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Optimality of myopic sensing in multi-channel opportunistic access.
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Abstract — We consider opportunistic communications over multiple channels where the state (“good ” or “bad”) of each chan-nel evolves as independent and identically distributed Markov processes. A user, with limited sensing and access capability, chooses one channel to sense and subsequently access (based on the sensed channel state) in each time slot. A reward is obtained when the user senses and accesses a “good ” channel. The objective is to design the optimal channel selection policy that maximizes the expected reward accrued over time. This problem can be generally formulated as a Partially Observable Markov Decision Process (POMDP) or a restless multi-armed bandit process, to which optimal solutions are often intractable. We show in this paper that the myopic policy, with a simple and robust structure, achieves optimality under certain conditions. This result finds applications in opportunistic communications in fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and anti-jamming. Opportunistic access, cognitive radio, POMDP, restless multi-armed bandit process, myopic policy. I. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Myopic Sensing Multi-channel Opportunistic Access Myopic Policy Restless Multi-armed Bandit Process Opportunistic Communication Expected Reward Optimal Solution Partially Observable Markov Decision Process Chan-nel Evolves Good Channel Certain Condition Opportunistic Access User Sens Time Slot Cognitive Radio Robust Structure Access Capability Optimal Channel Selection Policy Cognitive Radio Network Limited Sensing Resource-constrained Jamming Spectrum Overlay Sensed Channel State Multiple Channel |
| Content Type | Text |
| Resource Type | Article |
