A review of the noise uncertainty impact on energy detection with different OFDM system designs

Lörincz, Josip; Ramljak, Ivana; Begušić, Dinko

doi:10.1016/j.comcom.2019.09.013

Cited by 18 publications

(20 citation statements)

References 78 publications

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“…In addition, in Ref. [ 36 ] ( Table 1 ), the analyses of the impact of NU on ED performed without DT adaptations for diverse OFDM based systems were shown. The results obtained indicated that the ED performance in different OFDM systems was significantly impaired by the NU.…”

Section: Related Work On the Ss Of Ofdm Signalsmentioning

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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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%

“…The impact on the ED sensing performance of NU and DT as both separate and joint factors was analysed in Ref. [ 36 ]. Besides their ratio, it was concluded that the absolute values of DT and NU have a significant impact on sensing performance.…”

Section: Future Challenges For the Enhancement Of Ed Limitationsmentioning

confidence: 99%

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

Lörincz

Ramljak²,

Begušić

2021

Sensors

Self Cite

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“…Despite its aforementioned advantages, energy detection has several drawbacks, including the degradation of detection accuracy as a result of noise uncertainty (NU). The latter refers to the noise power fluctuations with time caused by the effects of various factors such as thermal noise, filtering effects, radiofrequency circuits, and interference from other signals [65]. Authors of [65] analyzed the impact of NU on energy detection performance using different OFDM system designs.…”

Section: ) Narrowband Sensing Techniquesmentioning

confidence: 99%

“…The latter refers to the noise power fluctuations with time caused by the effects of various factors such as thermal noise, filtering effects, radiofrequency circuits, and interference from other signals [65]. Authors of [65] analyzed the impact of NU on energy detection performance using different OFDM system designs. The results of their analyses show that, for all OFDM system designs, the probability of detection is higher for signals, with lower NU and higher SNR, which are transmitted at higher PU transmit power and detected with a higher number of samples.…”

Section: ) Narrowband Sensing Techniquesmentioning

confidence: 99%

A Review on SDR, Spectrum Sensing, and CR-based IoT in Cognitive Radio Networks

Kassri¹,

En‐Nouaary²,

Bah³

et al. 2021

IJACSA

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The inherent scarcity of frequency spectrum, along with the fixed spectrum allocation adopted policy, has led to a dire shortage of this indispensable resource. Furthermore, with the tremendous growth of wireless applications, this problem is intensified as the unlicensed frequency spectrum becomes overcrowded and unable to meet the requirement of emerging radio devices operating at higher data rates. Additionally, the already assigned spectrum is underutilized. That has prompted researchers to look for a way to address spectrum scarcity and enable efficient use of the available spectrum. In this context, Cognitive Radio (CR) technology has been proposed as a potential means to overcome this issue by introducing opportunistic usage to less congested portions of the licensed spectrum. In addition to outlining the fundamentals of Cognitive Radio, including Dynamic Spectrum Access (DSA) paradigms and CR functions, this paper has a three-fold objective: first, providing an overview of Software Defined Radio (SDR), in which the architecture, benefits, and ongoing challenges of SDR are presented; second, giving an extensive review of spectrum sensing, covering sensing types, narrowband and wideband sensing schemes with their pros and cons, Machine Learningbased sensing, and open issues that need to be further addressed in this field; third, exploring the use of Cognitive Radio in the Internet of Things (IoT) while highlighting the crucial contribution of CR in enabling IoT. This Review is elaborated in an informative fashion to help new researchers entering the area of Cognitive Radio Networks (CRN) to easily get involved.

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“…The impact of noise variability on the energy detection performance of signals transmitted by OFDM is reviewed in [23]. In addition, extensive analysis was carried out using simulations of the energy detection method for three different OFDM systems.…”

Section: Literature Reviewmentioning

confidence: 99%

5G cognitive radio system design with new algorithm asynchronous spectrum sensing

2021

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Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

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A review of the noise uncertainty impact on energy detection with different OFDM system designs

Cited by 18 publications

References 78 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

A Review on SDR, Spectrum Sensing, and CR-based IoT in Cognitive Radio Networks

5G cognitive radio system design with new algorithm asynchronous spectrum sensing

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