An Improved Energy Detector for Mobile Cognitive Users Over Generalized Fading Channels

Gahane, Lokesh; Sharma, Prabhat Kumar; Varshney, Neeraj; Tsiftsis, Theodoros A.; Kumar, Preetam

doi:10.1109/tcomm.2017.2754250

Cited by 53 publications

(20 citation statements)

References 45 publications

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“…The energy-detection based spectrum sensing technique is applied to the NN prediction due to its simplicity and ability to identify spectrum white spaces without requiring any a priori information of PU's signal pattern [17], [18]. The sensing result contains two states: "1" is for busy; "-1" is for idle.…”

Section: A Energy-detection Based Sensingmentioning

confidence: 99%

A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

Zhang

Hou

Towhidlou

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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We propose a neural network (NN) predictor and an adaptive mode selection scheme for the purpose of both improving secondary user's (SU's) throughput and reducing collision probability to the primary user (PU) in full-duplex (FD) cognitive networks. SUs can adaptively switch between FD transmissionand-reception (TR) and transmission-and-sensing (TS) modes based on the NN prediction results for each transmission duration. The prediction performance is then analysed in terms of prediction error probability. We also compare the performance of our proposed scheme with conventional TR and TS modes in terms of SUs average throughput and collision probability, respectively. Simulation results show that our proposed scheme achieves even better SUs average throughput compared with TR mode. Meanwhile, the collision probability can be reduced close to the level of TS mode.

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Section: A Energy-detection Based Sensingmentioning

confidence: 99%

A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

Zhang

Hou

Towhidlou

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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“…The IED demonstrated enhanced performance in comparison with the conventional ED [2]- [4]. Gamma function approximations were used to derive a distribution of the IED test statistics by matching the values of the mean and variance for the H 0 and H 1 test statistics in Gaussian noise [2].…”

Section: A Technical Literature Reviewmentioning

confidence: 99%

“…Gamma function approximations were used to derive a distribution of the IED test statistics by matching the values of the mean and variance for the H 0 and H 1 test statistics in Gaussian noise [2]. Gahane et al [4] have applied the IED to mobile cogni-tive users in cooperative cognitive networks over generalized Nakagami-m, Nakagami-q, κ − µ, and ν − µ fading channels, where the receiver operating characteristic (ROC) curves and area under the ROC curves (AUC) were studied.…”

Section: A Technical Literature Reviewmentioning

confidence: 99%

Performance Analysis of Improved Energy Detector With Hardware Impairments for Accurate Spectrum Sensing

2019

Self Cite

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The impact of transceiver hardware impairments on the accuracy of spectrum sensing cannot be ignored in low-cost and high data rate cognitive radio systems. Nevertheless, ideal hardware for spectrum sensing is widely assumed in the technical literature. This paper presents a novel method for evaluating the improved energy detector (IED) statistics using α-µ distribution over additive white Gaussian noise (AWGN) and Nakagami-m fading channel by considering transceiver hardware imperfections. Moreover, the performance of the IED over AWGN channel is highlighted by the area under the receiver operating curve. Furthermore, the average probability of detection is evaluated for both fading and non-fading environments. An asymptotic analysis studies detection probability over fading channels at a low average signal-to-noiseratio region. Moreover, p-order law combining and p-order law selecting diversity techniques are proposed to increase the performance of the detector. Our simulation results demonstrate that the diversity techniques significantly improve the detector performance. INDEX TERMS Area under the ROC curve (AUC), α-µ distribution, false alarm probability, improved energy detector, Nakagami-m fading channel, probability of detection, receiver operating characteristic (ROC) curve, transceiver hardware impairments.

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“…An IED scheme increases an amplitude of received signal sample to arbitrary power of the received signal ( p ) and produces the test statistics about the PU . In , authors have discussed the performance analysis of IED scheme in CR network.…”

Section: Introductionmentioning

confidence: 99%

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

Ranjeeth

Anuradha

Nallagonda³

2020

Int J Communication

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Summary The proposed cooperative spectrum sensing (CSS) network is equipped with multiple antennas and an improved energy detector (IED) scheme at each cognitive radio (CR). Each CR in the network receives the information about the primary user (PU) in the form of binary decisions at multiple antennas. Diversity technique called selection combining (SC) scheme is used at multiple antennas to select the maximum value of sensing information present at multiple antennas. Finally, sensing information will be passed to the fusion center (FC) through reporting channel, and the final decision about PU is made at FC using fusion rules. Initially, we have derived the novel missed detection probability expressions for AWGN channel, Rayleigh, and Rician fading environments. Later, the closed form of optimized expressions for proposed CSS network parameters are derived to achieve an optimal performance. The closed form of optimized expressions such as number of CR users (Nopt), normalize threshold value (λn,opt), and an arbitrary power of the received signal (popt) are derived under various fading environments. The performance is evaluated using complementary receiver operating characteristics (CROC) and total error rate curves. The MATLAB‐based simulations are evaluated with the strong support of theoretical expressions. Finally, various simulation parameters such as sensing channel SNR, the error rate in reporting channel, threshold value, and number of antennas at each CR are considered in the simulation to show the effect on the performance of proposed CSS network.

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An Improved Energy Detector for Mobile Cognitive Users Over Generalized Fading Channels

Cited by 53 publications

References 45 publications

A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

A Neural Network Prediction-Based Adaptive Mode Selection Scheme in Full-Duplex Cognitive Networks

Performance Analysis of Improved Energy Detector With Hardware Impairments for Accurate Spectrum Sensing

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

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