TY - GEN
T1 - Covariance-Based Transmission Power Control for Estimation over Wireless Sensor Networks
AU - Soleymani, Touraj
AU - Zoppi, Samuele
AU - Vilgelm, Mikhail
AU - Hirche, Sandra
AU - Kellerer, Wolfgang
AU - Baras, John S.
N1 - Publisher Copyright:
© 2018 European Control Association (EUCA).
PY - 2018/11/27
Y1 - 2018/11/27
N2 - In this study, we would like to design a transmission power control mechanism for minimizing the transmit power of a wireless sensor node subject to a constraint on the quality of estimation at a remote estimator. In particular, we measure the estimation distortion by a mean square error function, and model the transmit power as a function of the packet success rate using the IEEE 802.15.4 standard which was formed for the specification of low-data-rate and low-power wireless communication. We formulate the problem with an infinite horizon discounted cost function. We show that there is a separation between the designs of the optimal estimator and optimal transmit power policy. Then, we use dynamic programming to characterize the optimal transmit power policy in terms of the estimation error covariance. Finally, we propose approximate value iteration as an approximation algorithm to calculate a near-optimal transmit power policy.
AB - In this study, we would like to design a transmission power control mechanism for minimizing the transmit power of a wireless sensor node subject to a constraint on the quality of estimation at a remote estimator. In particular, we measure the estimation distortion by a mean square error function, and model the transmit power as a function of the packet success rate using the IEEE 802.15.4 standard which was formed for the specification of low-data-rate and low-power wireless communication. We formulate the problem with an infinite horizon discounted cost function. We show that there is a separation between the designs of the optimal estimator and optimal transmit power policy. Then, we use dynamic programming to characterize the optimal transmit power policy in terms of the estimation error covariance. Finally, we propose approximate value iteration as an approximation algorithm to calculate a near-optimal transmit power policy.
UR - https://www.scopus.com/pages/publications/85059810995
U2 - 10.23919/ECC.2018.8550129
DO - 10.23919/ECC.2018.8550129
M3 - Conference contribution
AN - SCOPUS:85059810995
T3 - 2018 European Control Conference, ECC 2018
SP - 857
EP - 862
BT - 2018 European Control Conference, ECC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th European Control Conference, ECC 2018
Y2 - 12 June 2018 through 15 June 2018
ER -