Primary user localisation and uplink resource allocation in orthogonal frequency division multiple access cognitive radio systems

2015 ◽  
Vol 9 (8) ◽  
pp. 1131-1137 ◽  
Author(s):  
Haewoon Nam ◽  
Mand Ben-Ghorbel ◽  
Nasir Saeed ◽  
Mohamed Slim Alouini
Frequenz ◽  
2016 ◽  
Vol 70 (5-6) ◽  
Author(s):  
Ibrahim Atef ◽  
Ashraf Eltholth ◽  
M. S. El-Soudani

AbstractIn cognitive radio systems, the random nature of primary users’ activities heavily influences the performance of spectrum sensing techniques. Considering both of the primary user random arrival and departure in one model is essential for mitigating the performance degradation in spectrum sensing. In this paper, we apply the probability based weighting energy detector (ED) to overcome the effect of random arrival and departure of primary user (PU), on a single carrier-frequency division multiple access (SC-FDMA) signal used in LTE uplink physical channel. Then compare the performance of weighted ED to the second order Cyclostationarity detector with/without the random arrival and departure of primary user signal during the secondary user’s sensing period. The simulation shows that the weighting ED approaches the performance of Cyclostationarity detector in the normal case, where there are no random activities of primary user signals during the secondary user’s sensing period, with less computational complexity. Moreover, the weighted ED outperforms the Cyclostationarity detector in the case of random arrival and departure of PU.


2009 ◽  
Vol 2 (1-2) ◽  
pp. 116-126 ◽  
Author(s):  
Joseph Wynn Mwangoka ◽  
Khaled Ben Letaief ◽  
Zhigang Cao

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 631
Author(s):  
Josip Lorincz ◽  
Ivana Ramljak ◽  
Dinko Begušić

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.


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