Proper utilization of the unused spectrum hole facilitates the expanding necessity of the elevated data rate in the upcoming 5th Generation (5G) wireless communication technology. Energy detection is a widely worked technique to fulfill this requirement with minimal time, cost, and efforts. With this motivation, this work develops an analytical framework to analyze the functioning of an energy detector (ED) based cognitive radio (CR) system over a composite fading distribution, characterized by $\alpha$-$\mu$/Inverse-Gamma (I-Gamma) composite fading channel. To begin with, closed-form expressions for the probability density function (PDF) are developed for single-input single-output (SISO) and single-input multiple-output (SIMO) channels. Exploiting these expressions, analytical results for the average probability of detection (PD) and the average area under the receiver operating characteristic curve (AUC) are obtained. Further, the breakdown is extended in determining average PD under high and very low signal-to-noise ratio (SNR) regime. Finally, the results are utilized as an application in analyzing the cooperative spectrum sensing (CSS) under different shadowing conditions. The optimization of the number of cognitive radios is carried out using the r-out-of-N voting rule. The validation of all the proposed results and their accuracy is determined using the Monte-Carlo simulations.

正确利用未使用的频谱孔将促进在即将到来的第五代（5G）无线通信技术中提高数据速率的必要性。能量检测是一项广泛使用的技术，可以用最少的时间，成本和精力来满足这一要求。以此动机为基础，这项工作建立了一个分析框架，以分析基于能量检测器（ED）的认知无线电（CR）系统在复合衰落分布上的功能，其特点是$\alpha$--$\mu$/反伽玛（I-Gamma）复合衰落信道。首先，针对单输入单输出（SISO）和单输入多输出（SIMO）通道开发了概率密度函数（PDF）的闭式表达式。利用这些表达式，可以获得平均检测概率（PD）和接收器工作特性曲线（AUC）下平均面积的分析结果。此外，在确定高和极低信噪比（SNR）方案下的平均PD时，击穿得到了扩展。最后，该结果可用于分析不同阴影条件下的协作频谱感知（CSS）。使用N的r-out-of-N对认知无线电的数量进行优化投票规则。所有提议的结果及其准确性的验证是使用蒙特卡洛模拟确定的。