Outage-Constrained Sensing Threshold Design for Decentralized Decision-Making in Cognitive Radio Networks

Bajaj, Ian; Lee, Yee Hui

doi:10.1109/tcomm.2016.2615626

Cited by 2 publications

(3 citation statements)

References 33 publications

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“…Due to the features characterizing of cognitive radio, it is pertinent to think about what could be considered a good combination of m and n. For a fixed K = n − m, it is possible to have different combinations of n and m, but although m ⟶ n would seem a good option especially when n is greater than or equal to 10, because redundancy is significantly reduced, this implies two considerations: (i) dispersion and recovery times increase, and (ii) what is even more important, the probability that K or more faults occur increases with n, as argued below. Consider two instances of IDA with parameters (5,3) and (10,8), respectively. Both offer the same tolerance, but the second case does so with a lower cost in redundancy (0.666 vs. 0.25, respectively).…”

Section: Additional Redundancymentioning

confidence: 99%

“…In the last 15 years, there has been exhaustive research to solve the main issues to make CR networks (CRN) effective and practical [1][2][3][4][5]. Several authors have proposed different functionalities for CR devices which can be divided into four main functionalities, such as spectrum sensing [6,7], decision-making [8], sharing, and mobility in order to solve the OSA efficiently [9]. These functionalities depend on the interpretation and adaptation of different parameters, for example, sensing and data interpretation for adaptive modulation, power adjustments, and the changes regarding the range of frequency operation.…”

Section: Introductionmentioning

confidence: 99%

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System Design for Opportunistic Spectrum Access Using Statistical Decision-Making and Coded-MAC

Rodríguez-Colina

Jiménez

Palacios-Luengas

et al. 2020

Wireless Communications and Mobile Computing

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Different mechanisms have been proposed to solve opportunistic spectrum access (OSA). In order to address spectrum management efficiently, these mechanisms can be divided into four main functionalities, spectrum sensing, decision-making, sharing, and mobility. These functionalities depend on the interpretation and adaptation of different parameters, for example, sensing and data interpretation for adaptive modulation, power adjustments, and changes regarding the range of frequency operation. For the decision-making function, a novel approach is proposed in which coding information is added to the establishment of the communication process thus assisting the medium access control (MAC). The presence of cognitive radio devices in the network coverage range can be controlled or coordinated by using specific redundancy codes. Hence, Reed Solomon (RS) code is used in this paper as part of the handshaking process to provide error correction. In addition, a redundancy strategy based on Rabin’s information dispersal algorithm (IDA) is presented to provide fault tolerance to the communication between cognitive radio devices. In this case, the information is divided into fragments dynamically, and each fragment is coded by an RS code and reassigned to a subset of recipients using alternate paths. This work shows how to optimize spectrum access based on IDA and RS codes to diversify channel occupation without losing significant information with several frequency hops presented in cognitive radio communications. The validations were executed in a discrete event simulator developed in Python. The proposed system for OSA was found to perform better than other approaches using pilot sequences. Our proposal, therefore, provides fault tolerance, to diversify channel occupation, and helps identify the presence of primary and secondary users when a common control channel (CCC) is implemented by the optimization of the spectrum use.

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Section: Additional Redundancymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

System Design for Opportunistic Spectrum Access Using Statistical Decision-Making and Coded-MAC

Rodríguez-Colina

Jiménez

Palacios-Luengas

et al. 2020

Wireless Communications and Mobile Computing

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show abstract

“…However, before going into further discussion about existing time triggered handoff strategies, we depict the behavior of a CR user under time triggered handoff scenario in Figure 4. The process starts with the detection of PU arrival and predicting PU stayed duration on its licensed channel via continuous sensing [45][5]. One possibility for an SU is to predetermine target channels for spectrum handoff, thus keeping a list of channels before transmission.…”

Section: Time Triggered Handoff Schemesmentioning

confidence: 99%

Time triggered handoff schemes in cognitive radio networks: A survey

Mir

Bhatti

2018

Journal of Network and Computer Applications

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Outage-Constrained Sensing Threshold Design for Decentralized Decision-Making in Cognitive Radio Networks

Cited by 2 publications

References 33 publications

System Design for Opportunistic Spectrum Access Using Statistical Decision-Making and Coded-MAC

System Design for Opportunistic Spectrum Access Using Statistical Decision-Making and Coded-MAC

Time triggered handoff schemes in cognitive radio networks: A survey

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