TY - GEN
T1 - Learning Parallel Markov Chains over Unreliable Wireless Channels
AU - Wang, Weichang
AU - Ying, Lei
N1 - Funding Information:
ACKNOWLEDGEMENT Research supported in part by NSF ECCS 1609202, ECCS 1739344, CNS 2002608 and CNS 2001687, and NASA University Leadership Initiative program (Contract No. NNX17AJ86A)
Publisher Copyright:
© 2020 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - This paper studies the problem of communications between aircraft and a control tower for aviation risk monitoring over wireless channels. The control tower needs to monitor the state of each aircraft in real time by receiving reports from the aircraft. Due to limited bandwidth, only a subset of aircraft can communicate with the control tower at the same time. This paper focuses on the problem of optimal scheduling of data transmissions to minimize the risk. We formulate the problem as learning states of parallel Markov chains where each Markov chain represents an aircraft, and the objective is to minimize the information entropy of all the aircraft. We propose an algorithm based on Whittle's index and study the indexability of the problem for both single-state wireless channels and multi-state wireless channels. Our numerical evaluations show that our algorithm improves the accuracy of the estimations compared with the heuristic scheduling methods such as greedy and Round Robin.
AB - This paper studies the problem of communications between aircraft and a control tower for aviation risk monitoring over wireless channels. The control tower needs to monitor the state of each aircraft in real time by receiving reports from the aircraft. Due to limited bandwidth, only a subset of aircraft can communicate with the control tower at the same time. This paper focuses on the problem of optimal scheduling of data transmissions to minimize the risk. We formulate the problem as learning states of parallel Markov chains where each Markov chain represents an aircraft, and the objective is to minimize the information entropy of all the aircraft. We propose an algorithm based on Whittle's index and study the indexability of the problem for both single-state wireless channels and multi-state wireless channels. Our numerical evaluations show that our algorithm improves the accuracy of the estimations compared with the heuristic scheduling methods such as greedy and Round Robin.
KW - Multi-state channel
KW - Restless Multi-Armed Bandit Problem
KW - Whittle's Index
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U2 - 10.1109/CISS48834.2020.1570614323
DO - 10.1109/CISS48834.2020.1570614323
M3 - Conference contribution
AN - SCOPUS:85085240860
T3 - 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020
BT - 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 54th Annual Conference on Information Sciences and Systems, CISS 2020
Y2 - 18 March 2020 through 20 March 2020
ER -