학술논문

A fast Bayesian model for latent radio signal prediction
Document Type
Conference
Source
2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, 2009. WiOPT 2009. 7th International Symposium on. :1-7 Jun, 2009
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Bayesian methods
Predictive models
Frequency
Cognitive radio
Uncertainty
Statistics
Educational institutions
Data analysis
Signal processing
Parameter estimation
Dynamic spectrum access
latent radio signal
Bayesian estimation
integrated nested Laplace approximation
Language
Abstract
This paper considers the use of a recently developed Bayesian statistical approximation technique that leads to very fast determination of highly accurate estimates for latent radio signal power. Following suitable data analysis, a first order non-stationary auto-regressive process is considered for latent radio signal and the fast approximation technique is then used to provide accurate estimates of the hidden model parameters. These estimates are based on having received several noisy, but spatially correlated, observations of the true latent signal. The implication of this technique for real time decision analysis and the problem of finding, and making use of, so-called radio spectrum holes is also discussed.