학술논문

Schwarz Information Criterion Based Thompson Sampling for Dynamic Spectrum Access in Non-Stationary Environment
Document Type
Periodical
Author
Source
IEEE Communications Letters IEEE Commun. Lett. Communications Letters, IEEE. 28(3):737-741 Mar, 2024
Subject
Communication, Networking and Broadcast Technologies
Sensors
Channel estimation
Wireless sensor networks
Wireless communication
Simulation
Silicon
Reinforcement learning
Dynamic spectrum access
non-stationary environment
Thompson sampling
Schwarz information criterion
Language
ISSN
1089-7798
1558-2558
2373-7891
Abstract
The listen before talk (LBT) mechanism is often used in dynamic spectrum access (DSA) schemes, which requires secondary users (SUs) to perform spectrum sensing before accessing a channel so as to avoid transmission collisions with primary users (PUs). In the scenario of DSA with multiple PU channels, channel sensing order according to the idle probabilities of PU channels is important for SUs to improve the spectrum efficiency. However, conventional DSA schemes are sluggish in updating the estimates of idle probabilities sequentially, which hinders their application in highly dynamic channels (with time-varying idle probabilities). To overcome this issue, we propose a change detection algorithm with a binary hypothesis testing of Schwarz Information Criterion (SIC), and present an SIC based Thompson Sampling Algorithm (SIC-TSA) to promptly update the estimates of idle probabilities. Moreover, the collision probabilities among SUs are analyzed. Numerical results are provided to show that SIC-TSA outperforms state-of-the-art methods, especially when channel traffic is high.