Value of Information in Optimal Flow-Level Scheduling of Users with Markovian Time-Varying Channels
February 8, 2013
Abstract:
In this paper we design, characterize in closed-form, and evaluate a new index rule for Markovian time-varying channels, which gives rise to a simple opportunistic scheduling rule for flow-level scheduling in wireless downlink systems. For user channels we employ the Gilbert-Elliot model with a flow-level interpretation: the channel condition follows a general two-state Markov chain with distinct probabilities of finishing the flow transmission. The index value of the bad channel condition takes into account both the one-period and the steady-state potential improvement of the service completion probability, while the good channel condition gets an absolute priority with the c*mu-index (well-known to be throughput-optimal) as the tie-breaking rule. Our computational study con firms near-optimality of the proposed rule in most of the instances, and suggests that information about the channels steady state is often enough to achieve near-optimality.
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Who is Peter Jacko?
Peter Jacko is currently with the Basque Center for Applied Mathematics (BCAM), Spain. He obtained his Ph.D. in Business Administration and Quantitative Methods (2009) and D.E.A. in Statistics and Operations Research (2006) from Carlos III University of Madrid, Spain. He obtained his Mgr. (2003) and Bc. (2002) degrees in Mathematics from Pavol Jozef Safarik University in Kosice, Slovakia. His main research interests are in designing simple and well-performing scheduling and resource allocation solutions to dynamic and stochastic problems, especially those arising in the context of networks.
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