Performance Analysis of Decision/Data Fusion-Aided Cooperative Cognitive Radio Network Over Generalized Fading Channel

Balam, Suresh Kumar; Siddaiah, P.; Nallagonda, Srinivas

doi:10.1109/taes.2018.2884184

Cited by 11 publications

(5 citation statements)

References 28 publications

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“…So far, Spectrum sensing in vehicular environments have been investigated in some fundamental works [10][11][12][13][14][15][16][17][18][19][20][21]. The work in [10] is among the first to study the influence of mobility on spectrum sensing in a joint optimization framework for sensor cooperation and sensing scheduling.…”

Section: Related Workmentioning

confidence: 99%

“…This distribution function is then used in deducing the expression of false-alarm and detection probability using majority rule at the fusion center. In addition, the performance of cooperative spectrum sensing were studied over Nakagami-m Fading Channels [18,19] and generalized κ − µ fading [20,21]. For a more in-depth discussion of spectrum sensing in CVNs, the reader is referred directly to [22].…”

Section: Related Workmentioning

confidence: 99%

“…Meanwhile, the theoretical results here compared with the simulating results for both C 1 and C 3 , so that the effectiveness of the analysis is justified (relative error less than 5%). The figure indicates that the expression ( 19) and ( 12), (20) give the lower and upper bounds of the detection probability for ED-based spectrum sensing under time-correlated Rayleigh fading channels. In the following, we are going to focus attention on cooperative cases.…”

Section: Performance Evaluationmentioning

confidence: 99%

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Performance Analysis of Cooperative Sensing over Time-Correlated Rayleigh Channels in Vehicular Environments

Qian

2020

Electronics

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Spectrum starvation is a key challenge for wireless services and applications in vehicular networks with serious negative implications for traffic safety and transportation efficiency. As a promising solution, cognitive radio (CR) allows CR-enabled vehicles to access the spectrum holes of primary users (PUs) in an opportunistic manner, but requires a robust sensing mechanism to provide adequate protection for PUs. However, highly dynamic environments make spectrum sensing an increasingly difficult problem. For example, vehicular communications are subject to multipath fading due to vehicle mobility. In this paper, the wireless channels in vehicular environments are considered to be subject to time-correlated Rayleigh fading. To facilitate the analysis, temporal correlation could be classified into complete correlation, partial correlation and complete independence according to the degree of correlation. The performance of cooperative sensing scheme is investigated for soft fusion (SF) and hard fusion (HF) approaches. The simulation results are presented to verify our theoretical analysis for varying conditions and scenarios. The results indicate that the detecting performance could be importantly influenced by channel correlation, which can be improved by vehicles’ cooperation.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

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Performance Analysis of Cooperative Sensing over Time-Correlated Rayleigh Channels in Vehicular Environments

Qian

2020

Electronics

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“…With this, analysis of SDCSs under the influence of individual fading channels can be avoided. Performance analysis of CSS with decision/data fusion over κ − μ fading channel is discussed in [27] and performance of data fusion-aided CR network (CRN) over κ − μ and η − μ fading channels is discussed in [28]. The present work is an extension of [28].…”

Section: Background Workmentioning

confidence: 99%

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Nallagonda¹,

Kumar²,

Nallagonda³

2019

IET Communications

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“…In [47], by considering different channel and network characteristics, the miss detection probability and TEP are evaluated for the proposed CSS using both HDFR and SDFS schemes over AWGN/generalized k ‐ μ fading models. The analysis presented in [48] is restricted to AWGN and lognormal shadow fading channels only; it can be generalized over several fading channels (for instance, Rayleigh, Rician, and Nakagami‐

m,n

/ q etc).…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of hard‐decision and soft‐data aided cooperative spectrum sensing over Nakagami‐m fading channel

Godugu

Vappangi

2023

IET Communications

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The secondary users can opportunistically utilize the spectrum holes left by the licensed users (also called primary users [PUs]) with the help of cognitive radio (CR) technology. The cooperative spectrum sensing (CSS) is crucial for the implementation of CR algorithms in the next‐generation wireless networks, for the specific identification of spectral gaps of PUs under any fading/shadowing channel. Accurate spectrum sensing reveals that the CUs only provide data when the PUs report being idle. Yet, there is always a possibility that CU transmission will cause interference with PU communications, leading to inefficient spectrum use. So, this work explores the performance of a proposed CSS by considering such factors with the key objective of enhancing spectrum utilisation efficiency. This paper evaluates the role of the proposed CSS with a variety of hard decision fusion rules (HDFR) schemes as well as soft data fusion schemes (SDFS) methods. Toward this end, for the proposed system, closed‐form expressions for the evaluation of various performance metrics such as the false alarm, miss‐detection probabilities, total error probability (TEP), and throughput/energy efficiency are derived by taking into consideration the Nakagami‐m fading environment using different hard and soft algorithms and are validated by means of numerical simulations. Furthermore, by taking into account various network specifications, such as channel error probability (q), fading severity parameter (m), number of samples (M), number of CR nodes (N), average sensing (S) channel signal‐to‐noise ratio, and sensing threshold (λ), a performance evaluation between the SDFS and HDFR schemes has been carried out. Furthermore, using HDFR/SDFS schemes, analytical models are formulated for determining an optimal number of CR nodes (Nopt$N_{opt}$) and optimal threshold (λopt$\lambda _{opt}$) values for achieving the lowest TEP and highest energy efficiency.

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Performance Analysis of Decision/Data Fusion-Aided Cooperative Cognitive Radio Network Over Generalized Fading Channel

Cited by 11 publications

References 28 publications

Performance Analysis of Cooperative Sensing over Time-Correlated Rayleigh Channels in Vehicular Environments

Performance Analysis of Cooperative Sensing over Time-Correlated Rayleigh Channels in Vehicular Environments

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Performance evaluation of hard‐decision and soft‐data aided cooperative spectrum sensing over Nakagami‐m fading channel

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