A Novel Sensing Nodes and Decision Node Selection Method for Energy Efficiency of Cooperative Spectrum Sensing in Cognitive Sensor Networks

Najimi, Maryam; Ebrahimzadeh, Ataollah; Andargoli, Seyed Mehdi Hosseini; Fallahi, Afshin

doi:10.1109/jsen.2013.2240900

Cited by 80 publications

(89 citation statements)

References 23 publications

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“…Therefore, λ 1 = 0 is the optimal solution to (12). Using this result, we can relax one of the arguments of the problem.…”

Section: A or Rulementioning

confidence: 94%

“…Censoring for distributed spectrum sensing is considered in [8]- [12]. The communication overhead of the cognitive radio network is reduced by employing a censoring policy in [8] for an OR rule based distributed spectrum sensing scenario.…”

Section: Introductionmentioning

confidence: 99%

“…Further, in [11], only the OR rule is considered, while in this paper, we apply this to the AND rule as well. A joint sensing and decision node selection scheme is considered in [12]. The network energy consumption is minimized subject to a detection performance constraint defined as in [11], in order to determine the sensing nodes from a pool of cognitive radios and subsequently the decision nodes from the selected sensing nodes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

To AND or To OR: How shall the fusion center rule in energy-constrained cognitive radio networks?

Maleki

Leus

Chatzinotas

et al. 2014

2014 IEEE International Conference on Communications (ICC)

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Abstract-Distributed spectrum sensing enhances the detection reliability of a cognitive radio network. However, this comes at the price of a higher energy consumption. To solve this problem, a combined censoring and sleeping scheme is considered where the cognitive radios switch off their sensing module with a specific sleeping rate in each sensing period. The awake cognitive radios send their local decisions to the fusion center only if it is deemed to be informative. The fusion center either employs the OR or the AND rule to make the final decision about the presence or absence of the primary user. This paper investigates which rule performs better in terms of energy efficiency under various conditions. The underlying sensing parameters are derived by minimizing the maximum average energy consumption per sensor subject to a constraint on the probabilities of false alarm and detection. This way, it can be ensured that the spectrum opportunities are utilized efficiently while the primary users are not interfered with. A case study based on IEEE 802.15.4/ZigBee is considered for performance evaluation. It is shown that significant energy savings can be obtained by employing combined censoring and sleeping.

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“…Therefore, λ 1 = 0 is the optimal solution to (12). Using this result, we can relax one of the arguments of the problem.…”

Section: A or Rulementioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

To AND or To OR: How shall the fusion center rule in energy-constrained cognitive radio networks?

Maleki

Leus

Chatzinotas

et al. 2014

2014 IEEE International Conference on Communications (ICC)

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show abstract

“…To achieve this, CRSNs have to perform spectrum sensing besides the information collection, and to design access schemes which produce strictly limited interference to primary users (PUs). On the other hand, different from CR networks [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], CRSNs inherit the fundamental limitations of traditional WSNs whose lifetime and capabilities (e.g. computation, communication and storage) are strictly limited due to constrains in energy resources and low-cost hardwares.…”

Section: Introductionmentioning

confidence: 99%

Utility‐based opportunistic spectrum access for cognitive radio sensor networks: joint spectrum sensing and random access control

et al. 2016

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This study formulates a novel optimisation problem for joint spectrum sensing and random access control (JS 2 RAC) in cognitive radio sensor networks (CRSNs). The JS 2 RAC is formulated as a network utility maximisation problem, which aims to maximise the sum of utilities over all links in the network but subject to the primary user protection constraint, the energy constraint, and the physical constraint. Due to the non-separable and non-convex nature of the JS 2 RAC problem, the authors propose a primal-decomposition-based iterative (PDI) algorithm which decomposes the JS 2 RAC problem into a spectrum sensing subproblem and a random access control subproblem, and solve the two subproblems iteratively. Then, the authors prove the convergence of the PDI algorithm and show its distributed implementation in practice. Simulations demonstrate the fast convergence and the near-optimal nature of the PDI algorithm and show its significant improvement in the network utility of CRSNs in comparison with the method of optimising spectrum sensing and random access separately.

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“…A joint sensing and decision node selection scheme is considered in [21]. The network energy consumption is minimized subject to a detection performance constraint defined as in [20], in order to determine the sensing nodes from a pool of cognitive radios and subsequently the decision nodes from the selected sensing nodes.…”

mentioning

confidence: 99%

To AND or To OR: On Energy-Efficient Distributed Spectrum Sensing With Combined Censoring and Sleeping

Maleki

Leus

Chatzinotas

et al. 2015

IEEE Trans. Wireless Commun.

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Abstract-Distributed spectrum sensing improves the detection reliability of a cognitive radio network but generally comes at the price of a large power consumption. Since cognitive radios are generally low-power sensors with limited batteries, a combined censoring and sleeping scheme is considered as an energy-efficient algorithm for distributed spectrum sensing. Each sensor switches off its sensing module with a specific sleeping rate. When the sensor is on, a censoring policy is employed in order to send the sensing result to the fusion center. The result is only transmitted, if it is deemed to be informative. Hence, the energy consumption of each sensor, including the sensing and transmission energies, is reduced. The underlying sensing parameters are derived by minimizing the maximum average energy consumption per sensor subject to a lower-bound on the global probability of detection and an upper-bound on the global probability of false alarm. We analyze the problem for the OR and the AND rule and provide a performance analysis for a case study based on the IEEE 802.15.4/ZigBee standard. It is shown that the combined censoring and sleeping scheme achieves a significant energy saving compared to the case where no censoring or sleeping is taken into account.Index Terms-Energy-efficiency, combined censoring and sleeping, distributed spectrum sensing, cognitive radio networks.

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A Novel Sensing Nodes and Decision Node Selection Method for Energy Efficiency of Cooperative Spectrum Sensing in Cognitive Sensor Networks

Cited by 80 publications

References 23 publications

To AND or To OR: How shall the fusion center rule in energy-constrained cognitive radio networks?

To AND or To OR: How shall the fusion center rule in energy-constrained cognitive radio networks?

Utility‐based opportunistic spectrum access for cognitive radio sensor networks: joint spectrum sensing and random access control

To AND or To OR: On Energy-Efficient Distributed Spectrum Sensing With Combined Censoring and Sleeping

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