One of the most important technical challenges when designing a Cognitive Radio Networks (CRNs) is spectrum sensing, which has the responsibility of recognizing the presence or absence of the primary users in the frequency bands. A common technique used for spectrum sensing is double energy detection since it can operate without any prior information regarding the characteristics of the primary user signals. A double threshold energy detection algorithm is based on the use of two thresholds, to check the energy of the received signals and decided whether the spectrum is occupied or not. Furthermore, thresholds play a key role in the energy detection algorithm, by considering the stochastic features of noise in this model, as a result calculating the optimal threshold is a crucial task. In this paper, the Bi-Section algorithm was used to detect the optimum energy level in the fuzzy region which is an area between the low and high energy threshold. For this purpose, the decision threshold was determined by the use of the Bisection function for cognitive users. Numerical simulations show that the proposed method achieves better detection performance than the conventional double-threshold energy-sensing schemes. Moreover, the presented technique has advantages such as increasing the probability of detection of primary users and decreasing the probability of Collison between primary and secondary users.
翻译:设计认知式无线电网络(CRNs)时最重要的技术挑战之一是频谱感测,其责任是承认频率波段中主要用户的存在或不存在。频谱感测使用的一种常见技术是双能量探测,因为它可以在不事先提供关于初级用户信号特点的任何信息的情况下操作。双门槛能量检测算法以使用两个阈值为基础,以检查所接收信号的能量并决定频谱是否占据。此外,阈值在能源检测算法中发挥着关键作用,因为考虑到这一模型中噪音的随机特征,因此计算最佳阈值是一项关键任务。在本文件中,双节算法用于探测模糊区域的最佳能源水平,而这个区域是低和高能源阈值之间的一个区域。为此,决定阈值是通过对认知用户使用比克函数确定的。数值模拟表明,拟议方法比传统的双峰能源测量计划取得更好的检测性表现。此外,所提出的技术具有优势,例如增加了初级用户的检测概率和第二位用户之间的概率。