Cognitive radio: methods for the detection of free bands

Ghozzi, Mohamed; Döhler, Mischa; Marx, François; Palicot, Jacques

doi:10.1016/j.crhy.2006.07.009

Cited by 54 publications

(32 citation statements)

References 12 publications

(30 reference statements)

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“…The cyclostationary feature detector relies on the fact that most signals exhibit periodic features, present in pilots, cyclic prefixes, modulations, carriers and other repetitive characteristics [25,26,27,28,29,30]. Since the noise is not periodic, the signal can be successfully detected.…”

Section: Cyclostationary Feature Detectionmentioning

confidence: 99%

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Spectrum Sensing for Cognitive Radio

2009

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Section: Cyclostationary Feature Detectionmentioning

confidence: 99%

“…A newer work focuses on cyclostationary feature detector for cognitive radio networks [30], called multi-cycles detector. In this work, a cyclostationarity detector scheme is employed on non-filtered signals, such as OFDM, to detect the cyclic frequency and its harmonics.…”

Section: Cyclostationary Feature Detectionmentioning

confidence: 99%

Spectrum Sensing for Cognitive Radio

2009

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“…If the hypothesis H0 represents the case where the PU is not in the frequency band of interest, and the H1 represents the case where the PU is in the band, the signal detection problem can be modelled by a simple binary hypothesis-testing problem as follows [27]～ [29] . In order to detect the PU, the energy detection method is employed in this paper.…”

Section: -1 Conventional Cr System With Multiple Antennasmentioning

confidence: 99%

Performance of Energy Detection Spectrum Sensing with Delay Diversity for Cognitive Radio System

Kim¹,

Koo²,

Kim³

2009

Journal of electromagnetic engineering and science

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In this paper, a new spectrum sensing method based on energy detection is proposed and analyzed in a cognitive radio(CR) system. We employ a delay diversity receiver for sensing the primary user's spectrum with reasonable cost and complexity. Conventional CR with the receiver equipping multiple antennas requires additional hardware and space for installing multiple antennas in accordance with increase in the number of antennas. If the number of antennas increases, detection probability as well as hardware complexity and cost rise. Then, it is difficult to make a primary user detector practically. Therefore, we adopt a delay diversity receiver for solving problems of the conventional spectrum detector utilizing multiple antennas. We derive analytical expressions for the spectrum sensing performance of the proposed system. From the simulation results, it is demonstrated that the primary user detector with the delay diversity receiver has almost half the complexity and shows similar or improved performance as compared with that employing multiple antennas. Therefore, the proposed spectrum sensing structure can be a practical solution for enhancing the detection capacity in CR system operations. The results of this paper can be applied to legacy CR systems with simple modifications.

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“…Sensors are needed for that. Different kinds of sensors may be necessary: a standard recognition sensor [35] if the band of interest is dedicated to a wireless standard, an energy detector (radiometer) or a cyclo-stationarity detector if the goal is to detect a hole in the spectrum [36]. Then, on the basis of the spectrum policy in the area (the position maybe provided by a GPS for instance, and the policy provided thanks to a database updated according to the place), a decision of transmission in this band is done and the radio parameters are set to the adequate values permitting this transmission (carrier frequency, data rate, etc.).…”

Section: Examples Of Cognitive Decisionsmentioning

confidence: 99%

High-Level Design Approach for the Specification of Cognitive Radio Equipments Management APIs

Moy

2009

J Netw Syst Manage

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Cognitive Radio (CR) equipments are radio devices that support the smart facilities offered by future cognitive networks. Even if several categories of equipments exist (terminal, base station, smart PDA, etc.), each requiring different processing capabilities (and associated cost or power consumption), these equipments have to integrate also a set of new capabilities as regards CR support, in addition to the usual radio signal processing elements. This implies real-time radio adaptation and sensing capabilities, but not only. We assert that it is necessary to add inside the radio equipments some management facilities for that purpose, and we propose in this paper a high-level design approach for the specification of a management framework. This includes a set of designing rules, based on hierarchical units that are distributed over three levels, and the associated APIs necessary to efficiently manage CR features inside a CR equipment. The proposed architecture is called HDCRAM (Hierarchical and Distributed Cognitive Architecture Management). HDCRAM is an extension of a former hierarchical and distributed reconfiguration management (HDReM) architecture, which is derived from our previous research on Software Defined Radio (SDR). The HDCRAM adds to the HDReM's reconfiguration management facilities the necessary new management features, which enable the support of sensing and decision making facilities. It consists in the combination of one Cognitive Radio Management Unit (CRMU) with eachReconfiguration Management Unit (ReMU) IntroductionThe design of cognitive radio (CR) equipments will not be done efficiently if one uses the same tools as those used for the design of conventional radio equipments. One reason is that designing such a radio device is not solely a radio signal processing issue anymore. Of course, as in many other industrial domains, such as aeronautics, it becomes a hardware/software mixed issue with a plurality of capabilities and running modes on the one hand. But on the other hand, designing cognitive radio equipments also consists in designing the necessary management needed to support the real-time sensing of the environment and the real-time adaptation of the signal processing. Signal processing in our approach is not restricted to the physical layer and also includes all layers' signal processing, up to the application layer. Another reason is that the range of ways a CR equipment will have to run, will be very wide compared to that of the current radio equipment operation. Abstraction is necessary during the design phase of a CR equipment. In this respect, this paper proposes a high-level design approach, 2 integrating the design rules needed for the management of the signal processing operators, as well as the exploration means as regards the operation modes.Even if designing the signal processing part of a radio chain is not an easy task, it is however usual. The new design aspect lies in the management part and the associated impact on the signal processing, which has to be fl...

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Cognitive radio: methods for the detection of free bands

Cited by 54 publications

References 12 publications

Spectrum Sensing for Cognitive Radio

Spectrum Sensing for Cognitive Radio

Performance of Energy Detection Spectrum Sensing with Delay Diversity for Cognitive Radio System

High-Level Design Approach for the Specification of Cognitive Radio Equipments Management APIs

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