Multi‐taper spectrum‐based estimator for cognitive radio using multiple antennas and STBC techniques. Issue 2 (31st January 2018)

• Record Type: Journal Article
• Authors: Abdul Salam, Ahmed O.; Sheriff, Ray E.; Al‐Araji, Saleh R.; Mezher, Kahtan; Nasir, Qassim
• Is Part Of: IET circuits, devices & systems. Volume 12:Issue 2(2018)
• Page Start: 133
• Page End: 143
• Publication Date: 2018-01-31
• Subjects: cognitive radio -- antenna arrays -- space-time block codes -- channel coding -- radio spectrum management -- MIMO communication -- singular value decomposition -- channel estimation -- diversity reception -- eigenvalues and eigenfunctions -- statistical analysis -- approximation theory; multitaper spectrum-based estimator -- multiple antennas -- STBC techniques -- SE design -- cognitive radio systems -- MTM -- spatiotemporal features -- bias-variance dilemma -- multiple-input-multiple-output channel -- space-time block code -- channel effects -- system capacity enhancement -- singular value decomposition -- performance enhancement -- dominant eigenchannels -- maximum-ratio combining -- higher signal-to-noise ratios -- high data rates -- reliability levels -- statistical analysis -- performance metrics -- quadratic form approximation -- MTSE -- periodogram SE algorithms -- PSE algorithms; Electronic circuits -- Periodicals; Electronic systems -- Periodicals; 621.381505
• DOI: 10.1049/iet-cds.2016.0498
• Languages: English
• ISSNs: 1751-858X

Abstract

Abstract : An effective approach for the design of spectrum estimation (SE) in cognitive radio systems using multi‐taper method (MTM) and spatiotemporal features is presented in this study, whereas the MTM balances the bias‐variance dilemma, the multiple‐input–multiple‐output (MIMO) and space–time block code (STBC) are customarily aimed to defeat the adverse channel effects and enhance the system capacity and performance. The singular value decomposition is exploited to determine the dominant eigenchannels in MIMO and STBC setups. The maximum‐ratio combining, on the other hand, is adopted to produce higher signal‐to‐noise ratios usually intended for high data rates and reliability levels. The statistical analysis and modelling of the performance metrics associated with the SE based on MTM‐STBC and MIMO are approached using the quadratic form approximation. Simulation exercises are employed to compare this different SE, which will be called multitaper spectrum estimation (MTSE), against other typical methods such as the periodogram without tapering options. The results exhibit performance gains due to the merger of MTSE and STBC technologies over MIMO and periodogram SE (PSE) algorithms. Further computational analysis shows that the MTSE–STBC has no extra burdens compared with its PSE counterpart.