TY - JOUR
T1 - Compressive Wideband Spectrum Sensing and Signal Recovery With Unknown Multipath Channels
AU - Wang, Hongwei
AU - Fang, Jun
AU - Duan, Huiping
AU - Li, Hongbin
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - We study the problem of joint wideband spectrum sensing and recovery of multi-band signals in a multi-antenna-based sub-Nyquist sampling framework. Specifically, the multi-band signal is composed of a number of uncorrelated narrowband signals spreading over a wide frequency band. Unlike existing works which assume the source signals impinge on the receiver via a line-of-sight (LOS) path, we consider a more practical unknown MIMO channel which results from 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 controlled amount of 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, power spectra as well as the source signals themselves. Recovery conditions of the proposed method are analyzed, and Cramér-Rao bound (CRB) results for our estimation problem are derived. Simulation results are presented to illustrate the effectiveness of the proposed method.
AB - We study the problem of joint wideband spectrum sensing and recovery of multi-band signals in a multi-antenna-based sub-Nyquist sampling framework. Specifically, the multi-band signal is composed of a number of uncorrelated narrowband signals spreading over a wide frequency band. Unlike existing works which assume the source signals impinge on the receiver via a line-of-sight (LOS) path, we consider a more practical unknown MIMO channel which results from 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 controlled amount of 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, power spectra as well as the source signals themselves. Recovery conditions of the proposed method are analyzed, and Cramér-Rao bound (CRB) results for our estimation problem are derived. Simulation results are presented to illustrate the effectiveness of the proposed method.
KW - CANDECOMP/PARAFAC decomposition
KW - Wideband spectrum sensing
KW - multipath propagation
KW - sub-Nyquist sampling
UR - http://www.scopus.com/inward/record.url?scp=85122892119&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85122892119&partnerID=8YFLogxK
U2 - 10.1109/TWC.2021.3139294
DO - 10.1109/TWC.2021.3139294
M3 - Article
AN - SCOPUS:85122892119
SN - 1536-1276
VL - 21
SP - 5305
EP - 5316
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 7
ER -