Compressive Wideband Spectrum Sensing and Carrier Frequency Estimation with Unknown Mimo Channels
Hongwei Wang, Jilin Wang, Jun Fang, Hongbin Li
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 predetermined time delay. The signal at each channel is then sampled by a synchronized low-rate analog-to-digital converter (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.
BibTeX
@inproceedings{icassp2021_compressivewideb,
title = {Compressive Wideband Spectrum Sensing and Carrier Frequency Estimation with Unknown Mimo Channels},
author = {Hongwei Wang and Jilin Wang and Jun Fang and Hongbin Li},
booktitle = {ICASSP 2021},
year = {2021}
}