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In this paper, we present an efficient rate-guaranteed opportunistic scheduling (ROS) scheme, which optimizes the system throughput performance while satisfying the ldquofairnessrdquo constraint for resource allocation by exploiting time-varying channel states. We prove the optimality of the proposed scheduler via mathematical analysis and show that it has lower computational complexity compared with existing opportunistic scheduling algorithms. We define a new concept of guaranteed-rate node with loss, which is extended from the service curve with a loss model, to analyze the performance bounds of ROS, such as the statistic end-to-end packet delay bound. We validate the mathematical analysis and demonstrate the throughput performance improvement and a delay bound based on ns-2 simulations.