Phase Type Viewpoint Spectrum Sensing for Cognitive Radios

Frequenz ◽  
2015 ◽  
Vol 69 (9-10) ◽  
Author(s):  
Mohammadreza Amini ◽  
Asra Mirzavandi
Keyword(s):  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Type Model ◽  
Computationally Efficient ◽  
Channel State ◽  
Secondary Users ◽  
Trade Off ◽  
Phase Type ◽  
Error Probabilities ◽  
Sensing Time

AbstractSpectrum sensing is one of the main functionalities of cognitive radios to find transmission opportunities without interfering primary users’ transmission. The more accurate and efficient the spectrum sensing is, the higher the throughput of secondary and primary networks is achieved. This paper presents adaptive spectrum sensing method based on phase type modelling that is computationally efficient for secondary users to conclude about the channel state (idle or busy) under collision constraint. The parameters of phase type model can be adjusted based on the desired operating point of the receiver sensor in its ROC curve. The presented approach can run a simple trade off between sensing time and the two error probabilities of the receiver sensor i.e. False alarm and Miss-detection, the trade off that cannot be easily achieved in other sensing method.

scholarly journals Discrete Markov Chain Based Spectrum Sensing for Cognitive Radio

2015 ◽  
Vol 5 (2) ◽  
pp. 297
Author(s):  
Mohammadreza Amini ◽  
Asra Mirzavandi ◽  
Mosrafa Rezaei
Keyword(s):  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Type Model ◽  
Channel State ◽  
Secondary Users ◽  
Primary Network ◽  
Phase Type ◽  
Error Probabilities ◽  
Discrete Markov Chain ◽  
Sensing Time

Spectrum sensing is one of the functionalities of cognitive radios to exploit spectrum holes without interrupting primary users transmission. The more efficient of the spectrum sensing, the highest the throughput of secondary and primary network. This paper presents spectrum sensing method based on phase type modelling that is simple to do for secondary users to conclude about the channel state (idle or busy) under collision constraint. The parameters of phase type model can be adjusted based on desired operating point of the receiver sensor in its ROC curve. The presented approach can run a trade off between sensing time and the two error probabilities of sensor false alarm and miss-detection.

Phase-Type Model Spectrum Sensing for Cognitive Radios

2015 ◽  
Vol 61 (5) ◽  
pp. 510-516
Author(s):  
Mohammadreza Amini ◽  
Asra Mirzavandi
Keyword(s):  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Type Model ◽  
Model Spectrum ◽  
Phase Type

scholarly journals Wideband Spectrum Sensing Based on Reconfigurable Filter Bank in Cognitive Radio

2019 ◽  
Vol 11 (11) ◽  
pp. 244
Author(s):  
Wang ◽  
Wu ◽  
Yao ◽  
Qin
Keyword(s):  
Fourier Transform ◽  
Spectrum Sensing ◽  
Filter Bank ◽  
Energy Detection ◽  
High Rate ◽  
Idle State ◽  
Trade Off ◽  
Wideband Spectrum Sensing ◽  
Wideband Signals ◽  
Sensing Time

In order to ease the conflict between the bandwidth demand of high-rate wireless communication and the shortage of spectrum resources, a wideband spectrum sensing method based on reconfigurable filter bank (RFB) with adjustable resolution is presented. The wideband signals are uniformly divided into multi-narrowband signals by RFB, which is designed by polyphase uniform Discrete Fourier Transform (DFT) modulation, and each sub-band is sensed by energy detection. According to the idle proportion of detected sub-bands, the number of RFB sub-bands is reset in next spectrum-sensing time. By simulating with collected wideband dataset, the influence of filter bank sub-bands number and idle state proportion on the sensing results is analyzed, and then on the basis of the trade-off between spectrum-sensing resolution and computational complexity, the optimal sub-bands number of filter bank is selected, so as to improve the detection performance and save resources.

scholarly journals Utilization of idle time slot in spectrum sensing under noise uncertainty

2022 ◽  
Vol 12 (1) ◽  
pp. 431
Author(s):  
Iyad Khalil Tumar ◽  
Adnan Mohammad Arar ◽  
Ayman Abd El Saleh
Keyword(s):  
Spectrum Sensing ◽  
Time Slot ◽  
Signal To Noise Ratio ◽  
Primary User ◽  
Idle Time ◽  
Detection Accuracy ◽  
Secondary Users ◽  
Noise Uncertainty ◽  
Received Power ◽  
Sensing Time

<p>Spectrum sensing in cognitive radio (CR) is a critical process as it directly influences the accuracy of detection. Noise uncertainty affects the reliability of detecting vacant holes in the spectrum, thus limiting the access of that spectrum by secondary users (SUs). In such uncertain environment; SUs sense the received power of a primary user (PU) independently with different measures of signal-to-noise ratio (SNR). Long sensing time serves in mitigating the effect of noise uncertainty, but on the cost of throughput performance of CR system. In this paper, the scheme of an asynchronous and crossed sensing-reporting is presented. The scheme reduces energy consumption during sensing process without affecting the detection accuracy. Exploiting the included idle time (𝑇𝑖) in sensing time slot; each SU collects power samples with higher SNR directly performs the reporting process to a fusion center (FC) consecutively. The FC terminates the sensing and reporting processes at a specific sensing time that corresponds to the lowest SNR (𝑆𝑁𝑅𝑤𝑎𝑙𝑙). Furthermore, this integrated scheme aims at optimizing the total frame duration (𝑇𝑓). Mathematical expressions of the scheme are obtained. Analytical results show the efficiency of the scheme in terms of energy saving and throughput increment under noise uncerainty.</p>

scholarly journals Sensing and Sharing Schemes for Spectral Efficiency of Cognitive Radios

