Stochastic systems: estimation, identification and adaptive control
Stochastic systems: estimation, identification and adaptive control
A rate-adaptive MAC protocol for multi-Hop wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
OFDM Wireless LANs: A Theoretical and Practical Guide
OFDM Wireless LANs: A Theoretical and Practical Guide
Exploiting medium access diversity in rate adaptive wireless LANs
Proceedings of the 10th annual international conference on Mobile computing and networking
Optimizing transmission rate in wireless channels using adaptive probes
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Optimal channel probing and transmission scheduling for opportunistic spectrum access
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Distributed opportunistic scheduling for ad-hoc communications: an optimal stopping approach
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Opportunistic spectral usage: bounds and a multi-band CSMA/CA protocol
IEEE/ACM Transactions on Networking (TON)
Direction finding and “smart antennas” using software radio architectures
IEEE Communications Magazine
Wideband fading channel capacity with training and partial feedback
IEEE Transactions on Information Theory
Scheduling in Wireless Networks
Foundations and Trends® in Networking
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In this study, we consider optimal opportunistic spectrum access (OSA) policies for a transmitter in a multichannel wireless system, where a channel can be in one of multiple states. In such systems, the transmitter typically does not have complete information on the channel states, but can learn by probing individual channels at the expense of certain resources, e.g., energy and time. The main goal is to derive optimal strategies for determining which channels to probe, in what sequence, and which channel to use for transmission. We consider two problems within this context and show that they are equivalent to different data maximization and throughput maximization problems. For both problems, we derive key structural properties of the corresponding optimal strategy. In particular, we show that it has a threshold structure and can be described by an index policy.We further show that the optimal strategy for the first problem can only take one of three structural forms. Using these results, we first present a dynamic program that computes the optimal strategy within a finite number of steps, even when the state space is uncountably infinite. We then present and examine a more efficient, but suboptimal, two-step look-ahead strategy for each problem. These strategies are shown to be optimal for a number of cases of practical interest. We examine their performance via numerical studies.