15,665 research outputs found
From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks
Strategies to acquire white space information is the single most significant functionality in cognitive
radio networks (CRNs) and as such, it has gone some evolution to enhance information accuracy. The
evolution trends are spectrum sensing, prediction algorithm and recently, geo‐location database
technique. Previously, spectrum sensing was the main technique for detecting the presence/absence of
a primary user (PU) signal in a given radio frequency (RF) spectrum. However, this expectation could not
materialized as a result of numerous technical challenges ranging from hardware imperfections to RF
signal impairments. To convey the evolutionary trends in the development of white space information,
we present a survey of the contemporary advancements in PU detection with emphasis on the practical
deployment of CRNs i.e. Television white space (TVWS) networks. It is found that geo‐location database
is the most reliable technique to acquire TVWS information although, it is financially driven. Finally,
using financially driven database model, this study compared the data‐rate and spectral efficiency of FCC
and Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms FCC TV
channelization as a result of having higher spectrum bandwidth. We proposed the adoption of an allinclusive
TVWS information acquisition model as the future research direction for TVWS information
acquisition techniques
From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks
Strategies to acquire white space information is the single most significant
functionality in cognitive radio networks (CRNs) and as such, it has gone some evolution
to enhance information accuracy. The evolution trends are spectrum sensing, prediction
algorithm and recently, geo-location database technique. Previously, spectrum sensing was
the main technique for detecting the presence/absence of a primary user (PU) signal in a
given radio frequency (RF) spectrum. However, this expectation could not materialized as
a result of numerous technical challenges ranging from hardware imperfections to RF
signal impairments. To convey the evolutionary trends in the development of white space
information, we present a survey of the contemporary advancements in PU detection with
emphasis on the practical deployment of CRNs i.e. Television white space (TVWS) networks.
It is found that geo-location database is the most reliable technique to acquire
TVWS information although, it is financially driven. Finally, using financially driven
database model, this study compared the data-rate and spectral efficiency of FCC and
Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms
FCC TV channelization as a result of having higher spectrum bandwidth. We proposed the
adoption of an all-inclusive TVWS information acquisition model as the future research
direction for TVWS information acquisition techniques
From sensing to predictions and database technique: a review of TV white space information acquisition in cognitive radio networks
Strategies to acquire white space information is the single most significant functionality in cognitive radio networks (CRNs) and as such, it has gone some evolution to enhance information accuracy. The evolution trends are spectrum sensing, prediction algorithm and recently, geo-location database technique. Previously, spectrum sensing was the main technique for detecting the presence/absence of a primary user (PU) signal in a given radio frequency (RF) spectrum. However, this expectation could not materialized as a result of numerous technical challenges ranging from hardware imperfections to RF signal impairments. To convey the evolutionary trends in the development of white space information, we present a survey of the contemporary advancements in PU detection with emphasis on the practical deployment of CRNs i.e. Television white space (TVWS) networks. It is found that geo-location database is the most reliable technique to acquire TVWS information although, it is financially driven. Finally, using financially driven database model, this study compared the data-rate and spectral efficiency of FCC and Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms FCC TV channelization as a result of having higher spectrum bandwidth. We proposed the adoption of an all-inclusive TVWS information acquisition model as the future research direction for TVWS information acquisition techniques
Enforcement in Dynamic Spectrum Access Systems
The spectrum access rights granted by the Federal government to spectrum users come with the expectation of protection from harmful interference. As a consequence of the growth of wireless demand and services of all types, technical progress enabling smart agile radio networks, and on-going spectrum management reform, there is both a need and opportunity to use and share spectrum more intensively and dynamically. A key element of any framework for managing harmful interference is the mechanism for enforcement of those rights. Since the rights to use spectrum and to protection from harmful interference vary by band (licensed/unlicensed, legacy/newly reformed) and type of use/users (primary/secondary, overlay/underlay), it is reasonable to expect that the enforcement mechanisms may need to vary as well.\ud
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In this paper, we present a taxonomy for evaluating alternative mechanisms for enforcing interference protection for spectrum usage rights, with special attention to the potential changes that may be expected from wider deployment of Dynamic Spectrum Access (DSA) systems. Our exploration of how the design of the enforcement regime interacts with and influences the incentives of radio operators under different rights regimes and market scenarios is intended to assist in refining thinking about appropriate access rights regimes and how best to incentivize investment and growth in more efficient and valuable uses of the radio frequency spectrum
Spectrum sensing by cognitive radios at very low SNR
Spectrum sensing is one of the enabling functionalities for cognitive radio
(CR) systems to operate in the spectrum white space. To protect the primary
incumbent users from interference, the CR is required to detect incumbent
signals at very low signal-to-noise ratio (SNR). In this paper, we present a
spectrum sensing technique based on correlating spectra for detection of
television (TV) broadcasting signals. The basic strategy is to correlate the
periodogram of the received signal with the a priori known spectral features of
the primary signal. We show that according to the Neyman-Pearson criterion,
this spectral correlation-based sensing technique is asymptotically optimal at
very low SNR and with a large sensing time. From the system design perspective,
we analyze the effect of the spectral features on the spectrum sensing
performance. Through the optimization analysis, we obtain useful insights on
how to choose effective spectral features to achieve reliable sensing.
Simulation results show that the proposed sensing technique can reliably detect
analog and digital TV signals at SNR as low as -20 dB.Comment: IEEE Global Communications Conference 200
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