Adaptive Double Threshold Based Spectrum Sensing to Overcome Sensing Failure in Presence of Noise Uncertainty

Mahendru, Garima; Shukla, Anil Kumar; Banerjee, Priya R.; Patnaik, L. M.

doi:10.1109/spin.2019.8711570

“…However, all these methods require extra implementation cost and increased hardware complexity. Our previous work in [39] aimed at introducing a novel mathematical model for energy detection-based sensing. It was re-modeling of the existing mathematical system to achieve desirable performance metrics without changing the sensing algorithm.…”

Section: Related Workunclassified

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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“…According to the proposed technique, the detection threshold is switched between the two suggested thresholds in accordance with the variation in noise uncertainty when the detection enters the region of confusion. The concept of threshold wall as proposed in Section 3A and as proposed in [31,39] is taken as the basis for formulation of mathematical expressions of double dynamic thresholds and justified below:…”

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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“…The decision threshold can adapt to the noise fluctuating without any knowledge of noise power or signal power [32]. While in [33] showed that performance can be significantly improved by using an adaptive double-threshold spectrum sensing scheme. Table 1 illustrates a brief comparison between the main noise uncertainty mitigation techniques in CR networks as mentioned above.…”

Section: Noise Uncertainty In Cognitive Radio Systemsmentioning

confidence: 99%

“…hence, the weighting factor for each PU sample is considered as a constant amplitude [34]. However, in a real scenario, the PU samples may occur at any time during the sensing block led to degradation in overall detection performance [32], [33]. Figure 4 illustrates the building blocks of weighted ED, the received PU samples are squared after passing the analog to digital converter (ADC) block and then multiplied by certain weights according to real PU probability occurrence and finally integrated to make a decision.…”

Section: Unequal Scale Sampling Criteria and Weighted Energy Detementioning

confidence: 99%

Double Threshold Weighted Energy Detection for Asynchronous PU Activities in the Presence of Noise Uncertainty

Hassan

¹

,

Eltholth

²

,

Ammar

³

2020

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Cognitive Heterogeneous Network (CHN) is a network that provides heterogeneous services on a cognitive radio basis. The existence of such heterogeneous services introduces a syndrome of concurrent problems. Handling each problem separately may result in more consequences. This paper aims to mitigate the combined effects of noise uncertainty and asynchronous primary user occurrence within the sensing interval of the secondary user in cognitive heterogeneous network. The paper proposes a double threshold energy detection method based on unequal scale sampling criteria. An analytic formula is deduced for both thresholds employing the power scaling criteria. Simulation results show a complete agreement with the performance expectations in terms of increased probability of detection while keeping the false alarm probability within the required limits, which is guaranteed by plotting the ROC curves. Moreover, an optimal threshold is formulated to minimize the overall detection errors, that led to further enhancements in performance as illustrated also via simulations.

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Adaptive Double Threshold Based Spectrum Sensing to Overcome Sensing Failure in Presence of Noise Uncertainty

Cited by 15 publications

References 15 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

Double Threshold Weighted Energy Detection for Asynchronous PU Activities in the Presence of Noise Uncertainty

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