On the Spectrum- and Energy-Efficiency Tradeoff in Cognitive Radio Networks

Hu, Hang; Zhang, Hang; Liang, Ying-Chang

doi:10.1109/tcomm.2015.2505281

Cited by 77 publications

(39 citation statements)

References 18 publications

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“…Fan and Jiang 35 have proposed an approach to compute the total sensing period for CU in multichannel CSS and provided the method to distribute the total sensing period among different channels to maximize the throughput. Therefore, Hu et al 44 have optimized the SE and EE separately by jointly optimizing the sensing time and decision threshold. Further, the expression for false-alarm probability has been derived, which depends on SNR values.…”

Section: Related Workmentioning

confidence: 99%

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Kumar

Thakur

Pandit

et al. 2019

Int J Communication

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One of the main challenges of spectrum sensing (SS) in the cognitive radio network (CRN) is selection of threshold for captivating the sensing decision, and such an issue becomes more challenging especially at low signal-to-noise ratio (SNR) because it affects the sensing performance and throughput of cognitive user (CU). However, the sensing decision of individual CU may not be accurate due to fading effects in the sensing environment, and significant improvement is accomplished with the cooperation of users. Therefore, in this paper, we have investigated the performance of energy detector SS (EDSS) technique in the CRN under fading environment with cooperative and noncooperative SS scenario. Further, we have introduced the concept of critical SNR (γ c ) to select the appropriate threshold and based on which the algorithms are proposed to enhance the throughput and reduce the total error (sensing error) probability of CU at different SNR (γ). From the results, we have accomplished that at the low SNR region (γ ≤ γ c ), throughput is maximum with constant false-alarm rate (CFAR) threshold selection approach in the cooperative scenario while in the high SNR region (γ > γ c ), its value is maximum with minimizing the error probability (MEP) threshold selection approach in the noncooperative scenario. Moreover, the sensing error is reduced with cooperation, and threshold selection with MEP approach outperforms CFAR approach for γ ≤ γ c . Further, the proposed approach outperforms the other approaches in terms of throughput and sensing error (total error) probability in the Rayleigh and Nakagami-m fading environments.

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Section: Related Workmentioning

confidence: 99%

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Kumar

Thakur

Pandit

et al. 2019

Int J Communication

View full text Add to dashboard Cite

show abstract

“…[11][12][13][14][15][16][17][18][19][20][21] In Gao et al, 11 joint optimization of number of secondary users (SUs), detector threshold, and sensing time is considered to maximize the EE. [11][12][13][14][15][16][17][18][19][20][21] In Gao et al, 11 joint optimization of number of secondary users (SUs), detector threshold, and sensing time is considered to maximize the EE.…”

Section: Related Workmentioning

confidence: 99%

“…[11][12][13][14][15][16][17][18][19][20][21] In Gao et al, 11 joint optimization of number of secondary users (SUs), detector threshold, and sensing time is considered to maximize the EE. In Hu et al, 12 spectrum efficiency (SE) along with EE is considered as performance metric. However, for AND fusion, detection probability is low compared with other fusion rules.…”

Section: Related Workmentioning

confidence: 99%

“…In Gao et al, 11 AND fusion rule is used to determine EE. In Hu et al, 12 the SE-EE trade-off for CSS is investigated and both SE and EE are optimized via joint optimization of sensing time and detector threshold. In Hu et al, 12 spectrum efficiency (SE) along with EE is considered as performance metric.…”

Section: Related Workmentioning

confidence: 99%

“…However, for AND fusion, detection probability is low compared with other fusion rules. However, the work in Hu et al 12 does not give the detailed explanation whether the optimal design parameters satisfy the detection accuracy and false alarm constraints. In Hu et al, 12 the SE-EE trade-off for CSS is investigated and both SE and EE are optimized via joint optimization of sensing time and detector threshold.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Joint sensing time and fusion rule threshold optimization for energy efficient CSS in cognitive radio sensor networks

Sharma

2018

Int J Communication

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Energy resources become precious when the secondary users (SUs) in cognitive radio (CR) network are battery operated, especially in cooperative spectrum sensing (CSS). So it becomes important to use their energy efficiently. In CSS, the number of cooperative users, fusion rule threshold, transmission power, and sensing time affects the energy efficiency (EE) of the CSS. In this paper, an iterative algorithm is proposed to determine joint optimal fusion rule threshold and sensing time that maximizes the EE of CSS. Results show that EE is maximum at optimum sensing duration τ s0 = 0.841 ms and fusion rule threshold k 0 = 4 at SNR = −18 dB. Maximum EE at optimal point is ξ max = 3.15 bits/Hz/J. KEYWORDS cognitive radio (CR), cooperative spectrum sensing (CSS), energy efficiency (EE), fusion rule (FR)

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Distributed Cognitive Radio Medium Access Control Protocol in Perfect and Imperfect Channel Sensing Scenarios

Pandit

Singh

2017

Spectrum Sharing in Cognitive Radio Networks

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On the Spectrum- and Energy-Efficiency Tradeoff in Cognitive Radio Networks

Cited by 77 publications

References 18 publications

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Joint sensing time and fusion rule threshold optimization for energy efficient CSS in cognitive radio sensor networks

Distributed Cognitive Radio Medium Access Control Protocol in Perfect and Imperfect Channel Sensing Scenarios

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