Compressive wideband spectrum sensing and carrier frequency Estimation with unknown mimo channels

Hongwei Wang, Jilin Wang, Jun Fang, Hongbin Li

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

We consider the problem of joint wideband spectrum sensing and carrier frequency estimation in a sub-Nyquist sampling framework. Specifically, a multi-antenna receiver is used to estimate the carrier frequencies and power spectra of multiple narrowband transmissions that spread over a wide frequency band. Unlike existing works that assume the source signals impinge on the receiver via a line-of-sight (LOS) path, we consider a more practical multiple-input multiple-output (MIMO) channel characterized by multipath propagation. A new sub-Nyquist sampling architecture is proposed, where each antenna output passes through two channels, namely, a direct path and a delayed path with a pre- determined time delay. The signal at each channel is then sampled by a synchronized low-rate analog-to-digital con- verter (ADC).We utilize the collected data samples to build a set of cross-correlation matrices with different time lags and develop a CANDECOMP/PARAFAC (CP) decomposition- based method to recover the carrier frequencies and power spectra of the source signals. Simulation results are presented to illustrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)8448-8452
Number of pages5
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2021-June
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada
Duration: 6 Jun 202111 Jun 2021

Keywords

  • Carrier fre- quency estimation
  • Cp decomposition
  • Sub-nyquist sampling
  • Wideband spectrum sensing

Fingerprint

Dive into the research topics of 'Compressive wideband spectrum sensing and carrier frequency Estimation with unknown mimo channels'. Together they form a unique fingerprint.

Cite this