Double threshold feature detector for cooperative Spectrum Sensing in Cognitive Radio Networks

Khan, Imtiyaz; Singh, Poonam

doi:10.1109/indicon.2014.7030573

“…Over two decades, researchers worldwide explored upon various methods for spectrum sensing. Based on the literature survey on spectrum sensing various methods like: Energy detection (ED) [8][9][10][11]; Cyclo-stationary feature detection [12][13][14]; Matched filter detection [15,16]; Statistical covariance-based detection [17,18]; Cooperative sensing [19,20]; compressed sensing [21][22][23] were proposed to examine the spectrum occupancy under different scenarios. Considering the research on spectrum sensing methods; energy detection draws the attention of the researchers for its lesser computational and operational complexity [24].…”

Section: Related Workunclassified

“…The basic concept of cyclo-stationary feature detection is extraction of statistical properties of the signal. In [14] OFDM modulation is considered due its popularity and the correlation structure of the signals with cyclic prefix. Table 1 represents the test statistic parameter used and decision threshold mathematical expressions for different detection techniques like Matched filter detection, cyclostationary feature detection, conventional energy detection with fixed threshold, existing double thresholds, available adaptive double thresholds, and the proposed energy detection with dynamic double thresholds.…”

Section: (D) Dynamic Double Thresholdunclassified

A Novel Double Threshold-Based Spectrum Sensing Technique at Low SNR Under Noise Uncertainty for Cognitive Radio Systems

Mahendru

¹

2022

Wireless Pers Commun

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Cognitive Radio is a novel concept that has invoked a paradigm shift in wireless communication and promises to solve the problem of spectrum underutilization. Spectrum sensing plays a pivotal role in a cognitive radio system by detecting the vacant spectrum for establishing a communication link. For any spectrum sensing method, detection probability and error probability portray a significant part in quantifying the detection performance. At low SNR, it becomes cumbersome to differentiate noise and signal due to which sensing method loses robustness and reliability. In this paper, mathematical modeling and critical measurement of detection probabilities has been done for energy detection-based spectrum sensing at low SNR in uncertain noisy environment. A mathematical model has been proposed to compute double thresholds for reliable sensing when the observed energy is less than the uncertainty in the noise power. A novel parameter “Threshold Wall” has been formulated for optimum threshold selection to overcome sensing failure. Comparative simulation and analytical result measurements have been presented that reveals improved sensing performance.Please check inserted city is correct for affiliation 1.Noida, it is correct

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“…The basic concept of cyclo-stationary feature detection is extraction of statistical properties of the signal. In [14] OFDM modulation is considered due its popularity and the correlation structure of the signals with cyclic prefix. Table I represents the different sensing methods, the test statistic parameter used and decision threshold.…”

Section: B Dynamic Double Thresholdmentioning

confidence: 99%

A novel double threshold-based spectrum sensing technique at low SNR under noise uncertainty for Cognitive Radio Systems

Mahendru¹

2021

Preprint

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Cognitive Radio is a novel concept that has invoked a paradigm shift in wireless communication and promises to solve the problem of spectrum underutilization. Spectrum sensing plays a pivotal role in a cognitive radio system by detecting the vacant spectrum for establishing a communication link. For any spectrum sensing method, detection probability and error probability portray a significant part in quantifying the detection performance. At low SNR, it becomes cumbersome to differentiate noise and signal due to which sensing method loses robustness and reliability. In this paper, mathematical modeling and critical measurement of detection probabilities has been done for energy detection-based spectrum sensing at low SNR in uncertain noisy environment. A mathematical model has been proposed to compute double thresholds for reliable sensing when the observed energy is less than the uncertainty in the noise power. A novel parameter “Threshold Wall” has been formulated for optimum threshold selection to overcome sensing failure. Comparative simulation and analytical result measurements have been presented that reveals improved sensing performance.

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“…CSS techniques for orthogonal frequency division multiplex (OFDM) signals already exist in literature [21,22]. The underlying idea of this work is to develop an efficient CBCSS technique for the OFDM signal environment like 3GPP LTE and LTE-Advanced [23].…”

Section: Introductionmentioning

confidence: 99%

Cluster-Based Cooperative Subcarrier Sensing Using Antenna Diversity-Based Weighted Data Fusion

Mughal

¹

,

Hussain

²

,

Ghafoor

³

2015

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Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth over-head during CSS. Thus, cluster based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output (MIMO) CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single as well as multiple antenna CR systems. We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing (OFDM) signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network. We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme.Keywords Cognitive Radio · cooperative spectrum sensing · cluster based sensing · weighted data fusion.

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Double threshold feature detector for cooperative Spectrum Sensing in Cognitive Radio Networks

Cited by 4 publications

References 9 publications

A Novel Double Threshold-Based Spectrum Sensing Technique at Low SNR Under Noise Uncertainty for Cognitive Radio Systems

A Novel Double Threshold-Based Spectrum Sensing Technique at Low SNR Under Noise Uncertainty for Cognitive Radio Systems

A novel double threshold-based spectrum sensing technique at low SNR under noise uncertainty for Cognitive Radio Systems

Cluster-Based Cooperative Subcarrier Sensing Using Antenna Diversity-Based Weighted Data Fusion

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