AI Article Synopsis
- This study focuses on wireless covert communication in environments with different noise levels across sensors.
- The authors use KL divergence to measure covertness and mutual information for transmission rates, employing Taylor series to approximate these metrics.
- They derive analytical expressions for optimization and demonstrate that selecting the right phase angle is crucial for effective communication in noisy conditions, backed by numerical results that confirm their method's advantages.
Article Abstract
This work investigates wireless covert communication in a multi-sensor asymmetric noise scenario. We adopt KL (Kullback-Leibler) divergence as the covertness constraint metric and mutual information as the transmission rate metric. To accurately approximate KL divergence and mutual information in covert communication, we employ the Taylor series expansion technique. Analytical expressions for KL divergence and mutual information in covert communication are derived, and we optimize the amplitude gain and phase angles based on these analytical expressions. Our findings underscore the importance of phase angle selection in covert communication within asymmetric noise systems. We propose an effective method for optimizing the transmission amplitude gain and phase angles in scenarios with asymmetric noise. Numerical results validate the effectiveness and superiority of our proposed method.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10857265 | PMC |
| http://dx.doi.org/10.3390/s24030796 | DOI Listing |
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