2018 ◽  
Vol 8 (5) ◽  
pp. 2934
Author(s):  
M. K. Kaushik ◽  
Y. Yoganandam ◽  
SK Sahoo
Keyword(s):  
Spectrum Sensing ◽  
Spectral Efficiency ◽  
Spectrum Sharing ◽  
Cognitive Radios ◽  
Packet Delay ◽  
Primary User ◽  
Secondary User ◽  
False Alarms ◽  
Data Traffic ◽  
Secondary Users

<span>Increase in data traffic, number of users and their requirements laid to a necessity of more bandwidth. Cognitive radio is one of the emerging technology which addresses the spectrum scarcity issue. In this work we study the advantage of having collaboration between cognitive enabled small cell network and primary macrocell. Different from the existing works at spectrum sensing stage we are applying enhanced spectrum sensing to avoid probability of false alarms and missed detections which has impact on spectral efficiency. Later power control optimization for secondary users known as Hybrid spectrum sharing is used for further improvement of spectral efficiency. Furthermore, the failed packets of Primary users are taken care by high ranked relays which in turn decreases the average Primary user packet delay by 20% when compared between assisted Secondary user method and non-assisted Secondary user method. </span>

A Reliable Cooperative Spectrum Sensing Strategy for Cognitive Radios

2013 ◽  
Vol 347-350 ◽  
pp. 1773-1779
Author(s):  
Shou Tao Lv ◽  
Ze Yang Dai ◽  
Jian Liu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Cognitive Radios ◽  
Radio Networks ◽  
Secondary Source ◽  
Secondary Users ◽  
Primary Users ◽  
The Third ◽  
Detection Probabilities

In cognitive radio networks (CRNs), the secondary users (SUs) need to continuously detect whether the primary users (PUs) occupy the spectrum. In order to improve the spectrum sensing accuracy, a novel reliable cooperative spectrum sensing strategy based on the detection results relayed twice from the secondary relays (SRs) to the secondary source (SS), referred to as CSS-DRT, is proposed in this paper. In this scheme, the spectrum sensing slot is divided into four equal sub-slots. In the first and third sub-slots, the SS and SRs detect the PU by themselves. Then, in the second sub-slot, if the SRs that detect the PU during the first sub-slot are more than or equal to a prespecified quantity, the corresponding SRs will send their flag signals (FSs) to the SS while the others keep quiet, where the FS is narrowband and indicates that the PU is present. Otherwise, if the SRs that detect the PU during the first sub-slot are less than the prespecified quantity, all the SRs will keep quiet in the second sub-slot. Meanwhile, the SS detects the PU based on the received signals from the PU and SRs. And, the SS uses the same method as employed in the second sub-slot to detect the PU in the last sub-slot wherein the SRs send their FSs based on their detections made during the third sub-slot. Finally, an ultimate decision is made by the OR ruler based on the SS detection results obtained during the spectrum sensing slot. Besides, we derive the closed-form expressions of the false alarm and detection probabilities for the proposed CSS-DRT scheme. In the end, simulation and numerical results show that our proposed scheme can achieve better performance than the non-cooperative method and an existing cooperative spectrum sensing method.

scholarly journals Energy-Efficient Cluster-Based Cooperative Spectrum Sensing in a Multiple Antenna Cognitive Radio Network

2021 ◽  
pp. 176-185
Author(s):  
Samson I. Ojo ◽  
◽  
Zachaeus K. Adeyemo ◽  
Damilare O. Akande ◽  
Ayobami O. Fawole
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Cluster Head ◽  
Fusion Rule ◽  
Probability Of Detection ◽  
Multiple Antenna ◽  
Secondary Users ◽  
Sensing Time

Spectrum Hole Detection (SHD) is a major operation in a Cognitive Radio (CR) network to identify empty spectrum for maximum utilization. However, SHD is often affected by multipath effects resulting in interference. The existing techniques used to address these problems are faced by poor detection rate, long sensing time and bandwidth inefficiency. Hence, this paper proposes a cluster-based Energy-Efficient Multiple Antenna Cooperative Spectrum Sensing (EEMACSS) for SHD in CR networks using Energy Detector (ED) with a modified combiner. Multiple secondary users are used to carry out local sensing using ED in multiple antenna configurations. The local sensing results are combined at the cluster head using majority fusion rule to determine the sensing results at each cluster. The sensing results from individual cluster are combined to determine the global sensing result using OR fusion rule. The proposed EEMACSS is evaluated using Probability of Detection (PD), Sensing Time (ST) and Spectral Efficiency (SE) by comparing with existing techniques. The results reveal that the proposed technique shows better performance.

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