Network Utility Maximization over Partially Observable Markovian Channels

Mathematics – Optimization and Control

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

9 pages, 2 figures, submitted to IEEE INFOCOM 2011

Scientific paper

We consider a utility maximization problem over partially observable Markov ON/OFF channels. In this network instantaneous channel states are never known, and at most one user is selected for service in every slot according to the partial channel information provided by past observations. Solving the utility maximization problem directly is difficult because it involves solving partially observable Markov decision processes. Instead, we construct an approximate solution by optimizing the network utility only over a good constrained network capacity region rendered by stationary policies. Using a novel frame-based Lyapunov drift argument, we design a policy of admission control and user selection that stabilizes the network with utility that can be made arbitrarily close to the optimal in the constrained region. Equivalently, we are dealing with a high-dimensional restless bandit problem with a general functional objective over Markov ON/OFF restless bandits. Thus the network control algorithm developed in this paper serves as a new approximation methodology to attack such complex restless bandit problems.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Network Utility Maximization over Partially Observable Markovian Channels does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Network Utility Maximization over Partially Observable Markovian Channels, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Network Utility Maximization over Partially Observable Markovian Channels will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-80328

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.