Optimal transmission policies for two-user multiple access broadcast using dynamic team theory

2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010

Volumn , Issue , 2010, Pages 806-813

  Mahajan, Aditya ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION SPACES; ARRIVAL RATES; BINARY FEEDBACK; BROADCAST CHANNELS; BUFFER STATE; CHANNEL FEEDBACKS; COUNTABLE STATE SPACE; DYNAMIC PROGRAMS; EXACT ANALYTIC SOLUTIONS; INFORMATION STRUCTURES; MULTIPLE ACCESS; NON-LINEAR DYNAMICS; NON-TRIVIAL; OPTIMAL POLICIES; OPTIMAL TRANSMISSION POLICY; REDUNDANT DATA; SUFFICIENT CONDITIONS; WINDOW PROTOCOL;

LIGHT TRANSMISSION; OPTIMIZATION;

DYNAMIC PROGRAMMING;

EID: 79952437570     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ALLERTON.2010.5706991     Document Type: Conference Paper

References (16)

1. F. C. Schoute, "Decentralized control in packet switched satellite communication," IEEE Trans. Autom. Control, vol. AC-23, no. 2, pp. 362-271, Apr. 1976.
2. P. Varaiya and J. Walrand, "Decentralized control in packet switched satellite communication," IEEE Trans. Autom. Control, vol. AC-24, no. 5, pp. 794-796, Oct. 1979.
3. M. G. Hluchyj and R. G. Gallager, "Multiacces of a slotted channel by finitely many users," in Proceedings of National Telecommunication Conference, 1981, pp. D.4.2.1-D.4.2.7.
4. J. M. Ooi and G. W. Wornell, "Decentralized control of a mutliple access broadcast channel: performance bounds," in Proccedings of the 35th Conference on Decision and Control, Kobe, Japan, 1996, pp. 293-298.
5. E. A. Hansen, D. S. Bernstein, and S. Zilberstein, "Dynamic programming for partially observable stochastic games," in Proceedings of the 19th national conference on artificial intelligence (AAAI), San Jose, CA, Jul. 2004, pp. 709-715.
6. D. S. Bernstein, E. A. Hansen, and S. Zilberstein, "Bounded policy iteration for decentralized POMDPs," in Proceedings of the 19th International Joint Conference on Artificial Intelligence (UAI), 2005, pp. 1287-1292.
7. D. Szer and F. Charpillet, "Point-based dynamic programming for decpomdps," in proceedings of the 21st national conference on Artificial intelligence (AAAI). AAAI Press, 2006, pp. 1233-1238.
8. S. Seuken and S. Zilberstein, "Memory-bounded dynamic programming for DEC-POMDPs," in Proceedings of the 20th international joint conference on Artifical intelligence (IJCAI). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2007, pp. 2009-2015.
9. L. I. Sennott, "The computation of average optimal policies in denumerable state Markov decision chains," Advances in Applied Probability, vol. 29, pp. 114-137, 1997.
10. M. DeGroot, Optimal Statistical Decisions. McGraw Hills, 1970.
11. H. S. Witsenhausen, "Separation of estimation and control for discrete time systems," Proc. IEEE, vol. 59, no. 11, pp. 1557-1566, Nov. 1971.
12. A. Mahajan, A. Nayyar, and D. Teneketzis, "Identifying tractable decentralized control problems on the basis of information structures," in proceedings of the 46th Allerton conference on communication, control and computation, Sep. 2008, pp. 1440-1449.
13. A. Anastasopoulos, "A sequential transmission scheme for multiple access channel with noiseless feedback," 2009, preprint.
14. P. R. Kumar and P. Varaiya, Stochastic Systems: Estimation Identification and Adaptive Control. Prentice Hall, 1986.
15. R. A. Howard, Dynamic Programming and Markov Processes. The M.I.T. Press, 1960.
16. M. Aicardi, F. Davoli, and R. Minciardi, "Decentralized optimal control of Markov chains with a common past information set," IEEE Trans. Autom. Control, vol. 32, no. 11, pp. 1028-1031, 1987.