No abstract

No abstract

Cognitive Radio (CR) is an intelligent technique for opportunistic access of idle resources. In CR, Spectrum sensing is one of its important key functionalities. It is used to sense the unused spectrum in an opportunistic manner. Energy detection constitutes a preferred approach for spectrum sensing in cognitive radio due to its simplicity and applicability. The conventional energy detection technique, which is based upon fixed threshold, is sensitive to noise uncertainty which is unavoidable in practical cases. This noise uncertainty gets the fixed threshold energy detector un-optimized in its performance. In this paper, an efficient energy detector is proposed for optimal CR performance. The proposed scheme is based upon a dynamic threshold energy detection algorithm, in which, the decision threshold is toggled between two levels based upon the average energy received from the primary user (PU) during a specified period of observation. Thresholds evaluations are based upon estimating the noise uncertainty factor. These thresholds are used to maximize the probability of detection (Pd) and minimize the probability of false alarm (Pfa). Theoretical analysis and simulation results show the effectiveness of the proposed scheme in comparison to the conventional energy detection method with less increase in complexity.

Spectrum Sensing (SS) constitutes the most critical task in Cognitive Radio (CR) systems for Primary User (PU) detection. Cooperative Spectrum Sensing (CSS) is introduced to enhance the detection reliability of the PU in fading environments. In this paper, we propose a soft decision based CSS algorithm using energy detection by taking into account the noise uncertainty effect. In the proposed algorithm, two threshold levels are utilized based on predicting the current PU activity, which can be successfully expected using a simple successive averaging process with time. The two threshold levels are evaluated based on estimating the noise uncertainty factor. In addition, they are toggled in a dynamic manner to compensate the noise uncertainty effect and to increase the probability of detection and decrease the probability of false alarm. Theoretical analysis is performed on the proposed algorithm to evaluate its enhanced false alarm and detection probabilities over the conventional soft decision CSS using different combining schemes. In addition, simulation results show the high efficiency of the proposed scheme compared to the conventional soft decision CSS, with high computational complexity enhancements.

Abstract-Spectrum Sensing (SS) is one of the most challenging issues in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed to enhance the detection reliability of a Primary User (PU) in fading environments. In this paper, we propose a hard decision based CSS algorithm using energy detection with taking into account the noise uncertainty effect. In the proposed algorithm, two dynamic thresholds are toggled based on predicting the current PU activity, which can be successfully expected using a simple successive averaging process with time. Also, their values are evaluated using an estimated value of the noise uncertainty factor. These dynamic thresholds are used to compensate the noise uncertainty effect and increase (decrease) the probability of detection (false alarm), respectively. Theoretical analysis is performed on the proposed algorithm to deduce its enhanced false alarm and detection probabilities compared to the conventional hard decision CSS. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high performance of the proposed scheme compared to the conventional CSS using different fusion rules.