Abstract
Energy efficiency (EE) is of great concern in cognitive radio networks since the throughput and energy consumption of secondary users (SUs) vary with the sensing time. However, the conditions of the detection probability and false alarm probability should be respected to better protect primary users (PUs) and to improve the sensing performance of SUs. Additionally, the PUs’ minimum averaged power provision should also be regarded as a key problem of interactive linking to SUs. Therefore, an integrated design between the PU and SUs is desired for the coordination of the whole cognitive radio system, especially regarding the satisfaction of EE and performance metrics. This study formulates sensing constraints in a unified way and calculates the minimum SNR of SUs, based on which the essential PU power provision is computed. Furthermore, EE is proved as a decreasing function with the PU’s active ratio, where the maximum EE is obtained corresponding to the minimum QoS requirements of the sensing process. Hence, a bisection-based method is proposed to maximize EE, which is considered as a concave function of SUs’ sensing time and has only one unique optimum. EE’s optimization was analyzed under different fusion rules for diverse SNR conditions. The optimum was also studied with sensing performance targets for various cases of PU power provision.
Highlights
We prove that a maximized EE is subject to a sparse presence of a primary users (PUs), similar to the PU1 case in Figure 1, where the assumption of free access is admitted as a principal impact, rather than the advantage of the false alarm probabilities of PU2
The main error risks in cognitive radio networks (CRNs) are expressed in two aspects: (1) a false alarm describes that secondary users (SUs) receives 1 and falls into sleep while the channel is available, which leads to spectrum waste; (2) miss detection indicates that SU receives 0 and starts transmission while the channel is occupied by PU, which increases the probability of a collision between the PU
We assume that the transmit power of the PU is determined as E pt and the gain of the fading channel is given as G for both primary and secondary users
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Achieve adethe spectrum band is shared among the and SUs, the reuse of the spectrum is strongly quate sensing performance by solving a quadratic equation at the minimum condition relatedof toSNR the PU’s presence which determine whether sufficient networks received at thecharacteristics, SUs; resources are left for other. Analysis quate sensing performance by solving a quadratic equation at the minimum condition of SNR received at works the SUs; In the literature, recent have mainly proposed new spectrum sensing techniques or (2)models It formulates the EE asEE a constrained three-dimensional optimization and optimized the or the sensing performances adaptively.
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