TY - GEN
T1 - A Connection between Feedback Capacity and Kalman Filter for Colored Gaussian Noises
AU - Fang, Song
AU - Zhu, Quanyan
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported in part by NSF under grant ECCS-1847056 and SES-1541164, in part by a U. S. DOT grant through C2SMART Center at NYU, and in part by the U.S. DHS through the CIRI under Grant 2015-ST061-CIRC01.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - In this paper, we establish a connection between the feedback capacity of additive colored Gaussian noise channels and the Kalman filters with additive colored Gaussian noises. In light of this, we are able to provide lower bounds on feedback capacity of such channels with finite-order auto-regressive moving average colored noises, and the bounds are seen to be consistent with various existing results in the literature; particularly, the bound is tight in the case of first-order auto-regressive moving average colored noises. On the other hand, the Kalman filtering systems, after certain equivalence transformations, can be employed as recursive coding schemes/algorithms to achieve the lower bounds. In general, our results provide an alternative perspective while pointing to potentially tighter bounds for the feedback capacity problem.
AB - In this paper, we establish a connection between the feedback capacity of additive colored Gaussian noise channels and the Kalman filters with additive colored Gaussian noises. In light of this, we are able to provide lower bounds on feedback capacity of such channels with finite-order auto-regressive moving average colored noises, and the bounds are seen to be consistent with various existing results in the literature; particularly, the bound is tight in the case of first-order auto-regressive moving average colored noises. On the other hand, the Kalman filtering systems, after certain equivalence transformations, can be employed as recursive coding schemes/algorithms to achieve the lower bounds. In general, our results provide an alternative perspective while pointing to potentially tighter bounds for the feedback capacity problem.
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U2 - 10.1109/ISIT44484.2020.9174357
DO - 10.1109/ISIT44484.2020.9174357
M3 - Conference contribution
AN - SCOPUS:85090416254
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2055
EP - 2060
BT - 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020
Y2 - 21 July 2020 through 26 July 2020
ER -