Integrated Sensing and Communication Signal Processing Based on Compressed Sensing Over Unlicensed Spectrum Bands
IEEE Transactions on Cognitive Communications and Networking(2023)
摘要
As a promising key technology of 6th generation (6G) mobile communication
system, integrated sensing and communication (ISAC) technology aims to make
full use of spectrum resources to enable the functional integration of
communication and sensing. The ISAC-enabled mobile communication system
regularly operate in non-continuous spectrum bands due to crowded licensed
frequency bands. However, the conventional sensing algorithms over
non-continuous spectrum bands have disadvantages such as reduced peak-to-side
lobe ratio (PSLR) and degraded anti-noise performance. Facing this challenge,
we propose a high-precision ISAC signal processing algorithm based on
compressed sensing (CS) in this paper. By integrating the resource block group
(RBG) configuration information in 5th generation new radio (5G NR) and channel
information matrices, we can dynamically and accurately obtain power estimation
spectra. Moreover, we employ the fast iterative shrinkage-thresholding
algorithm (FISTA) to address the reconstruction problem and utilize K-fold
cross validation (KCV) to obtain optimal parameters. Simulation results show
that the proposed algorithm has lower sidelobes or even zero sidelobes compared
with conventional sensing algorithms. Meanwhile, compared with the improved 2D
FFT algorithm and conventional 2D FFT algorithm, the proposed algorithms in
this paper have a maximum improvement of 54.66
estimation accuracy, and 41.54
respectively.
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关键词
Compressed sensing (CS),integrated sensing and communication (ISAC),machine learning (ML),non-continuous spectrum,non-continuous OFDM (NC-OFDM),signal processing,unlicensed spectrum bands
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