Comparing Iterative and Least-Squares Based Phase Noise Tracking in Receivers with 1-bit Quantization and Oversampling

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

High data rates require vast bandwidths, that can be found in the sub-THz band, and high sampling frequencies, which are predicted to lead to a problematically high analog-to-digital converter (ADC) power consumption. It was proposed to use 1-bit ADCs to mitigate this problem. Moreover, oscillator phase noise is predicted to be especially high at sub-THz carrier frequencies. For synchronization the phase must be tracked based on 1-bit quantized observations. We study iterative data-aided phase estimation, i.e., the expectation-maximization and the Fisher-scoring algorithm, compared to least-squares (LS) phase estimation. For phase interpolation at the data symbols, we consider the Kalman filter and the Rauch-Tung-Striebel algorithm. Compared to LS estimation, iterative phase noise tracking leads to a significantly lower estimation error variance at high signal-to-noise ratios. However, its benefit for the spectral efficiency using zero-crossing modulation (ZXM) is limited to marginal gains for high faster-than-Nyquist signaling factors, i.e., higher order ZXM modulation.

Details

Original languageEnglish
Title of host publicationProceedings of the 22nd IEEE Statistical Signal Processing Workshop, SSP 2023
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages31-35
Number of pages5
ISBN (electronic)978-1-6654-5245-8
Publication statusPublished - 2023
Peer-reviewedYes

Publication series

SeriesIEEE/SP Workshop on Statistical Signal Processing (SSP)
Volume2023-July

Workshop

Title22nd IEEE Statistical Signal Processing Workshop
Abbreviated titleSSP 2023
Conference number22
Duration2 - 5 July 2023
Website
LocationThe Hanoi Club Hotel & VinUniversity
CityHanoi
CountryViet Nam

Keywords

Keywords

  • 1-bit quantization, estimation, faster-than-Nyquist signaling, iterative algorithms, phase noise