Unified Analysis of Cooperative Spectrum Sensing Over Composite and Generalized Fading Channels

Hammadi, Ahmed Al; Alhussein, Omar; Sofotasios, Paschalis C.; Muhaidat, Sami; Al‐Qutayri, Mahmoud; Al-Araji, Saleh R.; Karagiannidis, George K.; Liang, Jie

doi:10.1109/tvt.2015.2487320

Cited by 38 publications

(32 citation statements)

References 45 publications

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“…When considering specific imperfect reporting channel, Lee analyzed the T-CSS performance over Rayleigh reporting channel [31], while several works studied spectrum sensing and T-CSS under generalized or composite fading conditions [32]- [37]. For example, da Costa et al [32] investigated the outage probability performance of a dual-hop decode-and-forward T-CSS scheme under the presence of Nakagami-m fading and interference conditions as well as the effects of fading severity, SU relay placement, the number of PU and SU nodes on the endto-end T-CSS performance.…”

Section: Related Workmentioning

confidence: 99%

“…Likewise, Sofotasios et al [35] investigated the performance of ED-based T-CSS under different diversity receptions in the presence of both generalized and extreme multipath fading conditions, which are typically encountered in enclosed areas such as malls and tunnels. More recently, the performance of T-CSS with multi-antenna nodes over generalized and composite fading channels was analyzed in [36], [37] with the aid of the generic and semi-analytic mixture Gamma (MG) distribution. Moreover, the optimal fusion rule and the number of antennas that minimize the total error rate in the square-law selection (SLS) framework were also analyzed.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the optimal fusion rule and the number of antennas that minimize the total error rate in the square-law selection (SLS) framework were also analyzed. Yet, accurate optimization of the detection threshold was not addressed in [36], [37]. It is also noted that Li et al [38] proposed interesting tradeoffs in T-CSS, namely: i) the impact of the number of sensing users on spectrum utilization and secondary throughput; and ii) the relationship between the detection threshold, detection performance and secondary throughput.…”

Section: Related Workmentioning

confidence: 99%

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Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Alhussein

Sofotasios

et al. 2020

IEEE Trans. Sustain. Comput.

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The present contribution proposes a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach in a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. In this context, exact analytic expressions are first derived for the corresponding probability of detection, probability of false alarm and secondary throughput, assuming that each secondary user (SU) sends its detection outcome to a fusion center only when it has detected a primary signal. Capitalizing on the findings of the analysis, the effects of critical measures, such as the detection threshold, the number of SUs and the number of employed antennas, on the overall system performance are also quantified. In addition, the optimal detection threshold for each antenna based on the Neyman-Pearson criterion is derived and useful insights are developed on how to maximize the system throughput with a reduced number of SUs. It is shown that the C-CSS approach provides two distinct benefits compared with the conventional sensing approach, i.e., without censoring: i) the sensing tail problem, which exists in imperfect sensing environments, can be mitigated; ii) less SUs are ultimately required to obtain higher secondary throughput, rendering the system more sustainable.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Alhussein

Sofotasios

et al. 2020

IEEE Trans. Sustain. Comput.

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“…For MRC, at the receiving end the total output SNR will be combined by all diversity branches and the collected data is added up to the reserved energy detector. Although MRC requires prior channel knowledge of the signal, in practice it estimates the upper bound on the performance of ED [11]. The total instantaneous SNR of MRC is given by, (39) where L denotes the number of antennas for each SU, the SNR of i-th receiver branch is defined as γ i .…”

Section: Upper Bound Of Detection Performance With Mrcmentioning

confidence: 99%

Cooperative spectrum sensing over generalized fading channels based on energy detection

Huang

Yuan

2018

China Commun.

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This paper analyzes the unified performance of energy detection (ED) of spectrum sensing (SS) over generalized fading channels in cognitive radio (CR) networks. The detective performance of SS schemes will be obviously affected by fading channel among communication nodes, and ED has the advantages of fast implementation, no requirement of priori received information and low complexity, so it is meaningful to investigate ED that is performed over fading channels such as Nakagami-m channel and Rice channel, or generalized fading channels such as κ-μ fading distribution and η-μ fading distribution. The α-κ-μ fading distribution is a generalized fading model that represents the nonlinear and small-scale variation of fading channels. The probability density function (p.d.f.) of instantaneous signal-to-ratio (SNR) of α-κ-μ distribution is derived from the p.d.f. of envelope to evaluate energy efficiency for sensing systems. Next, the detection probability of detective model with Marcum-Q function has been derived and the close-form expressions with moment generating function (MGF) method are deduced to achieve SS. Furthermore, novel and exact closed-form analytic expressions for average area under the receiver operating characteristics curve ( AUC ) also have been deduced to analyze the performance characteristics of ED over α-κ-μ fading channels. Besides, cooperative spectrum sensing (CSS) with diversity reception has been applied to improve the detection accuracy and mitigate the shadowed fading features with OR-rule. At last, the results show that the detection capacity can be evidently affected by α-κ-μ fading conditions, but appropriate channel parameters will improve sensing performance. On the other hand, the established ED-fading pattern is approved by simulations under diversity combination with CSS at the receiving end and it can significantly enhance the detection performance of proposed algorithms.

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“…A probabilidade de detecção e de falso alarme para SLC é apresentado nas expressões (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) e (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14) respectivamente. (3 − 24) As probabilidades de detecção e falso alarme para MRC são apresentadas nas expressões (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17) e (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)…”

Section: Selection Combining (Sc)unclassified

Análise Do Desempenho De Regras De Fusão Para Sensoriamento Cooperativo Do Espectro

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Unified Analysis of Cooperative Spectrum Sensing Over Composite and Generalized Fading Channels

Cited by 38 publications

References 45 publications

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

Cooperative spectrum sensing over generalized fading channels based on energy detection

Análise Do Desempenho De Regras De Fusão Para Sensoriamento Cooperativo Do Espectro

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