Opportunistic channel allocation decision making in cognitive radio communications

Shatila, Hazem; Khedr, Mohamed; Reed, Jeffrey H.

doi:10.1002/dac.2350

Cited by 15 publications

(7 citation statements)

References 29 publications

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“…The effect of imperfections in the radio environment map (REM) information on the performance of cognitive radio (CR) systems was investigated in [37]. In opportunistic channel allocation algorithms [38] the duration of fade event may play an important role. Therefore in our paper we propose fade duration statistics as a tool for opportunity length estimation.…”

Section: Mobile Sensing Of the Dvb-t Spectrummentioning

confidence: 99%

A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile Users

Csurgai-Horváth¹,

Rieger²,

Kertesz³

2016

Mobile Information Systems

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Cognitive radio (CR) systems are designed to utilize the available radio spectrum in an efficient and intelligent manner. Terrestrial Digital Video Broadcasting (DVB-T) frequency bands are one of the future candidates for cognitive radio applications especially because after digital television transition the TV white spaces (TVWS) became available for radio communication. This paper deals with the survey of the DVB-T spectrum; wideband measurements were performed on mobile platform in order to study the variation of the radio signal power in city area aboard a moving vehicle. The measurement environment was a densely built-in region where the proper DVB-T receiving was guaranteed by three TV transmitters, utilizing three central channel frequencies using 610, 746, and 770 MHz. In our paper the methods, the applied antenna, and measurement devices will be presented together with simulated and measured fading statistics. The final result is an estimation of the cognitive DVB-T spectrum utilization opportunity; furthermore a scenario is also proposed for secondary channel usage.

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Section: Mobile Sensing Of the Dvb-t Spectrummentioning

confidence: 99%

A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile Users

Csurgai-Horváth¹,

Rieger²,

Kertesz³

2016

Mobile Information Systems

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“…The CE makes the radio collect information about the operating environment, capability, and characteristics of the radio, and then changes the transmission parameters of the radio to satisfy the requirements of the user. Some researchers focus on only one transmission parameters reconfiguration in CR network, such as dynamic channel allocation [5][6][7][8] and resource allocation [9,10]. To achieve better performance in changeable wireless environment, we always hope more parameters of the radio can adapt with the changes of surrounding environment, which would make the radio have better ability to guarantee the user's QoS requirements.…”

Section: Introductionmentioning

confidence: 99%

A genetic‐based cognitive link decision algorithm for OFDM system

Tan

Zhang

Liu

et al. 2012

Int J Communication

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SUMMARYTo solve the problem of cognitive link decision for OFDM system in a time-varying environment, an improved genetic algorithm-based decision-making module is proposed. At first, the decision-making module collects the environmental information and QoS requirements of the radio and then produces link configuration for the radio on the basis of the improved genetic algorithm. New crossover and mutation strategies are introduced to accelerate convergence rate of the genetic algorithm. A novel population initialization method is also proposed to reduce the time of achieving the optimal decision by the decision-making module when the radio is operated in a slow changeable environment. Simulations and discussions demonstrate the effectiveness of the decision-making module, and this research work exhibits its importance of enhancing the decision speed that is of crucial demand in cognitive decision-making applications.

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“…Once the spectrum management phase is over, the licensed/primary user (PU) is allocated to the spectrum. Even the opportunistic spectrum allocation [9] can be easily implemented with the help of cognitive radios. Through cognitive radio networks (CRNs), the dynamic spectrum access [6,7] can be easily implemented.…”

Section: Introductionmentioning

confidence: 99%

“…In [8], a health care autonomous network based on cognitive radio infrastructure has been designed. Even the opportunistic spectrum allocation [9] can be easily implemented with the help of cognitive radios. This technology can also be used in public safety network through opportunistic spectrum access.…”

Section: Introductionmentioning

confidence: 99%

CCRA: channel criticality based resource allocation in cognitive radio networks

Kumar

Minz

2015

Int J Communication

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In cognitive radio networks, signal to interference plus noise ratio (SINR) is a quantity that is used to analyze the bounds of the capacity of a channel. This is the reason for SINR being one of the important parameters toward evaluating the performance of spectrum sharing in every network. To maximize the channel utilization in any network, the SINR of a channel should be considered to be within a threshold. This also leads to lesser power consumption, and the quality of service for the licensed users is maintained. Further, reduced SINR leads to an improvement in the quality of communication in the network. In this paper, a graph theoretic measure for the efficient utilization of channels in cognitive radio networks has been proposed and is named as channel criticality based resource allocation (CCRA). Using the SINR as the weight of the graph, a novel concept of channel criticality has also been introduced in this work. The proposed CCRA technique has also been compared with the existing interference aware channel assignment (IACA) technique in terms of the channel utilization. Through simulations, the CCRA has been observed to outperform the IACA scheme. The average channel utilization of the proposed CCRA was observed to have increased by 8%, when the secondary users were introduced in the network as compared with the IACA technique. Copyright Int. J. Commun. Syst. 2017; 30: e3012 V. KUMAR AND S. MINZThe betweenness of the link k for the source and destination pair .a; b/ is given by of 12 6

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Opportunistic channel allocation decision making in cognitive radio communications

Cited by 15 publications

References 29 publications

A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile Users

A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile Users

A genetic‐based cognitive link decision algorithm for OFDM system

CCRA: channel criticality based resource allocation in cognitive radio networks

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