On the Bayesian Cramér-Rao Bound for Phase Noise Estimation Based on 1-bit Quantized Samples

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

Contributors

Abstract

Digital receivers based on 1-bit quantization and temporal oversampling w. r. t. the transmit signal bandwidth are a promising solution for the design of energy-efficient communications systems in the millimeter-wave (mmWave) and sub-terahertz bands. However, off-the-shelf algorithms for channel estimation cannot be applied as 1-bit quantization is a highly non-linear operation. Phase noise (PN) in particular has a deteriorating effect on the communication performance at these high frequencies and, therefore, needs to be tracked and compensated at the receiver. In this context, we derive an analytical solution for a close approximation of the Bayesian Cramér-Rao bound for PN estimation in systems employing 1-bit quantization, which provides insights into the impact of various design parameters on the achievable estimation performance. Furthermore, we use the bound to benchmark the performance of two existing PN estimators, showing that one of these estimators performs close to the optimum.

Details

Original languageEnglish
Title of host publicationGLOBECOM 2022 - 2022 IEEE Global Communications Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6170-6175
Number of pages6
ISBN (electronic)978-1-6654-3540-6
ISBN (print)978-1-6654-3541-3
Publication statusPublished - 2022
Peer-reviewedYes

Publication series

SeriesIEEE Conference on Global Communications (GLOBECOM)
ISSN1930-529X

Conference

Title2022 IEEE Global Communications Conference
SubtitleAccelerating the Digital Transformation through Smart Communications
Abbreviated titleGLOBECOM 2022
Duration4 - 8 December 2022
Website
LocationWindsor Convention & Expo Center & Online
CityRio de Janeiro
CountryBrazil