Opportunistic scheduling for OFDM systems with fairness constraints
EURASIP Journal on Wireless Communications and Networking - Cognitive Radio and Dynamic Spectrum Sharing Systems
Adaptive radio resource allocation in OFDMA systems: a survey of the state-of-the-art approaches
Wireless Communications & Mobile Computing - Next Generation Wireless Communications and Mobile Computing-Networking Technologies
Downlink scheduling and resource allocation for OFDM systems
IEEE Transactions on Wireless Communications
Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems
IEEE Transactions on Wireless Communications
Opportunistic power scheduling for dynamic multi-server wireless systems
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
IEEE Journal on Selected Areas in Communications
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
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In this paper, we study an opportunistic scheduling problem in an OFDMA system, in which sub-carriers of the system are allocated to each user in each time slot considering the time-varying channel condition and QoS requirement of each user. We consider two different classes of services that are represented with different types of utility functions. The utility function for a user in one class is defined as a function of its average data rate, which can be applicable to best-effort services and the utility function for a user in the other class is defined as a function of its instantaneous data rate, which can be applicable to rate-sensitive services. Those two types of utility functions have been extensively considered in opportunistic scheduling in wireless networks. However, in most of the previous work, they are considered separately in different problems. In this paper, we formulate a stochastic optimization problem that can treat those two types of utility functions in a single problem, which enables us to implement an opportunistic scheduling algorithm that can consider those two classes of services in a single system in a unified way. Through simulations, we first show that our algorithm provides a good approximation to the optimal solution. In addition, we also verify the appropriateness of our utility models. Copyright © 2010 John Wiley & Sons, Ltd.