This paper presents, optimization analysis of energy detection based cooperative spectrum sensing system (CSSS) with hard-decision combining. Several system parameters are optimized to evaluate an optimal performance theoretically over noisy and generalized fading channels. In particular, wireless environments with noise plus \(\kappa -\mu \) and \(\eta -\mu \) fading are considered in the sensing channels. More precisely, each secondary user (SU, also called as cognitive radio user) depend on an energy detector (ED). The SU collects the signal from the primary user (PU), is given as input to the ED, and the energy of the signal is calculated for making a binary decision locally. The locally obtained decisions are combined using hard-decision combining and a final decision about position of the PU is made. In this work, the novel mathematical expressions for detection probability of a single SU is derived first, subject to noise plus fading and validated by using Monte Carlo simulations. Next, we develop theoretical frame works for optimization analysis of CSSS using derived mathematical expressions. The channel error probability is considered in both sensing and reporting channels. Further, we derive closed-form optimal expressions of number of SUs and detection threshold subject to generalized fading and optimal values are calculated. Through receiver operating characteristics (ROC), complementary ROC and total error rate, system performance is evaluated for the significant influence of channel and network parameters. Finally, the influence of the generalized fading severity parameters, the signal-to-noise ratio (SNR), the number of SUs, the detection threshold, and the channel error probability on the performance of CSSS is also investigated.

本文提出了基于能量检测的带硬决策的协同频谱感知系统（CSSS）的优化分析。对几个系统参数进行了优化，以在理论上评估噪声和广义衰落信道上的最佳性能。特别是在噪声加\（\ kappa-\ mu \）和\（\ eta-\ mu \）的无线环境中在感测通道中考虑了衰落。更准确地说，每个辅助用户（SU，也称为认知无线电用户）都依赖于能量检测器（ED）。SU收集来自主要用户（PU）的信号，作为对ED的输入，并计算信号的能量，以便在本地做出二进制决策。使用硬决策组合来组合本地获得的决策，并做出有关PU位置的最终决策。在这项工作中，首先推导了用于单个SU的检测概率的新颖数学表达式，该表达式受噪声加衰减的影响，并使用蒙特卡洛模拟进行了验证。接下来，我们使用派生的数学表达式开发用于CSSS优化分析的理论框架。在感测和报告信道中都考虑了信道错误概率。进一步，我们推导了SU数量和检测阈值的封闭形式最优表达式，这些阈值经过广义衰落并计算出最优值。通过接收器工作特性（ROC），互补的ROC和总错误率，可以评估系统性能对信道和网络参数的重大影响。最后，还研究了广义衰落严重性参数，信噪比（SNR），SU数量，检测阈值和信道错误概率对CSSS性能的影响。评估系统性能对信道和网络参数的重大影响。最后，还研究了广义衰落严重性参数，信噪比（SNR），SU数量，检测阈值和信道错误概率对CSSS性能的影响。评估系统性能对信道和网络参数的重大影响。最后，还研究了广义衰落严重性参数，信噪比（SNR），SU数量，检测阈值和信道错误概率对CSSS性能的影响。