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Optimal Transmission Policies for Noisy Channels

Author

Listed:
  • Ger Koole

    (Division of Mathematics and Computer Science, Vrije Universiteit, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands)

  • Zhen Liu

    (IBM T.J. Watson Research Center, 30 Saw Mill River Road, Hawthorne, New York 10532)

  • Rhonda Righter

    (Department of Operations and Management Information Systems, Santa Clara University, Santa Clara, California 95053)

Abstract

We consider transmission policies for multiple users sharing a single wireless link to a base station. The noise, and hence the probability of correct transmission of a packet, depends on the state of the user receiving the packet. The state for each user is independent of the states of the other users and changes according to a two-state (good/bad) Markov chain. The state of a user is observed only when it transmits. We give conditions under which the optimal policy is the myopic policy, in which a packet is transmitted to the user that is most likely to be in the better of the two states. We do this by showing that the optimal value function is marginally linear in each of the users' probabilities of being in the good state. Our model also may be applied to flexible manufacturing systems with unreliable tools and networked computer systems.

Suggested Citation

  • Ger Koole & Zhen Liu & Rhonda Righter, 2001. "Optimal Transmission Policies for Noisy Channels," Operations Research, INFORMS, vol. 49(6), pages 892-899, December.
  • Handle: RePEc:inm:oropre:v:49:y:2001:i:6:p:892-899
    DOI: 10.1287/opre.49.6.892.10024
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    References listed on IDEAS

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    1. Kimberly M. Wasserman & Tava Lennon Olsen, 2001. "On Mutually Interfering Parallel Servers Subject to External Disturbances," Operations Research, INFORMS, vol. 49(5), pages 700-709, October.
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    Cited by:

    1. Azam Asanjarani & Yoni Nazarathy, 2020. "The Role of Information in System Stability with Partially Observable Servers," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 949-968, September.

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