Signals},
  author={Manuel S. Stein},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.12309}
}
  • Manuel S. Stein
  • Published in ArXiv 2019
  • Engineering, Computer Science, Mathematics
  • This paper investigates the problem of estimating the spectral power parameters of random analog sources using numerical measurements acquired with minimum digitization complexity. Therefore, spectral analysis has to be performed with binary samples of the analog sensor output. Under the assumption that the structure of the spectral power density of the analog sources is given, we investigate the achievable accuracy for power level estimation with likelihood-oriented processing. The discussion… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 23 REFERENCES

    Channel Estimation in One-Bit Massive MIMO Systems: Angular Versus Unstructured Models

    VIEW 1 EXCERPT

    Glancing Through Massive Binary Radio Lenses: Hardware-Aware Interferometry With 1-Bit Sensors

    • Manuel S. Stein
    • Physics, Computer Science, Engineering, Mathematics
    • ArXiv
    • 2019
    VIEW 1 EXCERPT

    Latency Analysis for Sequential Detection in Low-Complexity Binary Radio Systems

    VIEW 1 EXCERPT

    Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs

    VIEW 1 EXCERPT

    Uplink Performance of Wideband Massive MIMO With One-Bit ADCs

    VIEW 1 EXCERPT

    Capacity Analysis of One-Bit Quantized MIMO Systems With Transmitter Channel State Information

    VIEW 1 EXCERPT