Robust Performance of Spectrum Sensing in Cognitive Radio Networks

Author(s):  
Shimin Gong ◽  
Ping Wang ◽  
Jianwei Huang

Harmonic coexistence of cognitive radio systems and licensed systems requires the secondary users to have the capability of sensing and keeping track of primary users’ transmissions. While existing spectrum sensing methods usually assume known distributions of the primary signals, such an assumption is often not true in practice. As a result, applying existing sensing methods will often lead to unreliable detection performance in practical networks. In this chapter, the authors try to investigate the sensing performance under the distribution uncertainty of primary signals. They first investigate the performance bounds for single user detection with unknown distribution, and provide an analytical expression for the lower bound of detection probability. Moreover, they bring the distribution uncertainty into multi-user cooperative sensing. The authors formulate the optimal sensing design as a robust optimization problem, and propose an iterative algorithm to determine the optimal decision threshold for each user. Extensive simulations demonstrate the effectiveness of the proposed algorithm.

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3614 ◽  
Author(s):  
Alexandru Martian ◽  
Mahmood Jalal Ahmad Al Sammarraie ◽  
Călin Vlădeanu ◽  
Dimitrie C. Popescu

Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one iteration. The proposed algorithm is analyzed and illustrated with numerical results obtained from simulations that closely match the theoretical results and show that it outperforms the conventional ED (CED) algorithm for spectrum sensing.


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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