NDLI: Spectrum estimation and spectrum hole opportunities prediction for cognitive radios using higher-order statistics

Content Provider	IEEE Xplore Digital Library
Author	Tabassam, A.A. Suleman, M.U. Khan, S. Tirmazi, S.H.R.
Copyright Year	2011
Description	Author affiliation: Institute of Informatics, Brandenburg University of Technology, 03042 - Cottbus, Germany (Tabassam, A.A.; Suleman, M.U.) \|\| School of Information Science, Halmstad University SE-301 18 - Halmstad, Sweden (Khan, S.; Tirmazi, S.H.R.)
Abstract	Cognitive Radio (CR) is a wireless advanced technology which can utilize an unlicensed as well as a licensed spectrum without a harmful interference to the primary users. An unbiased consistent spectrum estimator is required for the primary user's detection (sensing) for distinguishing the narrow band signals in a noisy environment. Cognitive radio's hardware solutions available in a commercial market are frequency band constrained at RF Front-End. In multi-dimensional radio spectrum space any of the dimension: time, frequency, code or space can be used as a transmission opportunity. The spectrum hole time opportunistic prediction is a promising solution to determine the free time slots for transmission within a frequency band. This paper presents classical and parametric statistical spectrum estimators for primary user's detection. It also presents statistical auto-regressive and moving average predictive modeling for grey-hole spectrum opportunities prediction in a time domain for cognitive radios where frequency, code and space (geographical location) are operational constraints. A prototype system for a cognitive radio is built on top of the software-defined radio in a MATLAB/-Simulink and interfaced with an USRP2 main-board and RFX2400 daughter-board from Ettus Research LLC.
Starting Page	213
Ending Page	217
File Size	647419
Page Count	5
File Format	PDF
ISBN	9781457701108
e-ISBN	9781457701092
DOI	10.1109/WiAd.2011.5983313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bluetooth USRP2 Software defined radio IEEE 802.11 Standards Autoregressive moving average model Time series analysis Predictive models MATLAB/-Simulink Cognitive radio Periodogram Mathematical model Autoregressive processes Spectrum estimation
Content Type	Text
Resource Type	Article

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