Stochastic systems: estimation, identification and adaptive control
Stochastic systems: estimation, identification and adaptive control
Discrete-time controlled Markov processes with average cost criterion: a survey
SIAM Journal on Control and Optimization
The Complexity of Optimal Queuing Network Control
Mathematics of Operations Research
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Probability in the Engineering and Informational Sciences
Optimal channel probing and transmission scheduling for opportunistic spectrum access
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Approximation Algorithms for Partial-Information Based Stochastic Control with Markovian Rewards
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
Monotonicity in Markov Reward and Decision Chains: Theory and Applications
Foundations and Trends® in Stochastic Systems
Approximation algorithms for restless bandit problems
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
IEEE Transactions on Wireless Communications
Opportunistic spectrum access for energy-constrained cognitive radios
IEEE Transactions on Wireless Communications
On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance
IEEE Transactions on Wireless Communications - Part 2
Optimal Transmission Scheduling in Symmetric Communication Models With Intermittent Connectivity
IEEE Transactions on Information Theory
Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework
IEEE Journal on Selected Areas in Communications
Restless watchdog: selective quickest spectrum sensing in multichannel cognitive radio systems
EURASIP Journal on Advances in Signal Processing - Special issue on dynamic spectrum access for wireless networking
Opportunistic spectrum access in self-similar primary traffic
EURASIP Journal on Advances in Signal Processing - Special issue on dynamic spectrum access for wireless networking
Algorithms for dynamic spectrum access with learning for cognitive radio
IEEE Transactions on Signal Processing
Betting on Gilbert-Elliot channels
IEEE Transactions on Wireless Communications
Multi-channel opportunistic access: a case of restless bandits with multiple plays
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Myopic sensing for multiple SUs in multichannel opportunistic access
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Dynamic multichannel access with imperfect channel state detection
IEEE Transactions on Signal Processing
Queuing analysis in multichannel cognitive spectrum access: a large deviation approach
INFOCOM'10 Proceedings of the 29th conference on Information communications
IEEE Transactions on Information Theory
Dynamic channel, rate selection and scheduling for white spaces
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
Optimal index rules for single resource allocation to stochastic dynamic competitors
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
On distributed scheduling with heterogeneously delayed network-state information
Queueing Systems: Theory and Applications
Opportunistic schedulers for optimal scheduling of flows in wireless systems with ARQ feedback
Proceedings of the 24th International Teletraffic Congress
A dynamic programming approximation for downlink channel allocation in cognitive femtocell networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Hi-index | 754.90 |
This paper considers opportunistic communication over multiple channels where the state ("good" or "bad") of each channel evolves as independent and identically distributed (i.i.d.) Markov processes. A user, with limited channel sensing capability, chooses one channel to sense and decides whether to use the channel (based on the sensing result) in each time slot. A reward is obtained whenever the user senses and accesses a "good" channel. The objective is to design a channel selection policy that maximizes the expected total (discounted or average) reward accrued over a finite or infinite horizon. This problem can be cast as a partially observed Markov decision process (POMDP) or a restless multiarmed bandit process, to which optimal solutions are often intractable. This paper shows that a myopic policy that maximizes the immediate one-step reward is optimal when the state transitions are positively correlated over time. When the state transitions are negatively correlated, we show that the same policy is optimal when the number of channels is limited to two or three, while presenting a counterexample for the case of four channels. This result finds applications in opportunistic transmission scheduling in a fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and antijamming.