SCHEDULING IN A QUEUING SYSTEM WITH ASYNCHRONOUSLY VARYING SERVICE RATES
Probability in the Engineering and Informational Sciences
Stable scheduling policies for fading wireless channels
IEEE/ACM Transactions on Networking (TON)
Resource Allocation and Cross Layer Control in Wireless Networks (Foundations and Trends in Networking, V. 1, No. 1)
Markov Chains and Stochastic Stability
Markov Chains and Stochastic Stability
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
IEEE Journal on Selected Areas in Communications
Dynamic power allocation and routing for time-varying wireless networks
IEEE Journal on Selected Areas in Communications
A tutorial on cross-layer optimization in wireless networks
IEEE Journal on Selected Areas in Communications
Scheduling in multichannel wireless networks with flow-level dynamics
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Stability with file arrivals and departures in multichannel cellular wireless networks
Queueing Systems: Theory and Applications
Stability and asymptotic optimality of opportunistic schedulers in wireless systems
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
Scheduling in a random environment: stability and asymptotic optimality
IEEE/ACM Transactions on Networking (TON)
Delay-based back-pressure scheduling in multihop wireless networks
IEEE/ACM Transactions on Networking (TON)
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We consider multiuser scheduling in wireless networks with channel variations and flow-level dynamics. Recently, it has been shown that the MaxWeight algorithm, which is throughput-optimal in networks with a fixed number users, fails to achieve the maximum throughput in the presence of flowlevel dynamics. In this paper, we propose a new algorithm, called workload-based scheduling with learning, which is provably throughput-optimal, requires no prior knowledge of channels and user demands, and performs significantly better than previously suggested algorithms.