Abstract
The rapid development in the area of cognitive radio technology leads the society to higher standards of spectrum sensing performance, particularly in low signal-to-noise ratio (SNR) environment. This article proposes an adaptive double-threshold energy sensing method based on Markov model (ADEMM). When using the double-threshold energy sensing method, the modified Markov model that accounts for the time varying characteristic of the channel occupancy was presented to resolve the ‘confused’ channel state. Furthermore, in order to overcome the effect of noise uncertainty, the findings of this article introduce an adaptive double-threshold spectrum sensing method that adjusts its thresholds according to the achievable maximal detection probability. Numerical simulations show that the proposed ADEMM achieves better detection performance than the conventional double-threshold energy sensing schemes, especially in very low SNR region.
Highlights
Recent decades witnessed a dramatic increase in the number of wireless communication users
According to Federal Communications Commission’s (FCC) recent study report [1], the assigned spectrum is not being fully utilized at a specific time and at particular geographic location resulting in a lot of underutilized spectrum resources
In the Cognitive radio (CR)-based system, the secondary user (SU) exploits the spectrum opportunity, which is defined as the frequency channel that is temporarily not used by the primary users (PUs) [2]
Summary
Recent decades witnessed a dramatic increase in the number of wireless communication users. In Ref [7], a new cooperative spectrum sensing scheme based on two-stage detectors was proposed, which chose single threshold during the first stage and double-threshold in the second stage. Another two-step spectrum sensing scheme to improve detection performance was put forward in Ref [8], which consists of two sensing methods, respectively, double-threshold energy sensing in the first step and cyclostationarity-based sensing in the second step It is computationally complex and requires longer sensing time. In Ref [9], a double-threshold method is applied to perform spectrum sensing, while the local energy detection results are divided into a hard decision and soft decision. Decision H0 or H1 will be made when the energy of the PU signal in this sub-channel is less or greater than the threshold value Vth, respectively. The probability of detection Pd and the probability of missing Pm can be identified
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