The upcoming sixth generation (6 G) systems can meet the high user demands. The existing communication systems are becoming inefficient in meeting the user demands. The multifold growth in the usage of high-definition multimedia applications requires new capabilities. The users are looking forward to high throughput and low latency. The shift from 5 G to 6 G networks is since the 6 G networks are expected to combine the terrestrial, aerial, and maritime communications into a robust network. This will provide the users a faster network with high reliability, accommodation to a larger number of users, and ultra-low latency. However, the limited availability of spectrum is a bottleneck in enhancing the user experience. Therefore, advanced techniques like cognitive radios and cooperative spectrum sensing are critical in the design of future network. The optimal usage and management of the available spectrum is significant for the performance of the network. In this paper, a cooperative spectrum sensing technique using Manta Ray Foraging Algorithm (MRFO) is proposed. The weighting vector at the fusion center is optimized using MRFO. The allocation of the spectrum is done using the optimal weight vector for secondary users. The proposed work aims at finding the maximum probability of detection. Probability of detection is significant in spectrum sensing. The channel needs to be sensed for the presence or absence of primary users. If the detection probability is maximized, then the channel usage efficiency will increase. The proposed method is compared with other state of the art methods. The results show that MRFO can be used efficiently for spectrum sharing by cognitive radios.

即将推出的第六代（6G）系统可以满足用户的高需求。现有的通信系统在满足用户需求方面变得效率低下。高清多媒体应用使用的成倍增长需要新的功能。用户期待高吞吐量和低延迟。从 5G 到 6G 网络的转变是因为 6G 网络有望将地面、空中和海上通信结合成一个强大的网络。这将为用户提供速度更快、可靠性高、适应更多用户和超低延迟的网络。然而，频谱的有限可用性是增强用户体验的瓶颈。因此，认知无线电和协作频谱感知等先进技术在未来网络的设计中至关重要。可用频谱的最佳使用和管理对于网络的性能非常重要。在本文中，提出了一种使用蝠鲼觅食算法（MRFO）的协作频谱感知技术。融合中心的加权向量使用 MRFO 进行优化。频谱的分配是使用次要用户的最佳权重向量完成的。拟议的工作旨在找到最大的检测概率。检测概率在频谱感知中很重要。需要感知信道是否存在主要用户。如果检测概率最大化，则信道使用效率将提高。将所提出的方法与其他最先进的方法进行比较。结果表明，MRFO 可以有效地用于认知无线电的频谱共享。