Misdetection Probability Analyses of OFDM Signals in Energy Detection Cognitive Radio Systems

Lörincz, Josip; Begušić, Dinko; Ramljak, Ivana

doi:10.23919/softcom.2018.8555811

Cited by 7 publications

(8 citation statements)

References 27 publications

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“…The SS of OFDM signals transmitted according to the described transmission process has been analysed in different studies in the literature [ 10 , 11 , 19 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. In Table 1 , an overview of ED methods and their corresponding merits are presented.…”

Section: Related Work On the Ss Of Ofdm Signalsmentioning

confidence: 99%

“…In Ref. [ 32 ], we showed the results related to the influence of NU on the energy misdetection probability of OFDM based systems in an MA system design. In addition, in Ref.…”

Section: Related Work On the Ss Of Ofdm Signalsmentioning

confidence: 99%

“…The ED approach impacted by NU and without DT adaptation [12,25,26,28,[30][31][32]36] Analyses of ED performance taking into account the impact of the NU variations Reduced detection probability of ED method due to impact of NU variation caused by thermal noise and interference from neighbor communication systems…”

Section: Approach Analysed In the Literature Description Of The Analysed Approach The Merit Of The Analysed Approachmentioning

confidence: 99%

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A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Lörincz

Ramljak²,

Begušić

2021

Sensors

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Cognitive radio (CR), as a concept based on the ability to detect and share the unutilised spectrum, has been envisioned as a promising candidate to improve the efficiency of frequency spectrum assignments. For the realisation of the CR concept, energy detection (ED), as one of the available spectrum sensing methods, is broadly considered because of its low computational complexity and implementation costs. Due to the vast usage of the orthogonal frequency division multiplexing (OFDM) technique in contemporary communication systems, the ED of OFDM signals in the CR networks has become important for practical realisation. Since the ED accuracy of the OFDM signals can be improved by the sensing threshold adaptation, this paper surveys the impact of noise variations and dynamic threshold (DT) adaptation on the ED performance of OFDM signals. Analyses were performed by the simulation of the ED related to OFDM signals transmitted in the margin or rate adaptive and combined margin and rate adaptive OFDM systems. The results obtained through extensive simulations provide fundamental insights into how different factors, including the transmission power, the signal to noise ratio, the false alarm probability and the sample quantity, affect the ED efficiency. Comprehensive analyses of the obtained results indicate the main ED weaknesses and how the appropriate selection of analysed factors can enhance the ED processes for different OFDM systems. The observed ED weaknesses were further thoroughly surveyed, and the open issues and challenges related to the enhancement of the main ED limitations have been elaborated. The presented survey results can serve as a basis for the improvement of a broadly accepted ED method in CR networks.

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Section: Related Work On the Ss Of Ofdm Signalsmentioning

confidence: 99%

“…In Ref. [ 32 ], we showed the results related to the influence of NU on the energy misdetection probability of OFDM based systems in an MA system design. In addition, in Ref.…”

Section: Related Work On the Ss Of Ofdm Signalsmentioning

confidence: 99%

Section: Approach Analysed In the Literature Description Of The Analysed Approach The Merit Of The Analysed Approachmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Lörincz

Ramljak²,

Begušić

2021

Sensors

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“…In [ 30 , 31 ], we analyze the performance of the ED process impacted by NU. The analysis was performed for the signals transmitted in the SISO-OFDM system based on rate-adaptive, margin (modulation)-adaptive and combined rate- and margin-adaptive system (transmission) designs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although previous research presented in [ 10 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ] considers the ED process in MIMO transmission systems, an algorithm that enables the simulation analysis of the ED performance in MIMO-OFDM systems based on the SLC method is still missing. According to our knowledge, this is the first paper that deals with an algorithm which enables such analyses through ROC curves developed for the different operating parameters of the analyzed MIMO-OFDM systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

Lörincz

Ramljak

Begušić

2021

Sensors

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Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.

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Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks

et al. 2021

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We address the problem of spectrum sensing in decentralized cognitive radio networks using a parametric machine learning method. In particular, to mitigate sensing performance degradation due to the mobility of the secondary users (SUs) in the presence of scatterers, we propose and investigate a classifier that uses a pilot based second order Kalman filter tracker for estimating the slowly varying channel gain between the primary user (PU) transmitter and the mobile SUs. Using the energy measurements at SU terminals as feature vectors, the algorithm is initialized by a K-means clustering algorithm with two centroids corresponding to the active and inactive status of PU transmitter. Under mobility, the centroid corresponding to the active PU status is adapted according to the estimates of the channels given by the Kalman filter and an adaptive K-means clustering technique is used to make classification decisions on the PU activity. Furthermore, to address the possibility that the SU receiver might experience location dependent co-channel interference, we have proposed a quadratic polynomial regression algorithm for estimating the noise plus interference power in the presence of mobility which can be used for adapting the centroid corresponding to inactive PU status. Simulation results demonstrate the efficacy of the proposed algorithm.

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Misdetection Probability Analyses of OFDM Signals in Energy Detection Cognitive Radio Systems

Cited by 7 publications

References 27 publications

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks

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