## 5 Simulation Results
However, in the framework of the novel ST-CSS scheme, the sensing performance can be further enhanced with extended equivalent sensing duration, which can compensate the loss of average throughput resulted from the less transmission time. It is further summarized that the proposed ST-CSS scheme is less sensitive to reporting time and significantly improves SU spectral efficiency. Figure 9: SU spectral efficiency \(\hat{C}\) versus \(\hat{Q}_{d}^{th}\) for the scheme of Novel ST-CSS and General CSS under decision fusion rules of OFR, MFR and AFR, respectively. Figure 11 contrasts spectrum utilization efficiency of the proposed ST-CSS with the schemes of energy efficient design in [34] and transmission delay efficient design in [35], which satisfies the interference constraint on PU (i.e., \(\hat{Q}_{d}^{th}=0.9\)). As is depicted in Figure 11, our proposed ST-CSS scheme aiming at maximizing spectral efficiency in Equation (58) provides the highest spectral efficiency, in all values of SNR, while energy efficient design is sub-optimal in lower SNR and delay efficient design becomes sub-optimal in higher SNR. Numerically, the proposed solution improves 1% to 21% and 1% to 19% more spectral efficiency than delay efficient design and energy efficient design in all values of SNR, and the degrees of improvement of the spectral efficiency is determined by SNR. This is because the goal of transmission delay efficient design is to design the sensing parameters that can minimize the SU transmission delay in the scenario of delay sensitive applications, while the goal of energy efficient design is to design the sensing parameters that can maximize the energy efficiency in energy limited CR network with the same fixed frame length. Furthermore, the complexity of those three schemes are equivalent, because they differ only from optimization target in corresponding scenario with the similar main steps as Algorithm 1 presents. Specially, our proposed scheme is more suitable to overcome the problem of spectrum scarcity. Figure 11: Comparisons of SU spectral efficiency among the schemes of the proposed ST-CSS, the transmission delay efficient design and the energy efficient design. Figure 10: Spectral efficiency versus number of cooperating SU for the novel ST-CSS scheme and the general CSS scheme under different values of reporting time. In order to evaluate the energy consumption of the proposed ST-CSS method in scenario of energy limited CR system, Figure 12 illustrates the SU energy efficiency and spectral efficiency of the novel ST-CSS scheme versus the number of cooperating SU synchronously. In this simulation, the energy efficient design in [34] is utilized to obtain the energy efficiency. Meanwhile, the optimal sensing time and the optimal combining rule are employed to obtain the SU spectral efficiency. It can be observed that the SU spectral efficiency enhances when \(K\) increases as a result of the improved cooperative sensing performance. However, energy efficiency will decrease as \(K\) increases, because more energy will be consumed to implement cooperative sensing and report sensing results. Though the more cooperative secondary sensor nodes in novel ST-CSS scheme can afford better spectral efficiency, it would shorten the CR networks lifetime due to increasing energy consumption.